Topic Editors

Department of Information Engineering, University of Padova, 35131 Padova, Italy
Department of Movement, Human and Health Science, Università degli Studi di Roma "Foro Italico", Piazza L. de Bosis 6, 00135 Rome, Italy
1. Gait & Motion Analysis Laboratory, Sol et Salus Hospital, viale San Salvador 204, Rimini, 47922 Torre Pedrera di Rimini, Italy
2. LAM-Motion Analysis Laboratory, San Sebastiano Hospital, Correggio, Neuromotor and Rehabilitation Department, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy

Human Movement Analysis

Abstract submission deadline
closed (31 January 2023)
Manuscript submission deadline
closed (30 April 2023)
Viewed by
119469

Topic Information

Dear Colleagues,

Human movement analysis has become very popular in different domains, such as clinical gait analysis, rehabilitation, robotics, sports science, animation and entertainment, video surveillance, and smart houses. The challenge for healthcare professionals, sports biomechanists, and researchers is to study the mechanics of motion and their correlation with various pathologies and/or injuries affecting the musculoskeletal system in less-constrained environments beyond laboratory settings. Recently, there has been great emphasis on the application and development of different sensors and, in particular, wearable sensing technologies that offer exciting opportunities for the continuous monitoring of human kinematics and kinetics in free-living conditions. The aim of this Topic Collection is to present recent findings on the development and application of sensor technologies for measurements of human movement.

In particular, this Topic Collection will report on various sensors, such as video recording sensors, IMU (inertial measurement units) plantar pressure sensors, and electromyography. Authors are encouraged to submit manuscripts for publication in (but not limited to) the following areas:

  • Biomechanical sensors in disease assessment, functional diagnosis, treatment, and rehabilitation;
  • Sensors for movement analysis for assisted living monitoring;
  • Biomechanical sensors in gait analysis;
  • Biomechanical sensors in sports;
  • Movement analysis through dynamic electromyography;
  • Plantar pressure analysis and gaitography;
  • Magneto-inertial sensors for human motion tracking;
  • Force sensors (strain gauge, piezo, etc.);
  • Ultrasound sensors for human movement analysis;
  • Goniometers;
  • Optical tracking systems;
  • Challenges in data processing, simulation, and validation for human movement analysis;
  • Challenges in data sensor fusion for human movement analysis;
  • Technical challenges in assuring the accuracy and robustness of the provided measures (i.e., sensor placement, measurement drift, repeatability of the provided measures);
  • Wireless sensors for human motion tracking;
  • Movement analysis and brain activity through mobile assessment (EEG, fNIRS,…)
  • Novel applications in the continuous monitoring of human motion in rehabilitation;
  • Measuring biomechanics of either the whole body or individual parts of the body.

Dr. Zimi Sawacha
Dr. Giuseppe Vannozzi
Dr. Andrea Merlo
Topic Editors

Keywords

  • human motion analysis
  • sensors for motion analysis
  • clinical gait analysis
  • human movement biomechanics
  • sport biomechanics
  • wearable sensors

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.7 4.5 2011 16.9 Days CHF 2400
Automation
automation
- - 2020 26.3 Days CHF 1000
Biomechanics
biomechanics
- - 2021 23.8 Days CHF 1000
Sensors
sensors
3.9 6.8 2001 17 Days CHF 2600
Bioengineering
bioengineering
4.6 4.2 2014 17.7 Days CHF 2700

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Published Papers (51 papers)

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17 pages, 8831 KiB  
Article
A Transformer-Based Neural Network for Gait Prediction in Lower Limb Exoskeleton Robots Using Plantar Force
by Jiale Ren, Aihui Wang, Hengyi Li, Xuebin Yue and Lin Meng
Sensors 2023, 23(14), 6547; https://doi.org/10.3390/s23146547 - 20 Jul 2023
Viewed by 1283
Abstract
Lower limb exoskeleton robots have shown significant research value due to their capabilities of providing assistance to wearers and improving physical motion functions. As a type of robotic technology, wearable robots are directly in contact with the wearer’s limbs during operation, necessitating a [...] Read more.
Lower limb exoskeleton robots have shown significant research value due to their capabilities of providing assistance to wearers and improving physical motion functions. As a type of robotic technology, wearable robots are directly in contact with the wearer’s limbs during operation, necessitating a high level of human–robot collaboration to ensure safety and efficacy. Furthermore, gait prediction for the wearer, which helps to compensate for sensor delays and provide references for controller design, is crucial for improving the the human–robot collaboration capability. For gait prediction, the plantar force intrinsically reflects crucial gait patterns regardless of individual differences. To be exact, the plantar force encompasses a doubled three-axis force, which varies over time concerning the two feet, which also reflects the gait patterns indistinctly. In this paper, we developed a transformer-based neural network (TFSformer) comprising convolution and variational mode decomposition (VMD) to predict bilateral hip and knee joint angles utilizing the plantar pressure. Given the distinct information contained in the temporal and the force-space dimensions of plantar pressure, the encoder uses 1D convolution to obtain the integrated features in the two dimensions. As for the decoder, it utilizes a multi-channel attention mechanism to simultaneously focus on both dimensions and a deep multi-channel attention structure to reduce the computational and memory consumption. Furthermore, VMD is applied to networks to better distinguish the trends and changes in data. The model is trained and tested on a self-constructed dataset that consists of data from 35 volunteers. The experimental results show that FTSformer reduces the mean absolute error (MAE) up to 10.83%, 15.04% and 8.05% and the mean squared error (MSE) by 20.40%, 29.90% and 12.60% compared to the CNN model, the transformer model and the CNN transformer model, respectively. Full article
(This article belongs to the Topic Human Movement Analysis)
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11 pages, 3814 KiB  
Communication
Optimum Handle Location for the Hand-Assisted Sit-to-Stand Transition: A Tool
by Arash Bagheri and Keith Alexander
Biomechanics 2023, 3(2), 267-277; https://doi.org/10.3390/biomechanics3020023 - 14 Jun 2023
Viewed by 973
Abstract
Background: The aging process contributes to the decline in physical capacity that leads to loss of independence in performing life activities. Immobility and instability are the most significant predictors and indicators of physical disability and dependence. As a result, a variety of assistive [...] Read more.
Background: The aging process contributes to the decline in physical capacity that leads to loss of independence in performing life activities. Immobility and instability are the most significant predictors and indicators of physical disability and dependence. As a result, a variety of assistive devices exist to address immobility and instability in older adults, including walkers, canes, crutches, wheelchairs and handrails. Sit-to-stand (STS) transitions are the most common transitions in daily mobility activities. The ability to perform STS transitions successfully is therefore one of the most important activities to focus attention on. As a result of physical deterioration, older adults will sooner or later be faced with their physical limitations, and in particular, will not be able to provide enough torque at critical body joints to make the STS transition. Aim: This paper suggests employing two-arm assistance using two handles located symmetrically in the body’s sagittal plane. During the aging process, people are faced with varying levels of muscle deterioration and body constraints and consequently require different levels of assistance to complete the transition successfully. This paper aims to develop a tool to find the optimum handle location for people based on their body constraints to reduce knee torque (identified as the critical joint in the STS transition). These findings are also used to measure the effects of assistive device handle position on the biomechanics of the two-arm assisted STS transition. Methods: For this purpose, a theoretical tool was developed by integrating human body kinetics with a multi-objective genetic algorithm to find the optimum hand force required at the seat-off point for a set of potential handle locations. The tool was set to achieve the minimum knee torque within the defined body constraints and assumptions. In line with the physics of the STS transition, the “seat-off point”, when subjects lose their seat support, was chosen as the most challenging point of the task. This was coupled with the “nose over toes” posture recommended to older adults by occupational therapists. Results and Discussion: The schematic of the developed tool shows that the best handle locations requiring the minimum torques at the body joints are positioned in handle zone 2, where the handles are placed vertically above the knee and below the hip joints and horizontally located ahead of the hip and behind the knee joints. Within this handle zone, both components of the hand forces (vertical downward and horizontal backward) provide assisting torque to all the body joints and consequently reduce the torques required at body joints. Full article
(This article belongs to the Topic Human Movement Analysis)
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8 pages, 690 KiB  
Case Report
Effects of Game-Specific Demands on Accelerations during Change of Direction Movements: Analysis of Youth Female Soccer
by Aki-Matti Alanen, Lauren C. Benson, Matthew J. Jordan, Reed Ferber and Kati Pasanen
Biomechanics 2023, 3(2), 250-257; https://doi.org/10.3390/biomechanics3020021 - 29 May 2023
Cited by 1 | Viewed by 1393
Abstract
The aim of this study was to assess center of mass (COM) acceleration and movement during change of direction (COD) maneuvers during a competitive soccer game to elucidate situation-specific demands of COD performance. This information can assist in developing soccer-specific tests and training [...] Read more.
The aim of this study was to assess center of mass (COM) acceleration and movement during change of direction (COD) maneuvers during a competitive soccer game to elucidate situation-specific demands of COD performance. This information can assist in developing soccer-specific tests and training methods. Fifteen elite-level female youth soccer players were tracked for one game with inertial measurement units (IMU) attached to the lower back. COD movements in combination with situational patterns were identified using high-speed video. LASSO regression was used to identify the most important predictors associated with higher vertical peak accelerations (PAv) of the COM during COD movements. COD angle, running speed, contact, and challenge from the opposition were identified as important features related to higher PAv. This study adds to the literature on the demands of COD performance in soccer match-play. The unique approach with game-specific situational data from female youth players provides increased insight into the game-demands of COD and agility performance. PAv in games was higher with larger COD angles, increased running speed, or with contact when the player was challenged by the opposition. A larger study including more games is warranted to increase confidence in using these variables as a basis for training or testing agility. Full article
(This article belongs to the Topic Human Movement Analysis)
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17 pages, 994 KiB  
Article
The Classification of Movement in Infants for the Autonomous Monitoring of Neurological Development
by Alexander Turner, Stephen Hayes and Don Sharkey
Sensors 2023, 23(10), 4800; https://doi.org/10.3390/s23104800 - 16 May 2023
Cited by 1 | Viewed by 1345
Abstract
Neurodevelopmental delay following extremely preterm birth or birth asphyxia is common but diagnosis is often delayed as early milder signs are not recognised by parents or clinicians. Early interventions have been shown to improve outcomes. Automation of diagnosis and monitoring of neurological disorders [...] Read more.
Neurodevelopmental delay following extremely preterm birth or birth asphyxia is common but diagnosis is often delayed as early milder signs are not recognised by parents or clinicians. Early interventions have been shown to improve outcomes. Automation of diagnosis and monitoring of neurological disorders using non-invasive, cost effective methods within a patient’s home could improve accessibility to testing. Furthermore, said testing could be conducted over a longer period, enabling greater confidence in diagnoses, due to increased data availability. This work proposes a new method to assess the movements in children. Twelve parent and infant participants were recruited (children aged between 3 and 12 months). Approximately 25 min 2D video recordings of the infants organically playing with toys were captured. A combination of deep learning and 2D pose estimation algorithms were used to classify the movements in relation to the children’s dexterity and position when interacting with a toy. The results demonstrate the possibility of capturing and classifying children’s complexity of movements when interacting with toys as well as their posture. Such classifications and the movement features could assist practitioners to accurately diagnose impaired or delayed movement development in a timely fashion as well as facilitating treatment monitoring. Full article
(This article belongs to the Topic Human Movement Analysis)
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11 pages, 968 KiB  
Article
Association of the Degree of Varus Thrust during Gait Assessed by an Inertial Measurement Unit with Patient-Reported Outcome Measures in Knee Osteoarthritis
by Shogo Misu, So Tanaka, Jun Miura, Kohei Ishihara, Tsuyoshi Asai and Tomohiko Nishigami
Sensors 2023, 23(10), 4578; https://doi.org/10.3390/s23104578 - 09 May 2023
Viewed by 1775
Abstract
This study aimed to assess the association between the degree of varus thrust (VT) assessed by an inertial measurement unit (IMU) and patient-reported outcome measures (PROMs) in patients with knee osteoarthritis. Seventy patients (mean age: 59.8 ± 8.6 years; women: n = 40) [...] Read more.
