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Bioengineering
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Bioengineering of the Motor System
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Bioengineering of the Motor System

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomechanics and Sports Medicine".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 5411

Special Issue Editor

Prof. Dr. Carlo Albino Frigo

E-Mail Website
Guest Editor
Movement Biomechanics and Motor Control Lab, DEIB, Politecnico di Milano, Milan, Italy
Interests: movement biomechanics; dynamics simulation; muscle function; muscle synergies; functional surgery; orthopedic surgery; compensation strategies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The complex phenomena involved in the control and realization of movement in humans are multifaceted. The motor system involves a neural control system, a mechanical structure, an actuation system, and mechanisms of energy supply. Knowledge about their function has considerably progressed over the years, but many aspects are still worth investigating and offer new insights. A substantial contribution to the advancement of knowledge is provided by new technologies that offer the possibility of analysing biological phenomena in detail and designing clinical applications. Through these new investigation approaches, bioengineering has become central to building on our understanding of both normal and pathological human posture and movement. Bioengineering of the motor system therefore presents itself as a new discipline, where physiology, clinical experience, and technology are integrated into methods for measuring, visualizing, and interpreting the biological phenomena connected to motor function. This Special Issue aims at collecting experiences and demonstrations from this multidisciplinary approach. Contributions in the various areas of interest are expected to provide a picture of the state of the art of this discipline and to show its potential and perspective for future advancements.

Researchers are welcome to submit original publications, systematic reviews, or case studies to this Special Issue.

Prof. Dr. Carlo Albino Frigo
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • movement biomechanics
  • motor control
  • human movement energetics
  • neural and EMG signal processing
  • posture and gait analysis
  • reaching and grasping
  • musculoskeletal modelling
  • dynamic simulation
  • motor rehabilitation
  • orthopaedic biomechanics
  • prosthetics and orthotics
  • functional electrical stimulation
  • sport biomechanics
  • technologies for monitoring and rehabilitation
  • motion capture

Published Papers (7 papers)