This study aimed to assess the association between the degree of varus thrust (VT) assessed by an inertial measurement unit (IMU) and patient-reported outcome measures (PROMs) in patients with knee osteoarthritis. Seventy patients (mean age: 59.8 ± 8.6 years; women: n = 40) were instructed to walk on a treadmill with an IMU attached to the tibial tuberosity. For the index of VT during walking (VT-index), the swing-speed adjusted root mean square of acceleration in the mediolateral direction was calculated. As the PROMs, the Knee Injury and Osteoarthritis Outcome Score were used. Data on age, sex, body mass index, static alignment, central sensitization, and gait speed were collected as potential confounders. After adjusting for potential confounders, multiple linear regression analysis revealed that the VT-index was significantly associated with the pain score (standardized β = −0.295; p = 0.026), symptoms score (standardized β = −0.287; p = 0.026), and activities of the daily living score (standardized β = −0.256; p = 0.028). Our results indicated that larger VT values during gait are associated with worse PROMs, suggesting that an intervention to reduce VT might be an option for clinicians trying to improve PROMs. Full article
(This article belongs to the Topic Human Movement Analysis)
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14 pages, 1726 KiB  
Article
Estimating the Standing Long Jump Length from Smartphone Inertial Sensors through Machine Learning Algorithms
by Beatrice De Lazzari, Guido Mascia, Giuseppe Vannozzi and Valentina Camomilla
Bioengineering 2023, 10(5), 546; https://doi.org/10.3390/bioengineering10050546 - 29 Apr 2023
Viewed by 1881
Abstract
The length of the standing long jump (SLJ) is widely recognized as an indicator of developmental motor competence or sports conditional performance. This work aims at defining a methodology to allow athletes/coaches to easily measure it using the inertial measurement units embedded on [...] Read more.
The length of the standing long jump (SLJ) is widely recognized as an indicator of developmental motor competence or sports conditional performance. This work aims at defining a methodology to allow athletes/coaches to easily measure it using the inertial measurement units embedded on a smartphone. A sample group of 114 trained young participants was recruited and asked to perform the instrumented SLJ task. A set of features was identified based on biomechanical knowledge, then Lasso regression allowed the identification of a subset of predictors of the SLJ length that was used as input of different optimized machine learning architectures. Results obtained from the use of the proposed configuration allow an estimate of the SLJ length with a Gaussian Process Regression model with a RMSE of 0.122 m in the test phase, Kendall’s τ < 0.1. The proposed models give homoscedastic results, meaning that the error of the models does not depend on the estimated quantity. This study proved the feasibility of using low-cost smartphone sensors to provide an automatic and objective estimate of SLJ performance in ecological settings. Full article
(This article belongs to the Topic Human Movement Analysis)
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19 pages, 2503 KiB  
Article
Machine Learning for Optical Motion Capture-Driven Musculoskeletal Modelling from Inertial Motion Capture Data
by Abhishek Dasgupta, Rahul Sharma, Challenger Mishra and Vikranth Harthikote Nagaraja
Bioengineering 2023, 10(5), 510; https://doi.org/10.3390/bioengineering10050510 - 24 Apr 2023
Cited by 4 | Viewed by 2477
Abstract
Marker-based Optical Motion Capture (OMC) systems and associated musculoskeletal (MSK) modelling predictions offer non-invasively obtainable insights into muscle and joint loading at an in vivo level, aiding clinical decision-making. However, an OMC system is lab-based, expensive, and requires a line of sight. Inertial [...] Read more.
Marker-based Optical Motion Capture (OMC) systems and associated musculoskeletal (MSK) modelling predictions offer non-invasively obtainable insights into muscle and joint loading at an in vivo level, aiding clinical decision-making. However, an OMC system is lab-based, expensive, and requires a line of sight. Inertial Motion Capture (IMC) techniques are widely-used alternatives, which are portable, user-friendly, and relatively low-cost, although with lesser accuracy. Irrespective of the choice of motion capture technique, one typically uses an MSK model to obtain the kinematic and kinetic outputs, which is a computationally expensive tool increasingly well approximated by machine learning (ML) methods. Here, an ML approach is presented that maps experimentally recorded IMC input data to the human upper-extremity MSK model outputs computed from (‘gold standard’) OMC input data. Essentially, this proof-of-concept study aims to predict higher-quality MSK outputs from the much easier-to-obtain IMC data. We use OMC and IMC data simultaneously collected for the same subjects to train different ML architectures that predict OMC-driven MSK outputs from IMC measurements. In particular, we employed various neural network (NN) architectures, such as Feed-Forward Neural Networks (FFNNs) and Recurrent Neural Networks (RNNs) (vanilla, Long Short-Term Memory, and Gated Recurrent Unit) and a comprehensive search for the best-fit model in the hyperparameters space in both subject-exposed (SE) as well as subject-naive (SN) settings. We observed a comparable performance for both FFNN and RNN models, which have a high degree of agreement (ravg,SE,FFNN=0.90±0.19, ravg,SE,RNN=0.89±0.17, ravg,SN,FFNN=0.84±0.23, and ravg,SN,RNN=0.78±0.23) with the desired OMC-driven MSK estimates for held-out test data. The findings demonstrate that mapping IMC inputs to OMC-driven MSK outputs using ML models could be instrumental in transitioning MSK modelling from ‘lab to field’. Full article
(This article belongs to the Topic Human Movement Analysis)
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12 pages, 429 KiB  
Article
Inter-Professional and Methodological Agreement in Using the Cutting Movement Assessment Score (CMAS)
by Paul A. Jones, Ali Rai, Thomas Dos’Santos and Lee C. Herrington
Biomechanics 2023, 3(2), 181-192; https://doi.org/10.3390/biomechanics3020016 - 07 Apr 2023
Cited by 1 | Viewed by 1324
Abstract
Background: The cutting movement assessment score (CMAS) provides a qualitative assessment of the side-step cutting (S-SC) technique. Previous research has been undertaken primarily by biomechanists experienced with S-SC evaluations. Little is known about the agreement between various sports science and medicine practitioners to [...] Read more.
Background: The cutting movement assessment score (CMAS) provides a qualitative assessment of the side-step cutting (S-SC) technique. Previous research has been undertaken primarily by biomechanists experienced with S-SC evaluations. Little is known about the agreement between various sports science and medicine practitioners to ascertain whether the tool can be used effectively by different practitioners in the field. Currently, the CMAS uses three camera views (CVS) to undertake the evaluation, and it would be worthwhile to know whether the CMAS can be effectively conducted with fewer camera views to improve clinical utility. Therefore, the aim of the study was to examine the inter-rater agreement between different sports science and medicine practitioners and agreement between using different CVS to evaluate the S-SC technique using the CMAS. Methods: Video data were collected from 12 male rugby union players performing a 45° S-SC manoeuvre toward both the left and right directions. Five different sports science and medicine practitioners evaluated footage from three cameras of one left and one right trial from each player using the CMAS. Twelve different trials were also evaluated by the sports rehabilitator using single and multiple CVS. Agreements (percentage; Kappa coefficients (K)) between different practitioners and configurations of the CVS were explored. Results: Good to excellent inter-rater agreements were found between all practitioners for total score (K = 0.63–0.84), with moderate to excellent inter-rater agreements observed across all items of the CMAS (K = 0.5–1.0). Excellent agreement was found between using three CVS vs. two CVS that included at least a sagittal view (K = 0.96–0.97). Lower agreement (K = 0.83) was found between angle-frontal views with three CVS. Conclusions: The CMAS can be used effectively by various practitioners to evaluate the movement quality of S-SC. The use of two CVS that include at least a sagittal plane view would suffice to evaluate the S-SC technique against the CMAS. Full article
(This article belongs to the Topic Human Movement Analysis)
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9 pages, 1295 KiB  
Communication
Description of Telemark Skiing Technique Using Full Body Inertial Measurement Unit
by Piotr Aschenbrenner, Bartosz Krawczyński, Marcin Krawczyński, Tomasz Grzywacz and Włodzimierz Erdmann
Sensors 2023, 23(7), 3448; https://doi.org/10.3390/s23073448 - 25 Mar 2023
Viewed by 3386
Abstract
Researchers involved in skiing investigations postulate Telemark skiing as an alternative technique to Alpine skiing, which may be associated with lower injury risk. A free heel of the boot, and a boot that enables flexion of the toe, are characteristic features. The aim [...] Read more.
Researchers involved in skiing investigations postulate Telemark skiing as an alternative technique to Alpine skiing, which may be associated with lower injury risk. A free heel of the boot, and a boot that enables flexion of the toe, are characteristic features. The aim of this research was to compare three types of turns on Telemark skis, through a biomechanical description of each skiing technique. Seven professional skiers were investigated. Two cameras and the MyoMotion Research Pro system were utilized. Eighteen wireless IMU sensors were mounted on each skier’s body. For every skier, five runs were recorded for each of the three turning techniques. Velocity of run, range of movement, angular velocity in joints, time sequences, and order of initialization of movement were obtained. A higher velocity of skiing was obtained during the parallel (14.2 m/s) and rotational turns (14.9 m/s), compared to a low–high turn (8.9 m/s). A comparison of knee angles, revealed similar minimum (18 and 16 degrees) and maximum (143 and 147 degrees) values achieved during the parallel and rotational techniques, which differed considerably from the low–high technique (27 and 121 degrees, respectively). There were no significant differences in trunk rotation angles. A detailed analysis of the Telemark skiing technique revealed novel information on how turns are executed by well-trained skiers and the impact of different approaches. Full article
(This article belongs to the Topic Human Movement Analysis)
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16 pages, 4491 KiB  
Article
Myoelectric Pattern Recognition Using Gramian Angular Field and Convolutional Neural Networks for Muscle–Computer Interface
by Junjun Fan, Jiajun Wen and Zhihui Lai
Sensors 2023, 23(5), 2715; https://doi.org/10.3390/s23052715 - 01 Mar 2023
Cited by 1 | Viewed by 2340
Abstract
In the field of the muscle–computer interface, the most challenging task is extracting patterns from complex surface electromyography (sEMG) signals to improve the performance of myoelectric pattern recognition. To address this problem, a two-stage architecture, consisting of Gramian angular field (GAF)-based 2D representation [...] Read more.
In the field of the muscle–computer interface, the most challenging task is extracting patterns from complex surface electromyography (sEMG) signals to improve the performance of myoelectric pattern recognition. To address this problem, a two-stage architecture, consisting of Gramian angular field (GAF)-based 2D representation and convolutional neural network (CNN)-based classification (GAF-CNN), is proposed. To explore discriminant channel features from sEMG signals, sEMG-GAF transformation is proposed for time sequence signal representation and feature modeling, in which the instantaneous values of multichannel sEMG signals are encoded in image form. A deep CNN model is introduced to extract high-level semantic features lying in image-form-based time sequence signals concerning instantaneous values for image classification. An insight analysis explains the rationale behind the advantages of the proposed method. Extensive experiments are conducted on benchmark publicly available sEMG datasets, i.e., NinaPro and CagpMyo, whose experimental results validate that the proposed GAF-CNN method is comparable to the state-of-the-art methods, as reported by previous work incorporating CNN models. Full article
(This article belongs to the Topic Human Movement Analysis)
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12 pages, 16231 KiB  
Article
Effect of Aging on the Trunk and Lower Limb Kinematics during Gait on a Compliant Surface in Healthy Individuals
by Keita Honda, Yusuke Sekiguchi and Shin-Ichi Izumi
Biomechanics 2023, 3(1), 103-114; https://doi.org/10.3390/biomechanics3010010 - 24 Feb 2023
Viewed by 1880
Abstract
Older adults have a smaller effective living space and reduced physical activity. Although walking ability in various living spaces is necessary to maintain a healthy life and a high level of physical activity, it is unclear how older adults adapt to compliant surfaces [...] Read more.
Older adults have a smaller effective living space and reduced physical activity. Although walking ability in various living spaces is necessary to maintain a healthy life and a high level of physical activity, it is unclear how older adults adapt to compliant surfaces when walking. The purpose of this study was to determine the differences in the trunk and lower limb kinematics while walking on a level versus compliant surface, and the effect of aging on these kinematic changes. Twenty-two healthy individuals (aged from 20–80 years) were asked to walk along a 7-m walkway at a comfortable speed on a level and compliant surface. Gait kinematics were measured using a three-dimensional camera-based motion analysis system. We found that knee and hip flexion and ankle plantarflexion angles in the early stance phase and thoracic flexion angle throughout the gait cycle were significantly increased when walking on a compliant surface versus a level surface. The change in the thoracic flexion angle, ankle plantarflexion angle, and cadence between level and compliant surfaces was significantly correlated with age. Therefore, older adults use increased thoracic flexion and ankle plantarflexion angles along with a higher cadence to navigate compliant surfaces. Full article
(This article belongs to the Topic Human Movement Analysis)
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19 pages, 3955 KiB  
Article
Skeleton-Based Fall Detection with Multiple Inertial Sensors Using Spatial-Temporal Graph Convolutional Networks
by Jianjun Yan, Xueqiang Wang, Jiangtao Shi and Shuai Hu
Sensors 2023, 23(4), 2153; https://doi.org/10.3390/s23042153 - 14 Feb 2023
Cited by 4 | Viewed by 2176
Abstract
The application of wearable devices for fall detection has been the focus of much research over the past few years. One of the most common problems in established fall detection systems is the large number of false positives in the recognition schemes. In [...] Read more.
The application of wearable devices for fall detection has been the focus of much research over the past few years. One of the most common problems in established fall detection systems is the large number of false positives in the recognition schemes. In this paper, to make full use of the dependence between human joints and improve the accuracy and reliability of fall detection, a fall-recognition method based on the skeleton and spatial-temporal graph convolutional networks (ST-GCN) was proposed, using the human motion data of body joints acquired by inertial measurement units (IMUs). Firstly, the motion data of five inertial sensors were extracted from the UP-Fall dataset and a human skeleton model for fall detection was established through the natural connection relationship of body joints; after that, the ST-GCN-based fall-detection model was established to extract the motion features of human falls and the activities of daily living (ADLs) at the spatial and temporal scales for fall detection; then, the influence of two hyperparameters and window size on the algorithm performance was discussed; finally, the recognition results of ST-GCN were also compared with those of MLP, CNN, RNN, LSTM, TCN, TST, and MiniRocket. The experimental results showed that the ST-GCN fall-detection model outperformed the other seven algorithms in terms of accuracy, precision, recall, and F1-score. This study provides a new method for IMU-based fall detection, which has the reference significance for improving the accuracy and robustness of fall detection. Full article
(This article belongs to the Topic Human Movement Analysis)
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14 pages, 1536 KiB  
Article
Quantification of Cycling Smoothness in Children with Cerebral Palsy
by Ahad Behboodi, Ashwini Sansare and Samuel C. K. Lee
Biomechanics 2023, 3(1), 79-92; https://doi.org/10.3390/biomechanics3010008 - 06 Feb 2023
Viewed by 1318
Abstract
Smoothness is a hallmark of skilled, coordinated movement, however, mathematically quantifying movement smoothness is nuanced. Several smoothness metrics exist, each having its own limitations and may be specific to a particular motion such as upper limb reaching. To date, there is no consensus [...] Read more.
Smoothness is a hallmark of skilled, coordinated movement, however, mathematically quantifying movement smoothness is nuanced. Several smoothness metrics exist, each having its own limitations and may be specific to a particular motion such as upper limb reaching. To date, there is no consensus on which smoothness metric is the most appropriate for assessing cycling motion in children with cerebral palsy (CP). We evaluated the ability of four preexisting metrics, dimensionless jerk, spectral arc length measure, roughness index, and cross-correlation; and two new metrics, arc length and root mean square error, to quantify the smoothness of cycling in a preexisting dataset from children with CP (mean age 13.7 ± 2.6 years). First, to measure the repeatability of each measure in distinguishing between different levels of un-smoothness, we applied each metric to a set of simulated crank motion signals with a known number of aberrant revolutions using subjects’ actual crank angle data. Second, we used discriminant function analysis to statistically compare the strength of the six metrics, relative to each other, to discriminate between a smooth cycling motion obtained from a dataset of typically developed children (TD), the control group (mean age 14.9 ± 1.4 years), and a less smooth, halted cycling motion obtained from children with CP. Our results show that (1) ArcL showed the highest repeatability in accurately quantifying an unsmooth motion when the same cycling revolutions were presented in a different order, and (2) ArcL and DJ had the highest discriminatory ability to differentiate between an unsmooth and smooth cycling motion. Combining the results from the repeatability and discriminatory analysis, ArcL was the most repeatable and sensitive metric in identifying unsmooth, halted cycling motion from smooth motion. ArcL can hence be used as a metric in future studies to quantify changes in the smoothness of cycling motion pre- vs. post-interventions. Further, this metric may serve as a tool to track motor recovery not just in individuals with CP but in other patient populations with similar neurological deficits that may present with halted, unsmooth cycling motion. Full article
(This article belongs to the Topic Human Movement Analysis)
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17 pages, 2160 KiB  
Article
An Explainable Spatial-Temporal Graphical Convolutional Network to Score Freezing of Gait in Parkinsonian Patients
by Hyeokhyen Kwon, Gari D. Clifford, Imari Genias, Doug Bernhard, Christine D. Esper, Stewart A. Factor and J. Lucas McKay
Sensors 2023, 23(4), 1766; https://doi.org/10.3390/s23041766 - 04 Feb 2023
Cited by 4 | Viewed by 2287
Abstract
Freezing of gait (FOG) is a poorly understood heterogeneous gait disorder seen in patients with parkinsonism which contributes to significant morbidity and social isolation. FOG is currently measured with scales that are typically performed by movement disorders specialists (i.e., MDS-UPDRS), or through patient [...] Read more.
Freezing of gait (FOG) is a poorly understood heterogeneous gait disorder seen in patients with parkinsonism which contributes to significant morbidity and social isolation. FOG is currently measured with scales that are typically performed by movement disorders specialists (i.e., MDS-UPDRS), or through patient completed questionnaires (N-FOG-Q) both of which are inadequate in addressing the heterogeneous nature of the disorder and are unsuitable for use in clinical trials The purpose of this study was to devise a method to measure FOG objectively, hence improving our ability to identify it and accurately evaluate new therapies. A major innovation of our study is that it is the first study of its kind that uses the largest sample size (>30 h, N = 57) in order to apply explainable, multi-task deep learning models for quantifying FOG over the course of the medication cycle and at varying levels of parkinsonism severity. We trained interpretable deep learning models with multi-task learning to simultaneously score FOG (cross-validated F1 score 97.6%), identify medication state (OFF vs. ON levodopa; cross-validated F1 score 96.8%), and measure total PD severity (MDS-UPDRS-III score prediction error ≤ 2.7 points) using kinematic data of a well-characterized sample of N = 57 patients during levodopa challenge tests. The proposed model was able to explain how kinematic movements are associated with each FOG severity level that were highly consistent with the features, in which movement disorders specialists are trained to identify as characteristics of freezing. Overall, we demonstrate that deep learning models’ capability to capture complex movement patterns in kinematic data can automatically and objectively score FOG with high accuracy. These models have the potential to discover novel kinematic biomarkers for FOG that can be used for hypothesis generation and potentially as clinical trial outcome measures. Full article
(This article belongs to the Topic Human Movement Analysis)
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11 pages, 3468 KiB  
Article
Effect of Different Protection on Lateral Ankle during Landing: An Instantaneous Impact Analysis
by Junchao Guo, Jiemeng Yang, Yawei Wang, Zhongjun Mo, Jingyu Pu and Yubo Fan
Bioengineering 2023, 10(1), 34; https://doi.org/10.3390/bioengineering10010034 - 27 Dec 2022
Cited by 1 | Viewed by 1508
Abstract
Ankle sprain is the most common injury during parachute landing. The biomechanical behavior of the tissues can help us understand the injury mechanism of ankle inversion. To accurately describe the injury mechanism of tissues and assess the effect of ankle protection, a stable [...] Read more.
Ankle sprain is the most common injury during parachute landing. The biomechanical behavior of the tissues can help us understand the injury mechanism of ankle inversion. To accurately describe the injury mechanism of tissues and assess the effect of ankle protection, a stable time of landing was obtained through the dynamic stability test. It was used for the boundary condition of the foot finite element (FE). The FE model was provided a static load equal to half of the bodyweight applied at the distal tibia and fibula; a foot-boot-brace FE model was established to simulate the landing of subjects on an inversion inclined platform of 0–20°, including non-, external, and elastic ankle braces. Compared with the non-ankle brace, both the external and elastic ankle braces decreased the peak strains of the cal-fibular, anterior Ta-fibular, and posterior Ta-fibular ligaments (15.2–33.0%), and of the peak stress of the fibula (15.2–24.5%). For the strain decrement of the aforementioned ligaments, the elastic brace performed better than the external ankle brace under the inversion of the 10° condition. The peak stress of the fibula (15.6 MPa) decreased up to 24.5% with an elastic brace and 5.6–10.3% with an external brace. The findings suggested that the behaviors of lateral ankle ligaments and fibula were meaningful for the functional ability of the ankle. This provides some suggestions regarding the optimal design of ankle protection. Full article
(This article belongs to the Topic Human Movement Analysis)
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12 pages, 5012 KiB  
Article
Biomechanical Characteristics of Long Stair Climbing in Healthy Young Individuals in a Real-World Study Using a Wearable Motion Analysis System
by Haruki Yaguchi, Yusuke Sekiguchi, Keita Honda, Kenichiro Fukushi, Chenhui Huang, Kentaro Nakahara, Cheng Zhenzhao and Shin-Ichi Izumi
Biomechanics 2022, 2(4), 601-612; https://doi.org/10.3390/biomechanics2040047 - 22 Nov 2022
Cited by 1 | Viewed by 2504
Abstract
Background: Stair climbing is a part of the basic activities of daily living. Previous biomechanical analyses of stairs have been conducted in the laboratory, resulting in only a few steps. Therefore, the biomechanical characteristics of long stair climbing in the real world remain [...] Read more.
Background: Stair climbing is a part of the basic activities of daily living. Previous biomechanical analyses of stairs have been conducted in the laboratory, resulting in only a few steps. Therefore, the biomechanical characteristics of long stair climbing in the real world remain unclear. The purpose of this study was to identify differences in kinematic and kinetic in the lower limb between the beginning and end phases of long stair climbing in an outdoor environment using a wearable motion analysis system. Eight subjects (four males and four females) were included in the data analysis (age: 23.6 ± 0.5 years). The long stair was 66 consecutive steps out of 202 stone steps. A wearable motion analysis system comprised six inertial measurement units and foot pressure sensors. The maximum ankle joint flexion angle in the end phase was significantly increased more than in the beginning phase (p < 0.001). On the other hand, the other kinematic, kinetic, and stair climbing speeds showed no significant difference between the phases. The findings indicated that fatigue during long stair climbing might increase ankle dorsiflexion to compensate for forwarding propulsion. Full article
(This article belongs to the Topic Human Movement Analysis)
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10 pages, 3125 KiB  
Article
Comparison of Three Single Leg Weightbearing Tasks with Statistical Parametric Mapping
by Nickolai J. P. Martonick, Craig P. McGowan, Russell T. Baker, Lindsay W. Larkins, Jeff G. Seegmiller and Joshua P. Bailey
Biomechanics 2022, 2(4), 591-600; https://doi.org/10.3390/biomechanics2040046 - 03 Nov 2022
Cited by 2 | Viewed by 1875
Abstract
The single leg squat (SLS), forward step down (FSD), and lateral step down (LSD) are clinically reliable movement screens for identifying motion imbalances. The current understanding for the kinematic profiles of each task is limited to discrete time points such as peak knee [...] Read more.
The single leg squat (SLS), forward step down (FSD), and lateral step down (LSD) are clinically reliable movement screens for identifying motion imbalances. The current understanding for the kinematic profiles of each task is limited to discrete time points such as peak knee flexion. However, analyses of the entire movement would better aid clinicians when selecting the appropriate task for rehabilitation or movement screen purposes. The current study used Statistical Parametric Mapping to ascertain differences in the kinematic waveforms for the entire duration of each task. The trunk, pelvis, hip, and knee were analyzed in the sagittal and frontal planes. Data for each variable and task were analyzed from 0–100% of the movement. Primary findings indicated that the FSD provoked a greater magnitude of knee abduction than the SLS and LSD from 26–66% of the movement. The SLS generated the greatest amounts of trunk, pelvic, and hip flexion for the entirety of the movement. The LSD elicited the least amount of ipsilateral trunk lean (90–100%). Thus, the FSD may be optimal for assessing frontal plane knee motion as a screen for injury risk, while the SLS has potential to place increased sagittal plane demand on the muscles of the hip. Full article
(This article belongs to the Topic Human Movement Analysis)
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13 pages, 647 KiB  
Article
Gender Comparisons and Associations between Lower Limb Muscle Activation Strategies and Resultant Knee Biomechanics during Single Leg Drop Landings
by Xiaohan Xu, Guojiong Hu, Genevieve K. R. Williams and Fenghao Ma
Biomechanics 2022, 2(4), 562-574; https://doi.org/10.3390/biomechanics2040044 - 01 Nov 2022
Cited by 1 | Viewed by 2505
Abstract
(1) Background: We aimed to compare gender differences in knee biomechanics and neuromuscular characteristics, and to determine the relationships between lower limb muscle pre-activations and knee biomechanics during a single leg drop landing, in order to identify riskier landing patterns to prevent injury [...] Read more.