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Research

13 pages, 1278 KiB  
Article
Effects of Action Observation Plus Motor Imagery Administered by Immersive Virtual Reality on Hand Dexterity in Healthy Subjects
by Paola Adamo, Gianluca Longhi, Federico Temporiti, Giorgia Marino, Emilia Scalona, Maddalena Fabbri-Destro, Pietro Avanzini and Roberto Gatti
Bioengineering 2024, 11(4), 398; https://doi.org/10.3390/bioengineering11040398 - 19 Apr 2024
Viewed by 377
Abstract
Action observation and motor imagery (AOMI) are commonly delivered through a laptop screen. Immersive virtual reality (VR) may enhance the observer’s embodiment, a factor that may boost AOMI effects. The study aimed to investigate the effects on manual dexterity of AOMI delivered through [...] Read more.
Action observation and motor imagery (AOMI) are commonly delivered through a laptop screen. Immersive virtual reality (VR) may enhance the observer’s embodiment, a factor that may boost AOMI effects. The study aimed to investigate the effects on manual dexterity of AOMI delivered through immersive VR compared to AOMI administered through a laptop. To evaluate whether VR can enhance the effects of AOMI, forty-five young volunteers were enrolled and randomly assigned to the VR-AOMI group, who underwent AOMI through immersive VR, the AOMI group, who underwent AOMI through a laptop screen, or the control group, who observed landscape video clips. All participants underwent a 5-day treatment, consisting of 12 min per day. We investigated between and within-group differences after treatments relative to functional manual dexterity tasks using the Purdue Pegboard Test (PPT). This test included right hand (R), left hand (L), both hands (B), R + L + B, and assembly tasks. Additionally, we analyzed kinematics parameters including total and sub-phase duration, peak and mean velocity, and normalized jerk, during the Nine-Hole Peg Test to examine whether changes in functional scores may also occur through specific kinematic patterns. Participants were assessed at baseline (T0), after the first training session (T1), and at the end of training (T2). A significant time by group interaction and time effects were found for PPT, where both VR-AOMI and AOMI groups improved at the end of training. Larger PPT-L task improvements were found in the VR-AOMI group (d: 0.84, CI95: 0.09–1.58) compared to the AOMI group from T0 to T1. Immersive VR used for the delivery of AOMI speeded up hand dexterity improvements. Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
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17 pages, 5127 KiB  
Article
Balance Evaluation Based on Walking Experiments with Exoskeleton Interference
by Liping Wang, Xin Li, Yiying Peng, Jianda Han and Juanjuan Zhang
Bioengineering 2024, 11(4), 386; https://doi.org/10.3390/bioengineering11040386 - 16 Apr 2024
Viewed by 447
Abstract
The impairment of walking balance function seriously affects human health and will lead to a significantly increased risk of falling. It is important to assess and improve the walking balance of humans. However, existing evaluation methods for human walking balance are relatively subjective, [...] Read more.
The impairment of walking balance function seriously affects human health and will lead to a significantly increased risk of falling. It is important to assess and improve the walking balance of humans. However, existing evaluation methods for human walking balance are relatively subjective, and the selected metrics lack effectiveness and comprehensiveness. We present a method to construct a comprehensive evaluation index of human walking balance. We used it to generate personal and general indexes. We first pre-selected some preliminary metrics of walking balance based on theoretical analysis. Seven healthy subjects walked with exoskeleton interference on a treadmill at 1.25 m/s while their ground reaction force information and kinematic data were recorded. One subject with Charcot–Marie–Tooth walked at multiple speeds without the exoskeleton while the same data were collected. Then, we picked a number of effective evaluation metrics based on statistical analysis. We finally constructed the Walking Balance Index (WBI) by combining multiple metrics using principal component analysis. The WBI can distinguish walking balance among different subjects and gait conditions, which verifies the effectiveness of our method in evaluating human walking balance. This method can be used to evaluate and further improve the walking balance of humans in subsequent simulations and experiments. Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
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11 pages, 2493 KiB  
Article
Direct Current Stimulation over the Primary Motor Cortex, Cerebellum, and Spinal Cord to Modulate Balance Performance: A Randomized Placebo-Controlled Trial
by Jitka Veldema, Teni Steingräber, Leon von Grönheim, Jana Wienecke, Rieke Regel, Thomas Schack and Christoph Schütz
Bioengineering 2024, 11(4), 353; https://doi.org/10.3390/bioengineering11040353 - 04 Apr 2024
Viewed by 559
Abstract
Objectives: Existing applications of non-invasive brain stimulation in the modulation of balance ability are focused on the primary motor cortex (M1). It is conceivable that other brain and spinal cord areas may be comparable or more promising targets in this regard. This study [...] Read more.