(1) Background: We aimed to compare gender differences in knee biomechanics and neuromuscular characteristics, and to determine the relationships between lower limb muscle pre-activations and knee biomechanics during a single leg drop landing, in order to identify riskier landing patterns to prevent injury and intervene properly. (2) Methods: Descriptive laboratory cross-sectional study on 38 healthy untrained subjects with low to moderate physical activity status. (3) Results: During the initial-contact phase of landing, females demonstrated greater peak vertical ground reaction force (GRF) normalized to body weight (49.12 ± 7.53 vs. 39.88 ± 5.69 N/kg; p < 0.001; Hedge’s g = 1.37), peak knee anterior reaction force normalized to body weight (0.23 ± 0.04 vs. 0.17 ± 0.05 N/kg; p < 0.001; Hedge’s g = 1.33), and decreased pre-activation of the semitendinosus (45.10 ± 20.05% vs. 34.03 ± 12.05%; p = 0.04; Hedge’s g = 0.67). The final regression equation was peak knee anterior reaction force = 0.024 + 0.025 (peak knee flexion moment) − 0.02 (semitendinosus-to-vastus lateralis pre-activation ratio) + 0.003 (peak vertical GRF) (R2 = 0.576, p < 0.001). (4) Conclusions: Overall, the data provided in this study support that a reduced semitendinosus-to-vastus lateralis pre-activation ratio predicted an increase in knee anterior reaction force and potentially an increase in ACL forces. Female non-athletes had gender-specific landing characteristics that may contribute to ACL injury. Future studies are warranted to consider more possible predictors of non-contact ACL injury. Full article
(This article belongs to the Topic Human Movement Analysis)
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9 pages, 1518 KiB  
Article
Kinetic and Kinematic Characteristics of Setting Motions in Female Volleyball Players
by Damjana V. Cabarkapa, Dimitrije Cabarkapa, Andrew C. Fry, Shay M. Whiting and Gabriel G. Downey
Biomechanics 2022, 2(4), 538-546; https://doi.org/10.3390/biomechanics2040042 - 18 Oct 2022
Cited by 1 | Viewed by 2953
Abstract
While being an integral part of both the offensive and defensive segments of the game, the biomechanical parameters of setting motions remain understudied in the scientific literature. Thus, the purpose of the present study was to examine differences in kinetic and kinematic characteristics [...] Read more.
While being an integral part of both the offensive and defensive segments of the game, the biomechanical parameters of setting motions remain understudied in the scientific literature. Thus, the purpose of the present study was to examine differences in kinetic and kinematic characteristics between: (a) three types of setting motions (i.e., front, middle, back); (b) two types of setting approaches (i.e., stationary, step-in); and (c) proficient (PRO) and non-proficient (N-PRO) volleyball players. Twenty recreationally active females performed five stationary and five step-in setting approaches to Zone 4–2 in a randomized order. Uni-dimensional force plate sampling at 1000 Hz and high-definition camera recording at 30 fps were used to obtain kinetic and kinematic variables of interest. The total number of setting attempts performed by each subject was 30, accounting for a grand total of 600 attempts. PRO setters had less knee flexion, shoulder flexion, and ankle dorsiflexion at the initial concentric phase of the volleyball setting motion when compared to the N-PRO setters. Moreover, significantly greater peak concentric and landing forces, impulse, rate of force development, and vertical jump height were observed for PRO setters compared to N-PRO setters, while no significant differences were found between different setting targets and approaches. Full article
(This article belongs to the Topic Human Movement Analysis)
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12 pages, 443 KiB  
Review
The Impact of Fatigue on Performance and Biomechanical Variables—A Narrative Review with Prospective Methodology
by Michele Aquino, John Petrizzo, Robert M. Otto and John Wygand
Biomechanics 2022, 2(4), 513-524; https://doi.org/10.3390/biomechanics2040040 - 01 Oct 2022
Cited by 3 | Viewed by 5438
Abstract
Landing kinetics and kinematics have historically been correlated with potential injury. A factor that requires more attention associated with its correlation to injury risk includes the impact of physiological fatigue. Fatigue is a multifaceted phenomenon involving central and peripheral factors resulting in a [...] Read more.
Landing kinetics and kinematics have historically been correlated with potential injury. A factor that requires more attention associated with its correlation to injury risk includes the impact of physiological fatigue. Fatigue is a multifaceted phenomenon involving central and peripheral factors resulting in a slowing or cessation of motor unit firing and a decrease in maximal force and power. Sports participation rarely results in momentary muscular failure occurring, as many sports consist of intermittent periods of activity that are interspersed with short rest periods that allow for recovery to take place. However, over the course of the competition, fatigue can still accumulate and can result in impaired performance. Current literature on the topic struggles to replicate the peripheral and central metabolic stresses required to induce a state of fatigue that would be equivalent to athletic exposure. Furthermore, the current literature fails to demonstrate consistency regarding the kinetic implications associated with fatigue, which may be secondary to the inconsistencies associated with fatigue protocols utilized. This article focuses on providing an overview of the current literature associated with fatigue’s impact on the kinetics associated with landing from a jump. The article will provide a prospective methodology utilizing repeat bouts of the Wingate Anaerobic Power Test. The proposed protocol may help further our understanding of the relationship between fatigue and lower extremity biomechanics. Full article
(This article belongs to the Topic Human Movement Analysis)
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13 pages, 2206 KiB  
Article
Pedestrian Origin–Destination Estimation Based on Multi-Camera Person Re-Identification
by Yan Li, Majid Sarvi, Kourosh Khoshelham, Yuyang Zhang and Yazhen Jiang
Sensors 2022, 22(19), 7429; https://doi.org/10.3390/s22197429 - 30 Sep 2022
Cited by 1 | Viewed by 1846
Abstract
Pedestrian origin–destination (O–D) estimates that record traffic flows between origins and destinations, are essential for the management of pedestrian facilities including pedestrian flow simulation in the planning phase and crowd control in the operation phase. However, current O–D data collection techniques such as [...] Read more.
Pedestrian origin–destination (O–D) estimates that record traffic flows between origins and destinations, are essential for the management of pedestrian facilities including pedestrian flow simulation in the planning phase and crowd control in the operation phase. However, current O–D data collection techniques such as surveys, mobile sensing using GPS, Wi-Fi, and Bluetooth, and smart card data have the disadvantage that they are either time consuming and costly, or cannot provide complete O–D information for pedestrian facilities without entrances and exits or pedestrian flow inside the facilities. Due to the full coverage of CCTV cameras and the huge potential of image processing techniques, we address the challenges of pedestrian O–D estimation and propose an image-based O–D estimation framework. By identifying the same person in disjoint camera views, the O–D trajectory of each identity can be accurately generated. Then, state-of-the-art deep neural networks (DNNs) for person re-ID at different congestion levels were compared and improved. Finally, an O–D matrix based on trajectories was generated and the resident time was calculated, which provides recommendations for pedestrian facility improvement. The factors that affect the accuracy of the framework are discussed in this paper, which we believe could provide new insights and stimulate further research into the application of the Internet of cameras to intelligent transport infrastructure management. Full article
(This article belongs to the Topic Human Movement Analysis)
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10 pages, 560 KiB  
Article
For Patients with Stroke, Balance Ability Affects the Leg Extension Angle on the Affected Side
by Yuta Matsuzawa, Takasuke Miyazaki, Yasufumi Takeshita, Sota Araki, Shintaro Nakatsuji, Seiji Fukunaga, Masayuki Kawada and Ryoji Kiyama
Appl. Sci. 2022, 12(19), 9466; https://doi.org/10.3390/app12199466 - 21 Sep 2022
Cited by 1 | Viewed by 1847
Abstract
In stroke patients, the impact of lower limb physical functions on the leg extension angle remains unclear. We set out to reveal the physical impairments of the affected side in such patients that were associated with leg extension angle during gait. Twenty-six stroke [...] Read more.
In stroke patients, the impact of lower limb physical functions on the leg extension angle remains unclear. We set out to reveal the physical impairments of the affected side in such patients that were associated with leg extension angle during gait. Twenty-six stroke patients walked for 16 m at a spontaneous speed. During walking, the leg extension angle and the increment of velocity during late stance, as an indicator of propulsion, were measured by inertial measurement units. The Berg balance scale (BBS), Fugl-Meyer assessment-lower limb, and motricity index-lower limb (MI-LL) were also evaluated. Stepwise multiple regression analysis was employed to reveal functions associated with the leg extension angle on the affected side. A path analysis was also used to confirm the relationship between the extracted factors, leg extension angle, and gait speed. Multiple regression analysis showed that the BBS was significantly related to the leg extension angle on the affected side (p < 0.001). Path analysis revealed that the leg extension angle was also indirectly affected by the MI-LL and that it affected gait speed via propulsion on the affected side. These findings could guide the prescription of effective gait training for improving gait performance during stroke rehabilitation. Full article
(This article belongs to the Topic Human Movement Analysis)
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13 pages, 999 KiB  
Article
Gait Kinematics and Asymmetries Affecting Fall Risk in People with Chronic Stroke: A Retrospective Study
by Shuaijie Wang and Tanvi Bhatt
Biomechanics 2022, 2(3), 453-465; https://doi.org/10.3390/biomechanics2030035 - 02 Sep 2022
Cited by 2 | Viewed by 2089
Abstract
Stroke survivors are at a relatively higher risk of falling than their healthy counterparts. To identify the key gait characteristics affecting fall risk in this population, this study analyzed the gait kinematics and gait asymmetries for 36 community-dwelling people with chronic stroke (PwCS). [...] Read more.
Stroke survivors are at a relatively higher risk of falling than their healthy counterparts. To identify the key gait characteristics affecting fall risk in this population, this study analyzed the gait kinematics and gait asymmetries for 36 community-dwelling people with chronic stroke (PwCS). According to their fall history in the last 12 months, they were divided into a fall group (n = 21) and non-fall group (n = 15), and then the gait kinematics (step length, stride length, stance time, swing time, trunk angle, and segment angles for lower limbs) and their asymmetries (symmetry ratio and symmetry index) were compared between these two groups. To investigate the relationship between fall types and gait characteristics, these variables were also compared between 11 slip-fallers and non-fallers, as well as between 7 trip-fallers and non-fallers. Our results indicated that the fallers showed smaller trunk and thigh angle, larger shank angle, and higher gait asymmetries (trunk and foot). Such changes in gait pattern could also be found in the trip-fallers, except the trunk angle. Additionally, the trip-fallers also showed a shorter step length, shorter stride length, shorter swing time, larger foot angle on the paretic side, and higher asymmetries in shank angle and step length, while the slip-fallers only showed changes in trunk angle and thigh angle and higher asymmetries in step length and foot angle compared to the non-fall group. Our results indicated that improper or pathological gait patterns (i.e., smaller thigh angle or higher foot asymmetry) increases the risk of falling in PwCS, and different fall types are associated with different gait characteristics. Our findings would be helpful for the development of fall risk assessment methods that are based on kinematic gait measurements. Implementation of objective fall risk assessments in PwCS has the potential to reduce fall-related injuries, leading to a reduction in associated hospital costs. Full article
(This article belongs to the Topic Human Movement Analysis)
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12 pages, 1109 KiB  
Article
Relationship between Joint Stiffness, Limb Stiffness and Whole–Body Center of Mass Mechanical Work across Running Speeds
by Li Jin and Michael E. Hahn
Biomechanics 2022, 2(3), 441-452; https://doi.org/10.3390/biomechanics2030034 - 30 Aug 2022
Cited by 2 | Viewed by 2044
Abstract
The lower–extremity system acts like a spring in the running stance phase. Vertical stiffness (Kvert) and leg stiffness (Kleg) reflect the whole–body center of mass (COM) and leg–spring system loading and response [...] Read more.