Objectives: Existing applications of non-invasive brain stimulation in the modulation of balance ability are focused on the primary motor cortex (M1). It is conceivable that other brain and spinal cord areas may be comparable or more promising targets in this regard. This study compares transcranial direct current stimulation (tDCS) over (i) the M1, (ii) the cerebellum, and (iii) trans-spinal direct current stimulation (tsDCS) in the modulation of balance ability. Methods: Forty-two sports students were randomized in this placebo-controlled study. Twenty minutes of anodal 1.5 mA t/tsDCS over (i) the M1, (ii) the cerebellum, and (iii) the spinal cord, as well as (iv) sham tDCS were applied to each subject. The Y Balance Test, Single Leg Landing Test, and Single Leg Squat Test were performed prior to and after each intervention. Results: The Y Balance Test showed significant improvement after real stimulation of each region compared to sham stimulation. While tsDCS supported the balance ability of both legs, M1 and cerebellar tDCS supported right leg stand only. No significant differences were found in the Single Leg Landing Test and the Single Leg Squat Test. Conclusions: Our data encourage the application of DCS over the cerebellum and spinal cord (in addition to the M1 region) in supporting balance control. Future research should investigate and compare the effects of different stimulation protocols (anodal or cathodal direct current stimulation (DCS), alternating current stimulation (ACS), high-definition DCS/ACS, closed-loop ACS) over these regions in healthy people and examine the potential of these approaches in the neurorehabilitation. Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
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17 pages, 2744 KiB  
Article
Post-Stroke Functional Changes: In-Depth Analysis of Clinical Tests and Motor-Cognitive Dual-Tasking Using Wearable Sensors
by Masoud Abdollahi, Ehsan Rashedi, Pranav Madhav Kuber, Sonia Jahangiri, Behnam Kazempour, Mary Dombovy and Nasibeh Azadeh-Fard
Bioengineering 2024, 11(4), 349; https://doi.org/10.3390/bioengineering11040349 - 02 Apr 2024
Viewed by 578
Abstract
Clinical tests like Timed Up and Go (TUG) facilitate the assessment of post-stroke mobility, but they lack detailed measures. In this study, 21 stroke survivors and 20 control participants underwent TUG, sit-to-stand (STS), and the 10 Meter Walk Test (10MWT). Tests incorporated single [...] Read more.
Clinical tests like Timed Up and Go (TUG) facilitate the assessment of post-stroke mobility, but they lack detailed measures. In this study, 21 stroke survivors and 20 control participants underwent TUG, sit-to-stand (STS), and the 10 Meter Walk Test (10MWT). Tests incorporated single tasks (STs) and motor-cognitive dual-task (DTs) involving reverse counting from 200 in decrements of 10. Eight wearable motion sensors were placed on feet, shanks, thighs, sacrum, and sternum to record kinematic data. These data were analyzed to investigate the effects of stroke and DT conditions on the extracted features across segmented portions of the tests. The findings showed that stroke survivors (SS) took 23% longer for total TUG (p < 0.001), with 31% longer turn time (p = 0.035). TUG time increased by 20% (p < 0.001) from STs to DTs. In DTs, turning time increased by 31% (p = 0.005). Specifically, SS showed 20% lower trunk angular velocity in sit-to-stand (p = 0.003), 21% longer 10-Meter Walk time (p = 0.010), and 18% slower gait speed (p = 0.012). As expected, turning was especially challenging and worsened with divided attention. The outcomes of our study demonstrate the benefits of instrumented clinical tests and DTs in effectively identifying motor deficits post-stroke across sitting, standing, walking, and turning activities, thereby indicating that quantitative motion analysis can optimize rehabilitation procedures. Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
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13 pages, 2200 KiB  
Article
Comparison of sEMG Onset Detection Methods for Occupational Exoskeletons on Extensive Close-to-Application Data
by Stefan Kreipe, Thomas Helbig, Hartmut Witte, Nikolaus-Peter Schumann and Christoph Anders
Bioengineering 2024, 11(2), 119; https://doi.org/10.3390/bioengineering11020119 - 25 Jan 2024
Viewed by 777
Abstract
The design of human-machine interfaces of occupational exoskeletons is essential for their successful application, but at the same time demanding. In terms of information gain, biosensoric methods such as surface electromyography (sEMG) can help to achieve intuitive control of the device, for example [...] Read more.
The design of human-machine interfaces of occupational exoskeletons is essential for their successful application, but at the same time demanding. In terms of information gain, biosensoric methods such as surface electromyography (sEMG) can help to achieve intuitive control of the device, for example by reduction of the inherent time latencies of a conventional, non-biosensoric, control scheme. To assess the reliability of sEMG onset detection under close to real-life circumstances, shoulder sEMG of 55 healthy test subjects was recorded during seated free arm lifting movements based on assembly tasks. Known algorithms for sEMG onset detection are reviewed and evaluated regarding application demands. A constant false alarm rate (CFAR) double-threshold detection algorithm was implemented and tested with different features. Feature selection was done by evaluation of signal-to-noise-ratio (SNR), onset sensitivity and precision, as well as timing error and deviation. Results of visual signal inspection by sEMG experts and kinematic signals were used as references. Overall, a CFAR algorithm with Teager-Kaiser-Energy-Operator (TKEO) as feature showed the best results with feature SNR = 14.48 dB, 91% sensitivity, 93% precision. In average, sEMG analysis hinted towards impending movements 215 ms before measurable kinematic changes. Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
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23 pages, 1640 KiB  
Article
Optimizing RNNs for EMG Signal Classification: A Novel Strategy Using Grey Wolf Optimization
by Marcos Aviles, José Manuel Alvarez-Alvarado, Jose-Billerman Robles-Ocampo , Perla Yazmín Sevilla-Camacho  and Juvenal Rodríguez-Reséndiz
Bioengineering 2024, 11(1), 77; https://doi.org/10.3390/bioengineering11010077 - 13 Jan 2024
Viewed by 877
Abstract
Accurate classification of electromyographic (EMG) signals is vital in biomedical applications. This study evaluates different architectures of recurrent neural networks for the classification of EMG signals associated with five movements of the right upper extremity. A Butterworth filter was implemented for signal preprocessing, [...] Read more.
Accurate classification of electromyographic (EMG) signals is vital in biomedical applications. This study evaluates different architectures of recurrent neural networks for the classification of EMG signals associated with five movements of the right upper extremity. A Butterworth filter was implemented for signal preprocessing, followed by segmentation into 250 ms windows, with an overlap of 190 ms. The resulting dataset was divided into training, validation, and testing subsets. The Grey Wolf Optimization algorithm was applied to the gated recurrent unit (GRU), long short-term memory (LSTM) architectures, and bidirectional recurrent neural networks. In parallel, a performance comparison with support vector machines (SVMs) was performed. The results obtained in the first experimental phase revealed that all the RNN networks evaluated reached a 100% accuracy, standing above the 93% achieved by the SVM. Regarding classification speed, LSTM ranked as the fastest architecture, recording a time of 0.12 ms, followed by GRU with 0.134 ms. Bidirectional recurrent neural networks showed a response time of 0.2 ms, while SVM had the longest time at 2.7 ms. In the second experimental phase, a slight decrease in the accuracy of the RNN models was observed, standing at 98.46% for LSTM, 96.38% for GRU, and 97.63% for the bidirectional network. The findings of this study highlight the effectiveness and speed of recurrent neural networks in the EMG signal classification task. Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
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18 pages, 3503 KiB  
Article
Walking with a Posterior Cruciate Ligament Injury: A Musculoskeletal Model Study
by Lucia Donno, Alessandro Galluzzo, Valerio Pascale, Valerio Sansone and Carlo Albino Frigo
Bioengineering 2023, 10(10), 1178; https://doi.org/10.3390/bioengineering10101178 - 11 Oct 2023
Viewed by 1068
Abstract
The understanding of the changes induced in the knee’s kinematics by a Posterior Cruciate Ligament (PCL) injury is still rather incomplete. This computational study aimed to analyze how the internal loads are redistributed among the remaining ligaments when the PCL is lesioned at [...] Read more.
The understanding of the changes induced in the knee’s kinematics by a Posterior Cruciate Ligament (PCL) injury is still rather incomplete. This computational study aimed to analyze how the internal loads are redistributed among the remaining ligaments when the PCL is lesioned at different degrees and to understand if there is a possibility to compensate for a PCL lesion by changing the hamstring’s contraction in the second half of the swing phase. A musculoskeletal model of the knee joint was used for simulating a progressive PCL injury by gradually reducing the ligament stiffness. Then, in the model with a PCL residual stiffness at 15%, further dynamic simulations of walking were performed by progressively reducing the hamstring’s force. In each condition, the ligaments tension, contact force and knee kinematics were analyzed. In the simulated PCL-injured knee, the Medial Collateral Ligament (MCL) became the main passive stabilizer of the tibial posterior translation, with synergistic recruitment of the Lateral Collateral Ligament. This resulted in an enhancement of the tibial–femoral contact force with respect to the intact knee. The reduction in the hamstring’s force limited the tibial posterior sliding and, consequently, the tension of the ligaments compensating for PCL injury decreased, as did the tibiofemoral contact force. This study does not pretend to represent any specific population, since our musculoskeletal model represents a single subject. However, the implemented model could allow the non-invasive estimation of load redistribution in cases of PCL injury. Understanding the changes in the knee joint biomechanics could help clinicians to restore patients’ joint stability and prevent joint degeneration. Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
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