The lower–extremity system acts like a spring in the running stance phase. Vertical stiffness (Kvert) and leg stiffness (Kleg) reflect the whole–body center of mass (COM) and leg–spring system loading and response in running, while joint stiffness (Kjoint) represents joint–level dynamic loading and response. This study aimed to investigate whether Kjoint is associated with Kvert and Kleg across different running speeds. Twenty healthy subjects were recruited into a treadmill running study (1.8 to 3.8 m/s, with 0.4 m/s intervals). We found that Kjoint accounted for 38.4% of the variance in Kvert (p = 0.046) and 42.4% of the variance in Kleg (p = 0.028) at 1.8 m/s; Kjoint also accounted for 49.8% of the variance in Kvert (p = 0.014) and 79.3% of the variance in Kleg (p < 0.0001) at 2.2 m/s. Kknee had the strongest unique association with Kvert and Kleg at 1.8 and 2.2 m/s. Kjoint was associated with Kleg at a wider range of speeds. These findings built a connection between joint stiffness and limb stiffness within a certain range of running speeds. Kknee may need to be considered as an important factor in future limb stiffness optimization and general running performance enhancement. Full article
(This article belongs to the Topic Human Movement Analysis)
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10 pages, 1543 KiB  
Article
Gait Symmetry Is Unaffected When Completing a Motor Dexterity Task While Using a Walking Workstation in Healthy, Young Adults
by Heather R. Vanderhoof, Emily A. Chavez and Jeffrey D. Eggleston
Biomechanics 2022, 2(3), 431-440; https://doi.org/10.3390/biomechanics2030033 - 24 Aug 2022
Viewed by 1522
Abstract
Walking workstations may counteract sedentarism in working adults; however, performing dual-task walking may affect gait or work performance. The purpose of this study was to examine gait symmetry parameters and work performance while completing a fine motor dexterity task during walking workstation use. [...] Read more.
Walking workstations may counteract sedentarism in working adults; however, performing dual-task walking may affect gait or work performance. The purpose of this study was to examine gait symmetry parameters and work performance while completing a fine motor dexterity task during walking workstation use. Gait function, quantified as gait symmetry, was used to identify attentional resource allocation of the co-occurring tasks during the dual-task conditions. Eighteen college-aged students performed the Purdue Pegboard Test (PPT) with left and right hands separately while using a walking workstation at a self-selected speed. Gait symmetry indices were computed on stride length and lower extremity angular joint positions and were analyzed for a comparison of the baseline and PPT dual-task conditions. No asymmetries were found in stride length or lower extremity angular joint positions at any sub-phase of gait during walking workstation use. PPT scores decreased significantly in the walking condition compared to the seated and standing conditions. Overall, gait symmetry did not change at any lower extremity angular joint position at any sub-phase; however, there was a decrease in PPT performance, which may relate to decreased work performance. However, increased exposure to the PPT task while using a walking workstation may improve work performance over time. Full article
(This article belongs to the Topic Human Movement Analysis)
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10 pages, 1173 KiB  
Article
Sex Impact on Knee and Ankle Muscle Extensor Forces during Loaded Running
by Kade D. Wagers, Nicholas J. Lobb, AuraLea C. Fain, Kayla D. Seymore and Tyler N. Brown
Biomechanics 2022, 2(3), 421-430; https://doi.org/10.3390/biomechanics2030032 - 18 Aug 2022
Cited by 2 | Viewed by 2017
Abstract
Background: This study determined whether the knee and ankle muscle extensor forces increase when running with a body-borne load and whether these forces differ between the sexes. Methods: Thirty-six (twenty male and sixteen female) adults had the knee and ankle extensor force quantified [...] Read more.
Background: This study determined whether the knee and ankle muscle extensor forces increase when running with a body-borne load and whether these forces differ between the sexes. Methods: Thirty-six (twenty male and sixteen female) adults had the knee and ankle extensor force quantified when running 4.0 m/s with four body-borne loads (20, 25, 30, and 35 kg). Peak normalized (BW) and unnormalized (N) extensor muscle force, relative effort, and joint angle and angular velocity at peak muscle force for both the ankle and the knee were submitted to a mixed model ANOVA. Results: Significant load by sex interactions for knee unnormalized extensor force (p = 0.025) and relative effort (p = 0.040) were observed, as males exhibited greater knee muscle force and effort than females and increased their muscle force and effort with additional load. Males also exhibited greater ankle normalized and unnormalized extensor force (p = 0.004, p < 0.001) and knee unnormalized force than females (p = 0.005). The load increased the normalized ankle and knee muscle force (p < 0.001, p = 0.030) and relative effort (p < 0.001, p = 0.044) and the unnormalized knee muscle force (p = 0.009). Conclusion: Running with a load requires greater knee and ankle extensor force, but males exhibited greater increases in muscle force, particularly at the knee, than females. Full article
(This article belongs to the Topic Human Movement Analysis)
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17 pages, 2210 KiB  
Article
User-Centric Proximity Estimation Using Smartphone Radio Fingerprinting
by Aleš Švigelj, Andrej Hrovat and Tomaž Javornik
Sensors 2022, 22(15), 5609; https://doi.org/10.3390/s22155609 - 27 Jul 2022
Cited by 4 | Viewed by 1646
Abstract
The integration of infectious disease modeling with the data collection process is crucial to reach its maximum potential, and remains a significant research challenge. Ensuring a solid empirical foundation for models used to fill gaps in data and knowledge is of paramount importance. [...] Read more.
The integration of infectious disease modeling with the data collection process is crucial to reach its maximum potential, and remains a significant research challenge. Ensuring a solid empirical foundation for models used to fill gaps in data and knowledge is of paramount importance. Personal wireless devices, such as smartphones, smartwatches and wireless bracelets, can serve as a means of bridging the gap between empirical data and the mathematical modeling of human contacts and networking. In this paper, we develop, implement, and evaluate concepts and architectures for advanced user-centric proximity estimation based on smartphone radio environment monitoring. We investigate innovative methods for the estimation of proximity, based on a person-radio-environment trace recorded by the smartphone, and define the proximity parameter. For this purpose, we developed a smartphone application and back-end services. The results show that, with the proposed procedure, we can estimate the proximity of two devices in terms of near, medium, and far distance with reasonable accuracy in real-world case scenarios. Full article
(This article belongs to the Topic Human Movement Analysis)
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17 pages, 13619 KiB  
Article
Multiple Groups of Agents for Increased Movement Interference and Synchronization
by Alexis Meneses, Hamed Mahzoon, Yuichiro Yoshikawa and Hiroshi Ishiguro
Sensors 2022, 22(14), 5465; https://doi.org/10.3390/s22145465 - 21 Jul 2022
Viewed by 1673
Abstract
We examined the influence of groups of agents and the type of avatar on movement interference. In addition, we studied the synchronization of the subject with the agent. For that, we conducted experiments utilizing human subjects to examine the influence of one, two, [...] Read more.
We examined the influence of groups of agents and the type of avatar on movement interference. In addition, we studied the synchronization of the subject with the agent. For that, we conducted experiments utilizing human subjects to examine the influence of one, two, or three agents, as well as human or robot avatars, and finally, the agent moving biologically or linearly. We found the main effect on movement interference was the number of agents; namely, three agents had significantly more influence on movement interference than one agent. These results suggest that the number of agents is more influential on movement interference than other avatar characteristics. For the synchronization, the main effect of the type of the agent was revealed, showing that the human agent kept more synchronization compared to the robotic agent. In this experiment, we introduced an additional paradigm on the interference which we called synchronization, discovering that a group of agents is able to influence this behavioral level as well. Full article
(This article belongs to the Topic Human Movement Analysis)
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11 pages, 1972 KiB  
Article
A Pilot Study of the Efficiency of LSTM-Based Motion Classification Algorithms Using a Single Accelerometer
by Kyu-Young Kang, Seul-Gi Lee, Hyeon Kang, Jung-Gil Kim, Gye-Rae Tack and Jin-Seung Choi
Appl. Sci. 2022, 12(14), 7243; https://doi.org/10.3390/app12147243 - 19 Jul 2022
Cited by 2 | Viewed by 1502
Abstract
Inertial sensors are widely used for classifying the motions of daily activities. Although hierarchical classification algorithms were commonly used for defined motions, deep-learning models have been used recently to classify a greater diversity of motions. In addition, ongoing studies are actively investigating algorithm [...] Read more.
Inertial sensors are widely used for classifying the motions of daily activities. Although hierarchical classification algorithms were commonly used for defined motions, deep-learning models have been used recently to classify a greater diversity of motions. In addition, ongoing studies are actively investigating algorithm efficiency (e.g., training time and accuracy). Thus, a deep-learning model was constructed in this study for the classification of a given motion based on the raw data of inertial sensors. Furthermore, the number of epochs (150, 300, 500, 750, and 900) and hidden units (100, 150, and 200) were varied in the model to determine its efficiency based on training time and accuracy, and the optimum accuracy and training time was determined. Using a basic long short-term memory (LSTM), which is a neural network known to be suitable for sequential data, the data classification training was conducted on a common desktop PC with typical specifications. The results show that the accuracy was the highest (99.82%) with 150 hidden units and 300 epochs, while the training time was also relatively short (78.15 min). In addition, the model accuracy did not always increase even when the model complexity was increased (by increasing the number of epochs and hidden units) and the training time increased as a consequence. Hence, through suitable combinations of the two factors that constitute deep-learning models according to the data, the potential development and use of efficient models have been verified. From the perspective of training optimization, this study is significant in having determined the importance of the conditions for hidden units and epochs that are suitable for the given data and the adverse effects of overtraining. Full article
(This article belongs to the Topic Human Movement Analysis)
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10 pages, 1425 KiB  
Article
Can Slight Variations to Lateral Wedge Insoles Induce Significant Biomechanical Changes in Patients with Knee Osteoarthritis?
by Vitor Ferreira, Leandro Machado, Adélio Vilaça, Francisco Xará-Leite and Paulo Roriz
Biomechanics 2022, 2(3), 342-351; https://doi.org/10.3390/biomechanics2030027 - 16 Jul 2022
Cited by 1 | Viewed by 2142
Abstract
Lateral wedge insoles are recommended in order to minimize the impacts of osteoarthritis of the knee. The amount of wedging required to induce a biomechanical response with clinical significance is still controversial. This study aimed to investigate the immediate biomechanical effects of different [...] Read more.
Lateral wedge insoles are recommended in order to minimize the impacts of osteoarthritis of the knee. The amount of wedging required to induce a biomechanical response with clinical significance is still controversial. This study aimed to investigate the immediate biomechanical effects of different amounts of wedging in symptomatic medial knee OA. A 3D motion capture system and five force platforms were used to acquire walking kinematic and kinetic data along a 10 m walkway. Each participant was tested for six different lateral wedge insoles (0, 2, 4, 6, 8, and 10°) in a randomized order. Thirty-eight patients with medial osteoarthritis of the knee were recruited. The application of insoles resulted in an incremental reduction of the first peak of the external knee adduction moment under all experimental conditions in comparison with the control condition (0° insole). A significant increase (p < 0.05) was observed in peak ankle eversion and in ankle eversion at the first peak of the external knee adduction moment with insoles higher than 8° and 6°, respectively. Slight variations to lateral wedge insoles, greater than 2°, appear to induce significant biomechanical changes in patients with knee osteoarthritis. Full article
(This article belongs to the Topic Human Movement Analysis)
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14 pages, 2189 KiB  
Article
Human Lower Limb Motion Capture and Recognition Based on Smartphones
by Lin-Tao Duan, Michael Lawo, Zhi-Guo Wang and Hai-Ying Wang
Sensors 2022, 22(14), 5273; https://doi.org/10.3390/s22145273 - 14 Jul 2022
Cited by 6 | Viewed by 2351
Abstract
Human motion recognition based on wearable devices plays a vital role in pervasive computing. Smartphones have built-in motion sensors that measure the motion of the device with high precision. In this paper, we propose a human lower limb motion capture and recognition approach [...] Read more.
Human motion recognition based on wearable devices plays a vital role in pervasive computing. Smartphones have built-in motion sensors that measure the motion of the device with high precision. In this paper, we propose a human lower limb motion capture and recognition approach based on a Smartphone. We design a motion logger to record five categories of limb activities (standing up, sitting down, walking, going upstairs, and going downstairs) using two motion sensors (tri-axial accelerometer, tri-axial gyroscope). We extract the motion features and select a subset of features as a feature vector from the frequency domain of the sensing data using Fast Fourier Transform (FFT). We classify and predict human lower limb motion using three supervised learning algorithms: Naïve Bayes (NB), K-Nearest Neighbor (KNN), and Artificial Neural Networks (ANNs). We use 670 lower limb motion samples to train and verify these classifiers using the 10-folder cross-validation technique. Finally, we design and implement a live detection system to validate our motion detection approach. The experimental results show that our low-cost approach can recognize human lower limb activities with acceptable accuracy. On average, the recognition rate of NB, KNN, and ANNs are 97.01%, 96.12%, and 98.21%, respectively. Full article
(This article belongs to the Topic Human Movement Analysis)
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11 pages, 1335 KiB  
Article
Cyclograms Reveal Alteration of Inter-Joint Coordination during Gait in People with Multiple Sclerosis Minimally Disabled
by Massimiliano Pau, Bruno Leban, Micaela Porta, Jessica Frau, Giancarlo Coghe and Eleonora Cocco
Biomechanics 2022, 2(3), 331-341; https://doi.org/10.3390/biomechanics2030026 - 13 Jul 2022
Cited by 2 | Viewed by 1920
Abstract
Subtle alterations of gait patterns in people with Multiple Sclerosis (pwMS) with minimal or no disability often coexist with normal spatio-temporal parameters. Here, we retrospectively investigate the existence of possible anomalies in lower limb inter-joint coordination (i.e., the functional relationship between joint pairs) [...] Read more.
Subtle alterations of gait patterns in people with Multiple Sclerosis (pwMS) with minimal or no disability often coexist with normal spatio-temporal parameters. Here, we retrospectively investigate the existence of possible anomalies in lower limb inter-joint coordination (i.e., the functional relationship between joint pairs) in pwMS with apparently physiologic gait features. Twenty-seven pwMS with Expanded Disability Status Scale scores ≤ 2, and 27 unaffected age-and-sex-matched individuals, were tested using 3D computerized gait analysis. Raw data were processed to extract the main spatio-temporal parameters and the kinematics in the sagittal plane at the hip, knee, and ankle joints. Angle-angle diagrams (cyclograms) were obtained by coupling the flexion-extension values for the hip-knee and knee-ankle joint pairs at each point of the gait cycle. Cyclogram area, perimeter, and dimensionless ratio were employed to quantify inter-joint coordination. The results demonstrate that cyclograms of pwMS are characterized by significantly reduced perimeters for both investigated joint pairs and reduced area at the hip–knee joint pair. In the latter pair, the differences between groups involved the entire swing phase. For the knee-ankle pair, the average cyclogram of pwMS departed from normality from the late stance until the mid-swing phase. Such findings suggest that inter-joint coordination is impaired even in minimally disabled pwMS who exhibit a normal gait pattern in terms of spatio-temporal parameters. The quantitative and qualitative study of cyclogram features may provide information that is useful for better understanding the underlying mechanisms of walking dysfunctions in MS. Full article
(This article belongs to the Topic Human Movement Analysis)
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14 pages, 2873 KiB  
Review
Biomechanics of the Upper Limbs: A Review in the Sports Combat Ambit Highlighting Wearable Sensors
by Andrés Blanco Ortega, Jhonatan Isidro Godoy, Dariusz Slawomir Szwedowicz Wasik, Eladio Martínez Rayón, Claudia Cortés García, Héctor Ramón Azcaray Rivera and Fabio Abel Gómez Becerra
Sensors 2022, 22(13), 4905; https://doi.org/10.3390/s22134905 - 29 Jun 2022
Cited by 6 | Viewed by 2776
Abstract
Over time, inertial sensors have become an essential ally in the biomechanical field for current researchers. Their miniaturization coupled with their ever-improvement make them ideal for certain applications such as wireless monitoring or measurement of biomechanical variables. Therefore, in this article, a compendium [...] Read more.
Over time, inertial sensors have become an essential ally in the biomechanical field for current researchers. Their miniaturization coupled with their ever-improvement make them ideal for certain applications such as wireless monitoring or measurement of biomechanical variables. Therefore, in this article, a compendium of their use is presented to obtain biomechanical variables such as velocity, acceleration, and power, with a focus on combat sports such as included box, karate, and Taekwondo, among others. A thorough search has been made through a couple of databases, including MDPI, Elsevier, IEEE Publisher, and Taylor & Francis, to highlight some. Research data not older than 20 years have been collected, tabulated, and classified for interpretation. Finally, this work provides a broad view of the use of wearable devices and demonstrates the importance of using inertial sensors to obtain and complement biomechanical measurements on the upper extremities of the human body. Full article
(This article belongs to the Topic Human Movement Analysis)
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11 pages, 2001 KiB  
Article
Noncontact and High-Precision Sensing System for Piano Keys Identified Fingerprints of Virtuosity
by Takanori Oku and Shinichi Furuya
Sensors 2022, 22(13), 4891; https://doi.org/10.3390/s22134891 - 29 Jun 2022
Cited by 3 | Viewed by 2654
Abstract
Dexterous tool use is typically characterized by fast and precise motions performed by multiple fingers. One representative task is piano playing, which involves fast performance of a sequence of complex motions with high spatiotemporal precision. However, for several decades, a lack of contactless [...] Read more.
Dexterous tool use is typically characterized by fast and precise motions performed by multiple fingers. One representative task is piano playing, which involves fast performance of a sequence of complex motions with high spatiotemporal precision. However, for several decades, a lack of contactless sensing technologies that are capable of precision measurement of piano key motions has been a bottleneck for unveiling how such an outstanding skill is cultivated. Here, we developed a novel sensing system that can record the vertical position of all piano keys with a time resolution of 1 ms and a spatial resolution of 0.01 mm in a noncontact manner. Using this system, we recorded the piano key motions while 49 pianists played a complex sequence of tones that required both individuated and coordinated finger movements to be performed as fast and accurately as possible. Penalized regression using various feature variables of the key motions identified distinct characteristics of the key-depressing and key-releasing motions in relation to the speed and accuracy of the performance. For the maximum rate of the keystrokes, individual differences across the pianists were associated with the peak key descending velocity, the key depression duration, and key-lift timing. For the timing error of the keystrokes, the interindividual differences were associated with the peak ascending velocity of the key and the inter-strike variability of both the peak key descending velocity and the key depression duration. These results highlight the importance of dexterous control of the vertical motions of the keys for fast and accurate piano performance. Full article
(This article belongs to the Topic Human Movement Analysis)
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15 pages, 3920 KiB  
Article
Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia
by Chen Ye, Yuhao Xiao, Ruoyu Li, Hongkai Gu, Xinyu Wang, Tianyang Lu and Lingjing Jin
Sensors 2022, 22(12), 4642; https://doi.org/10.3390/s22124642 - 20 Jun 2022
Cited by 1 | Viewed by 2354
Abstract
Abnormal movement of the head and neck is a typical symptom of Cervical Dystonia (CD). Accurate scoring on the severity scale is of great significance for treatment planning. The traditional scoring method is to use a protractor or contact sensors to calculate the [...] Read more.
Abnormal movement of the head and neck is a typical symptom of Cervical Dystonia (CD). Accurate scoring on the severity scale is of great significance for treatment planning. The traditional scoring method is to use a protractor or contact sensors to calculate the angle of the movement, but this method is time-consuming, and it will interfere with the movement of the patient. In the recent outbreak of the coronavirus disease, the need for remote diagnosis and treatment of CD has become extremely urgent for clinical practice. To solve these problems, we propose a multi-view vision based CD severity scale scoring method, which detects the keypoint positions of the patient from the frontal and lateral images, and finally scores the severity scale by calculating head and neck motion angles. We compared the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) subscale scores calculated by our vision based method with the scores calculated by a neurologist trained in dyskinesia. An analysis of the correlation coefficient was then conducted. Intra-class correlation (ICC)(3,1) was used to measure absolute accuracy. Our multi-view vision based CD severity scale scoring method demonstrated sufficient validity and reliability. This low-cost and contactless method provides a new potential tool for remote diagnosis and treatment of CD. Full article
(This article belongs to the Topic Human Movement Analysis)
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10 pages, 1776 KiB  
Article
Quantification of the Dependence of the Measurement Error on the Quantization of the A/D Converter for Center of Pressure Measurements
by Jan Jens Koltermann and Martin Gerber
Biomechanics 2022, 2(2), 309-318; https://doi.org/10.3390/biomechanics2020024 - 14 Jun 2022
Viewed by 1697
Abstract
In this scientific study, the question of the influence of the quantization error on the CoP measurement is be clarified. For this purpose, the quantization error is investigated in two scenarios, first with the technical/physical reproduction of the CoP, and then with test [...] Read more.
In this scientific study, the question of the influence of the quantization error on the CoP measurement is be clarified. For this purpose, the quantization error is investigated in two scenarios, first with the technical/physical reproduction of the CoP, and then with test persons. From the results, a model is derived with which a technical and economic optimum between resolution and error can be generated for an individual case. The study was carried out with 170 healthy volunteers, aged 20–30 years. The test persons stood in a bipedal position for 15 s on a Kislter force plate (type 9260AA). In the investigation, it was shown that, for the measurement of center of pressure (CoP), signals to mostly 16-bit analog/digital converters are suitable but not, per se, the most economical variant. With the introduction of a quality criterion, a reasonable design for the planned test case can be made. Full article
(This article belongs to the Topic Human Movement Analysis)
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15 pages, 4825 KiB  
Article
Motor Signatures in Digitized Cognitive and Memory Tests Enhances Characterization of Parkinson’s Disease
by Jihye Ryu and Elizabeth B. Torres
Sensors 2022, 22(12), 4434; https://doi.org/10.3390/s22124434 - 11 Jun 2022
Cited by 1 | Viewed by 1831
Abstract
Although interest in using wearable sensors to characterize movement disorders is growing, there is a lack of methodology for developing clinically interpretable biomarkers. Such digital biomarkers would provide a more objective diagnosis, capturing finer degrees of motor deficits, while retaining the information of [...] Read more.
Although interest in using wearable sensors to characterize movement disorders is growing, there is a lack of methodology for developing clinically interpretable biomarkers. Such digital biomarkers would provide a more objective diagnosis, capturing finer degrees of motor deficits, while retaining the information of traditional clinical tests. We aim at digitizing traditional tests of cognitive and memory performance to derive motor biometrics of pen-strokes and voice, thereby complementing clinical tests with objective criteria, while enhancing the overall characterization of Parkinson’s disease (PD). 35 participants including patients with PD, healthy young and age-matched controls performed a series of drawing and memory tasks, while their pen movement and voice were digitized. We examined the moment-to-moment variability of time series reflecting the pen speed and voice amplitude. The stochastic signatures of the fluctuations in pen drawing speed and voice amplitude of patients with PD show a higher signal-to-noise ratio compared to those of neurotypical controls. It appears that contact motions of the pen strokes on a tablet evoke sensory feedback for more immediate and predictable control in PD, while voice amplitude loses its neurotypical richness. We offer new standardized data types and analytics to discover the hidden motor aspects within the cognitive and memory clinical assays. Full article
(This article belongs to the Topic Human Movement Analysis)
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8 pages, 245 KiB  
Communication
Validity of Calculating Continuous Relative Phase during Cycling from Measures Taken with Skin-Mounted Electro-Goniometers
by Chris Whittle, Simon A. Jobson and Neal Smith
Sensors 2022, 22(12), 4371; https://doi.org/10.3390/s22124371 - 09 Jun 2022
Viewed by 1690
Abstract
The aim of this study was to assess the validity of electro-goniometers as a tool for recording continuous relative phase data at two joint couplings during cycling tasks at a range of cadences. Seven participants (4 male, 3 female, age: 29 ± 7 [...] Read more.
The aim of this study was to assess the validity of electro-goniometers as a tool for recording continuous relative phase data at two joint couplings during cycling tasks at a range of cadences. Seven participants (4 male, 3 female, age: 29 ± 7 years, height: 1.76 ± 0.10 m, mass: 71.97 ± 11.57 kg) performed exercise bouts of 30 s at four prescribed cadences (60, 80, 100, 120 rev·min−1) on a stationary ergometer (Wattbike, Nottingham, UK). Measures were synchronously recorded by bi-axial electro-goniometers (Biometrics, UK) and a 12-camera motion-capture system (Qualisys, Gothenburg, Sweden), with both systems sampling at 500 Hz. Sagittal plane joint angle and joint angular velocity were recorded at the hip, knee and ankle and analysed for ten complete pedal revolutions per participant per condition. Data were interpolated to 100 time points and used to calculate mean continuous relative phase (CRP) per pedal revolution at two intra-limb couplings: (i) knee flexion/extension–ankle plantarflexion/dorsiflexion (KA) and (ii) hip flexion/extension–knee flexion/extension (HK). At the KA coupling, significant differences in mean CRP were found between measurement systems at 120 rev·min−1 (p = 0.006). At the HK coupling, significant differences in mean CRP were found between measurement systems at 80 rev·min−1 (p = 0.043) and 100 rev·min−1 (p = 0.028). ICC values for most comparisons were below 0.5, suggesting poor levels of agreement between systems. Significant differences in mean CRP per pedal revolution and poor levels of agreement between systems suggests that electro-goniometers are not a suitable alternative to motion-capture systems when attempting to record CRP during cycling. Full article
(This article belongs to the Topic Human Movement Analysis)
14 pages, 4018 KiB  
Article
Classification and Regression of Muscle Neural Signals on Human Lower Extremities via BP_AdaBoost
by Junyao Wang, Yuehong Dai and Xiaxi Si
Appl. Sci. 2022, 12(12), 5830; https://doi.org/10.3390/app12125830 - 08 Jun 2022
Cited by 1 | Viewed by 1561
Abstract
Electromyography (EMG) signals are widely applied in the classification of human motion and intention recognition as having the characteristic of earlier than actual limb motion. In this article, to improve its accuracy of classification and prediction, we firstly analyze the relationship between muscle [...] Read more.
Electromyography (EMG) signals are widely applied in the classification of human motion and intention recognition as having the characteristic of earlier than actual limb motion. In this article, to improve its accuracy of classification and prediction, we firstly analyze the relationship between muscle length and joint movement and select rectus femoris and biceps femoris as the experimental muscles to collect neural signals by means of musculoskeletal analysis software. EMG sensors are used to measure those muscles’ EMG signals of five kinds of knee movements, including thigh-raising, calf-raising, squatting, knee bending on chair, and walking. We designed a BP_AdaBoost algorithm with the BP neural network as a weak classifier and weak regressor, and a muscle neural activation is used as the input for recognition. It is a negative correlation between the length of the rectus femoris and the biceps femoris during gait. Their muscle neural signals are used as the input of the recognition algorithm. The experiment results show that the proposed algorithm improves the rate of BP neural network from 78.82% to 93.52%. The thigh EMG signal successfully maps the knee joint angle by utilizing BP_AdaBoost; its error in identifying five kinds of motion modes is lowest compared with other regression algorithms. Full article
(This article belongs to the Topic Human Movement Analysis)
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17 pages, 1764 KiB  
Article
Modeling Joint Stiffness Change by Pelvic Tightening Based on Pelvic Alignment
by Michihiro Yoshida, Takayuki Tanaka and Yoshio Tsuchiya
Biomechanics 2022, 2(2), 264-280; https://doi.org/10.3390/biomechanics2020021 - 22 May 2022
Viewed by 3894
Abstract
This paper aims to develop a regression model that explains the relationship between changes in lumbar joint stiffness and pelvic alignment (posture or shape of the bones of the pelvis and lumbar spine) due to pelvic tightening. The proposed model is based on [...] Read more.
This paper aims to develop a regression model that explains the relationship between changes in lumbar joint stiffness and pelvic alignment (posture or shape of the bones of the pelvis and lumbar spine) due to pelvic tightening. The proposed model is based on the hypothesis that lumbar joint stiffness increases with changes in pelvic alignment. The proposed model is based on experimentally measured stiffness values and pelvic alignment data sets. The stiffness of the lumbar joint was estimated by motion analysis using a motion-capture system. Ninety-six volunteers participated in the experiment to estimate stiffness values, and the validity of using lumbar joint stiffness as the output of the model was examined. The pelvic alignment was measured through X-ray images. Pelvic alignment was measured using radiographic images, and 25 volunteers participated. The Results section states that the amount of change in the posture of the sacrum relative to the pelvis and the curvature of the lumbar spine contributes to the change in lumbar joint stiffness. Future work will include FEM analysis to validate the overall hypothesis and the validity of applying the model to a group other than those who participated in the development of the model. Full article
(This article belongs to the Topic Human Movement Analysis)
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9 pages, 2708 KiB  
Article
Influence of Sagittal Lumbopelvic Morphotypes on the Range of Motion of Human Lumbar Spine: An In Vitro Cadaveric Study
by Wei Wang, Chao Kong, Fumin Pan, Wei Wang, Xueqing Wu, Baoqing Pei and Shibao Lu
Bioengineering 2022, 9(5), 224; https://doi.org/10.3390/bioengineering9050224 - 20 May 2022
Cited by 1 | Viewed by 2056
Abstract
Background: Although spinopelvic radiographs analysis is the standard for a pathological diagnosis, it cannot explain the activities of the spine in daily life. This study investigates the correlation between sagittal parameters and spinal range of motion (ROM) to find morphological parameters with kinetic [...] Read more.
Background: Although spinopelvic radiographs analysis is the standard for a pathological diagnosis, it cannot explain the activities of the spine in daily life. This study investigates the correlation between sagittal parameters and spinal range of motion (ROM) to find morphological parameters with kinetic implications. Methods: Six L1–S1 human lumbar specimens were tested with a robotic testing device. Eight sagittal parameters were measured in the three-dimensional model. Pure moments were applied to simulate the physiological activities in daily life. Results: The correlation between sagittal parameters and the ROM was moderate in flexion and extension, but weak in lateral bending and rotation. In flexion–extension, the ROM was moderately correlated with SS and LL. SS was the only parameter correlated with the ROM under all loading conditions. The intervertebral rotation distribution showed that the maximal ROM frequently occurred at the L5–S1 segment. The minimal ROM often appeared near the apex point of the lumbar. Conclusion: Sagittal alignment mainly affected the ROM of the lumbar in flexion and extension. SS and apex may have had kinetic significance. Our findings suggest that the effect of sagittal parameters on lumbar ROM is important information for assessing spinal activity. Full article
(This article belongs to the Topic Human Movement Analysis)
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16 pages, 1749 KiB  
Article
Learning the Relative Dynamic Features for Word-Level Lipreading
by Hao Li, Nurbiya Yadikar, Yali Zhu, Mutallip Mamut and Kurban Ubul
Sensors 2022, 22(10), 3732; https://doi.org/10.3390/s22103732 - 13 May 2022
Cited by 2 | Viewed by 1746
Abstract
Lipreading is a technique for analyzing sequences of lip movements and then recognizing the speech content of a speaker. Limited by the structure of our vocal organs, the number of pronunciations we could make is finite, leading to problems with homophones when speaking. [...] Read more.
Lipreading is a technique for analyzing sequences of lip movements and then recognizing the speech content of a speaker. Limited by the structure of our vocal organs, the number of pronunciations we could make is finite, leading to problems with homophones when speaking. On the other hand, different speakers will have various lip movements for the same word. For these problems, we focused on the spatial–temporal feature extraction in word-level lipreading in this paper, and an efficient two-stream model was proposed to learn the relative dynamic information of lip motion. In this model, two different channel capacity CNN streams are used to extract static features in a single frame and dynamic information between multi-frame sequences, respectively. We explored a more effective convolution structure for each component in the front-end model and improved by about 8%. Then, according to the characteristics of the word-level lipreading dataset, we further studied the impact of the two sampling methods on the fast and slow channels. Furthermore, we discussed the influence of the fusion methods of the front-end and back-end models under the two-stream network structure. Finally, we evaluated the proposed model on two large-scale lipreading datasets and achieved a new state-of-the-art. Full article
(This article belongs to the Topic Human Movement Analysis)
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9 pages, 2932 KiB  
Technical Note
Improved Multichannel Electromyograph Using Off-the-Shelf Components for Education and Research
by Enrico M. Staderini, Stefano Mugnaini, Harish Kambampati, Andrea Magrini and Sandro Gentili
Sensors 2022, 22(10), 3616; https://doi.org/10.3390/s22103616 - 10 May 2022
Cited by 3 | Viewed by 1943
Abstract
Most students and researchers with limited funding are often looking for simple and low-cost devices for the acquisition of the electromyogram signal (EMG) in an educational or research setting. Thus, off-the-shelf devices are used and they have already been described in the literature, [...] Read more.
Most students and researchers with limited funding are often looking for simple and low-cost devices for the acquisition of the electromyogram signal (EMG) in an educational or research setting. Thus, off-the-shelf devices are used and they have already been described in the literature, but they are used without considering their real performances, which are, in general, quite poor from the electronic and signal processing points of view. It is the purpose of this communication to present the evidence of these issues, and to describe an improved version of the “classical” duo, composed of the common ECG/EMG Olimex board and the Arduino microprocessor board. In this case, the Arduino-DUE is used. Three main points are highlighted in this paper: (a) the bandpass characteristics of the ECG/EMG Olimex board and how they can be improved to cope with EMG bandwidth requirements; (b) the increase in sampling frequency of the signal; and, finally, (c) the possibility of automatic detection of more ECG/EMG Olimex boards installed at the same time as the shields on the Arduino-DUE board. Very simple and low-cost modifications on the ECG/EMG Olimex board could deliver a much better performing multichannel EMG acquisition system, suitable for educational classroom experiments and early proof-of-concept research. Full article
(This article belongs to the Topic Human Movement Analysis)
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8 pages, 1233 KiB  
Article
The Influence of Different Footwear Insole Stiffness on Center of Pressure and Ankle Kinematics during Walking: A Case Report
by Li Jin
Biomechanics 2022, 2(2), 205-212; https://doi.org/10.3390/biomechanics2020017 - 01 May 2022
Cited by 1 | Viewed by 2403
Abstract
During locomotion, the foot–ankle system plays an important role for forward progression of the body. The center of pressure (COP) is regarded as the point of the ground reaction force (GRF) vector acting on the foot surface during the stance phase. COP movement [...] Read more.
During locomotion, the foot–ankle system plays an important role for forward progression of the body. The center of pressure (COP) is regarded as the point of the ground reaction force (GRF) vector acting on the foot surface during the stance phase. COP movement trajectory and velocity reflect the stance phase forward progression of the foot segment and the ankle joint motion characteristics. This study aimed to investigate different levels of footwear insole stiffness on COP forward velocity, GRF and ankle joint angles during walking stance phase. Two healthy subjects (one female, one male; age 26.5 ± 6.4 years, height 168.5 ± 2.1 cm, weight 64.9 ± 5.4 kg) participated in this study. Subjects were asked to walk along a 10 m walkway at two different speeds: self–selected normal (SSN) and self–selected fast (SSF). Within each walking speed, subjects were required to walk under two different insole stiffness conditions: (1) normal shoe insole (NSI) from the testing shoe (Nike Free RN Flyknit 2017) used in this study; (2) 1.6 mm thick carbon fiber insole (CFI) fitted within the testing shoe. Stiffer insole (CFI) significantly decreased peak ankle internal rotation angle (p = 0.001) and sagittal plane angle ROM (p = 0.022); additionally, CFI significantly increased peak ankle eversion angle compared to the NSI condition (p = 0.028). In conclusion, increasing footwear insole stiffness would alter stance phase ankle joint motion at SSF walking speed. Additionally, stiffer insoles may tend to decrease COP peak velocity at the initial heel strike and the terminal stance phase. Future research should investigate the combined effects of various insole properties on lower extremity system kinematic and kinetic patterns in various locomotion activities. Full article
(This article belongs to the Topic Human Movement Analysis)
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16 pages, 3493 KiB  
Article
Estimating Running Ground Reaction Forces from Plantar Pressure during Graded Running
by Eric C. Honert, Fabian Hoitz, Sam Blades, Sandro R. Nigg and Benno M. Nigg
Sensors 2022, 22(9), 3338; https://doi.org/10.3390/s22093338 - 27 Apr 2022
Cited by 15 | Viewed by 5132
Abstract
Ground reaction forces (GRFs) describe how runners interact with their surroundings and provide the basis for computing inverse dynamics. Wearable technology can predict time−continuous GRFs during walking and running; however, the majority of GRF predictions examine level ground locomotion. The purpose of this [...] Read more.
Ground reaction forces (GRFs) describe how runners interact with their surroundings and provide the basis for computing inverse dynamics. Wearable technology can predict time−continuous GRFs during walking and running; however, the majority of GRF predictions examine level ground locomotion. The purpose of this manuscript was to predict vertical and anterior–posterior GRFs across different speeds and slopes. Eighteen recreationally active subjects ran on an instrumented treadmill while we collected GRFs and plantar pressure. Subjects ran on level ground at 2.6, 3.0, 3.4, and 3.8 m/s, six degrees inclined at 2.6, 2.8, and 3.0 m/s, and six degrees declined at 2.6, 2.8, 3.0, and 3.4 m/s. We estimated GRFs using a set of linear models and a recurrent neural network, which used speed, slope, and plantar pressure as inputs. We also tested eliminating speed and slope as inputs. The recurrent neural network outperformed the linear model across all conditions, especially with the prediction of anterior–posterior GRFs. Eliminating speed and slope as model inputs had little effect on performance. We also demonstrate that subject−specific model training can reduce errors from 8% to 3%. With such low errors, researchers can use these wearable−based GRFs to understand running performance or injuries in real−world settings. Full article
(This article belongs to the Topic Human Movement Analysis)
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13 pages, 1026 KiB  
Article
Near-Fall Detection in Unexpected Slips during Over-Ground Locomotion with Body-Worn Sensors among Older Adults
by Shuaijie Wang, Fabio Miranda, Yiru Wang, Rahiya Rasheed and Tanvi Bhatt
Sensors 2022, 22(9), 3334; https://doi.org/10.3390/s22093334 - 27 Apr 2022
Cited by 5 | Viewed by 2514
Abstract
Slip-induced falls are a growing health concern for older adults, and near-fall events are associated with an increased risk of falling. To detect older adults at a high risk of slip-related falls, this study aimed to develop models for near-fall event detection based [...] Read more.
Slip-induced falls are a growing health concern for older adults, and near-fall events are associated with an increased risk of falling. To detect older adults at a high risk of slip-related falls, this study aimed to develop models for near-fall event detection based on accelerometry data collected by body-fixed sensors. Thirty-four healthy older adults who experienced 24 laboratory-induced slips were included. The slip outcomes were first identified as loss of balance (LOB) and no LOB (NLOB), and then the kinematic measures were compared between these two outcomes. Next, all the slip trials were split into a training set (90%) and a test set (10%) at sample level. The training set was used to train both machine learning models (n = 2) and deep learning models (n = 2), and the test set was used to evaluate the performance of each model. Our results indicated that the deep learning models showed higher accuracy for both LOB (>64%) and NLOB (>90%) classifications than the machine learning models. Among all the models, the Inception model showed the highest classification accuracy (87.5%) and the largest area under the receiver operating characteristic curve (AUC), indicating that the model is an effective method for near-fall (LOB) detection. Our approach can be helpful in identifying individuals at the risk of slip-related falls before they experience an actual fall. Full article
(This article belongs to the Topic Human Movement Analysis)
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11 pages, 1427 KiB  
Article
Development of a Novel Coaching Platform to Improve Tackle Technique in Youth Rugby Players: A Proof of Concept
by Ed Daly, Patrick Esser, Alan Griffin, Damien Costello, Justin Servis, David Gallagher and Lisa Ryan
Sensors 2022, 22(9), 3315; https://doi.org/10.3390/s22093315 - 26 Apr 2022
Cited by 1 | Viewed by 2191
Abstract
Rugby union is a field sport that is played at amateur and professional levels by male and female players globally. One of the most prevalent injury risks associated with the sport involves tackle collisions with opposition players. This suggests that a targeted injury [...] Read more.
Rugby union is a field sport that is played at amateur and professional levels by male and female players globally. One of the most prevalent injury risks associated with the sport involves tackle collisions with opposition players. This suggests that a targeted injury reduction strategy could focus on the tackle area in the game. In amateur rugby union, injuries to the head, face and shoulder are the most common injury sites in youth rugby playing populations. A suboptimal tackle technique may contribute to an increased injury risk in these populations. One proposed mitigation strategy to reduce tackle-related injuries in youth populations may be to increase tackle proficiency by coaching an effective tackle technique. The present study aimed to demonstrate a proof of concept for a tackle technique coaching platform using inertial measurement units (IMUs) and a bespoke mobile application developed for a mobile device (i.e., a mobile phone). The test battery provided a proof of concept for the primary objective of modelling the motion of a player in a tackle event. The prototype (bespoke mobile application) modelled the IMU in a 3D space and demonstrated the orientation during a tackle event. The participants simulated ten tackle events that were ten degrees above and ten degrees below the zero degree of approach, and these (unsafe tackles) were indicated by a red light on the mobile display unit. The parameters of ten degrees above and below the zero angle of approach were measured using an inclinometer mobile application. These tackle event simulations provided a real-time stream of data that displayed the angle of tackles on a mobile device. The novel coaching platform could therefore constitute part of an injury reduction strategy for amateur or novice coaches to instruct safer tackle practice in youth rugby playing populations. Full article
(This article belongs to the Topic Human Movement Analysis)
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20 pages, 4095 KiB  
Article
Hand Motion Analysis during the Execution of the Action Research Arm Test Using Multiple Sensors
by Jesus Fernando Padilla-Magaña, Esteban Peña-Pitarch, Isahi Sánchez-Suarez and Neus Ticó-Falguera
Sensors 2022, 22(9), 3276; https://doi.org/10.3390/s22093276 - 24 Apr 2022
Cited by 2 | Viewed by 2466
Abstract
The Action Research Arm Test (ARAT) is a standardized outcome measure that can be improved by integrating sensors for hand motion analysis. The purpose of this study is to measure the flexion angle of the finger joints and fingertip forces during the performance [...] Read more.
The Action Research Arm Test (ARAT) is a standardized outcome measure that can be improved by integrating sensors for hand motion analysis. The purpose of this study is to measure the flexion angle of the finger joints and fingertip forces during the performance of three subscales (Grasp, Grip, and Pinch) of the ARAT, using a data glove (CyberGlove II®) and five force-sensing resistors (FSRs) simultaneously. An experimental study was carried out with 25 healthy subjects (right-handed). The results showed that the mean flexion angles of the finger joints required to perform the 16 activities were Thumb (Carpometacarpal Joint (CMC) 28.56°, Metacarpophalangeal Joint (MCP) 26.84°, and Interphalangeal Joint (IP) 13.23°), Index (MCP 46.18°, Index Proximal Interphalangeal Joint (PIP) 38.89°), Middle (MCP 47.5°, PIP 42.62°), Ring (MCP 44.09°, PIP 39.22°), and Little (MCP 31.50°, PIP 22.10°). The averaged fingertip force exerted in the Grasp Subscale was 8.2 N, in Grip subscale 6.61 N and Pinch subscale 3.89 N. These results suggest that the integration of multiple sensors during the performance of the ARAT has clinical relevance, allowing therapists and other health professionals to perform a more sensitive, objective, and quantitative assessment of the hand function. Full article
(This article belongs to the Topic Human Movement Analysis)
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16 pages, 2466 KiB  
Article
Inertial Sensor-to-Segment Calibration for Accurate 3D Joint Angle Calculation for Use in OpenSim
by Giacomo Di Raimondo, Benedicte Vanwanseele, Arthur van der Have, Jill Emmerzaal, Miel Willems, Bryce Adrian Killen and Ilse Jonkers
Sensors 2022, 22(9), 3259; https://doi.org/10.3390/s22093259 - 24 Apr 2022
Cited by 11 | Viewed by 4157
Abstract
Inertial capture (InCap) systems combined with musculoskeletal (MSK) models are an attractive option for monitoring 3D joint kinematics in an ecological context. However, the primary limiting factor is the sensor-to-segment calibration, which is crucial to estimate the body segment orientations. Walking, running, and [...] Read more.
Inertial capture (InCap) systems combined with musculoskeletal (MSK) models are an attractive option for monitoring 3D joint kinematics in an ecological context. However, the primary limiting factor is the sensor-to-segment calibration, which is crucial to estimate the body segment orientations. Walking, running, and stair ascent and descent trials were measured in eleven healthy subjects with the Xsens InCap system and the Vicon 3D motion capture (MoCap) system at a self-selected speed. A novel integrated method that combines previous sensor-to-segment calibration approaches was developed for use in a MSK model with three degree of freedom (DOF) hip and knee joints. The following were compared: RMSE, range of motion (ROM), peaks, and R2 between InCap kinematics estimated with different calibration methods and gold standard MoCap kinematics. The integrated method reduced the RSME for both the hip and the knee joints below 5°, and no statistically significant differences were found between MoCap and InCap kinematics. This was consistent across all the different analyzed movements. The developed method was integrated on an MSK model workflow, and it increased the sensor-to-segment calibration accuracy for an accurate estimate of 3D joint kinematics compared to MoCap, guaranteeing a clinical easy-to-use approach. Full article
(This article belongs to the Topic Human Movement Analysis)
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12 pages, 1901 KiB  
Article
Investigation of Impact of Walking Speed on Forces Acting on a Foot–Ground Unit
by Barbara Jasiewicz, Ewa Klimiec, Piotr Guzdek, Grzegorz Kołaszczyński, Jacek Piekarski, Krzysztof Zaraska and Tomasz Potaczek
Sensors 2022, 22(8), 3098; https://doi.org/10.3390/s22083098 - 18 Apr 2022
Cited by 1 | Viewed by 2300
Abstract
Static and dynamic methods can be used to assess the way a foot is loaded. The research question is how the pressure on the feet would vary depending on walking/running speed. This study involved 20 healthy volunteers. Dynamic measurement of foot pressure was [...] Read more.
Static and dynamic methods can be used to assess the way a foot is loaded. The research question is how the pressure on the feet would vary depending on walking/running speed. This study involved 20 healthy volunteers. Dynamic measurement of foot pressure was performed using the Ortopiezometr at normal, slow, and fast paces of walking. Obtained data underwent analysis in a “Steps” program. Based on the median, the power generated by the sensors during the entire stride period is the highest during a fast walk, whereas based on the average; a walk or slow walk prevails. During a fast walk, the difference between the mean and the median of the stride period is the smallest. Regardless of the pace of gait, the energy released per unit time does not depend on the paces of the volunteers’ gaits. Conclusions: Ortopiezometr is a feasible tool for the dynamic measurement of foot pressure. For investigations on walking motions, the plantar pressure analysis system, which uses the power generated on sensors installed in the insoles of shoes, is an alternative to force or energy measurements. Regardless of the pace of the walk, the amounts of pressure applied to the foot during step are similar among healthy volunteers. Full article
(This article belongs to the Topic Human Movement Analysis)
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41 pages, 10912 KiB  
Systematic Review
Analysis of the Active Measurement Systems of the Thoracic Range of Movements of the Spine: A Systematic Review and a Meta-Analysis
by Pablo Esteban-González, Eleuterio A. Sánchez-Romero and Jorge Hugo Villafañe
Sensors 2022, 22(8), 3042; https://doi.org/10.3390/s22083042 - 15 Apr 2022
Cited by 3 | Viewed by 2736
Abstract
(1) Objective: to analyze current active noninvasive measurement systems of the thoracic range of movements of the spine. (2) Methods: A systematic review and meta-analysis were performed that included observational or clinical trial studies published in English or Spanish, whose subjects were healthy [...] Read more.
(1) Objective: to analyze current active noninvasive measurement systems of the thoracic range of movements of the spine. (2) Methods: A systematic review and meta-analysis were performed that included observational or clinical trial studies published in English or Spanish, whose subjects were healthy human males or females ≥18 years of age with reported measurements of thoracic range of motion measured with an active system in either flexion, extension, lateral bending, or axial rotation. All studies that passed the screening had a low risk of bias and good methodological results, according to the PEDro and MINORS scales. The mean values and 95% confidence interval of the reported measures were calculated for different types of device groups. To calculate the differences between the type of device measures, studies were pooled for different types of device groups using Review Manager software. (3) Results: 48 studies were included in the review; all had scores higher than 7.5 over 10 on the PEDro and MINORs methodological rating scales, collecting a total of 2365 healthy subjects, 1053 males and 1312 females; they were 39.24 ± 20.64 years old and had 24.44 ± 3.81 kg/m2 body mass indexes on average. We summarized and analyzed a total of 11,892 measurements: 1298 of flexoextension, 1394 of flexion, 1021 of extension, 491 of side-to-side lateral flexion, 637 of right lateral flexion, 607 of left lateral flexion, 2170 of side-to-side rotation, 2152 of right rotation and 2122 of left rotation. (4) Conclusions: All collected and analyzed measurements of physiological movements of the dorsal spine had very disparate results from each other, the cause of the reason for such analysis is that the measurement protocols of the different types of measurement tools used in these measurements are different and cause measurement biases. To solve this, it is proposed to establish a standardized measurement protocol for all tools. Full article
(This article belongs to the Topic Human Movement Analysis)
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