Musculoskeletal Disorders and Diseases: Biomechanical Modeling in Sport, Health, Rehabilitation and Ergonomics

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 2133

Special Issue Editor


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Guest Editor
International Institute of Biomechanics and Occupational Ergonomics, Université de Toulon, CS60584, 83041 Toulon, France
Interests: musculoskeletal disorders; systematic reviews and meta-analysis; occupational health; ergonomics; biomechanics; MSD prevalence; safety; public health
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Special Issue Information

Dear Colleagues,

Protecting people at work and at leisure, and improving their quality of life, is one of the major challenges of our century. From this perspective, understanding the mechanisms that lead to the development of musculoskeletal disorders and diseases is a major multidisciplinary scientific challenge. This Special Issue is dedicated to recent advances in biomechanical modeling research used to explore and understand the musculoskeletal system (macro- and microscopic). Computational techniques, biomechanical calculation tools and numerical tools enable us to quantify and qualify the most important parameters (biomechanical, physiological, biological or environmental) involved in the onset, prevention and reduction of the effects of musculoskeletal disorders and/or the development of musculoskeletal diseases. They can be used as a complement to experimental protocols, clinical studies, process design, ergonomics, etc., to study, evaluate and understand various situations in life, such as repeated movements in the workplace, evaluation of leisure-time physical activities, analysis of sporting movements to assess performance, design of new equipment to compensate for a motor impairment, proposal of new recommendations in a clinical setting, etc. We support all articles promoting the latest research in the fields of sport, health, rehabilitation and ergonomics that contribute to improving people's health and quality of life.

Prof. Dr. Philippe Gorce
Guest Editor

Manuscript Submission Information

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Keywords

  • musculoskeletal disorders
  • musculoskeletal diseases
  • injury biomechanics
  • muscle biomechanics dynamic and kinematic modeling
  • gait and posture
  • muscle electromyography
  • motion analysis
  • postural control and balance
  • occupational health
  • occupational ergonomics
  • sport medicine
  • sport performance
  • quality of life

Published Papers (2 papers)

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Research

16 pages, 2874 KiB  
Article
Compensation Method for Missing and Misidentified Skeletons in Nursing Care Action Assessment by Improving Spatial Temporal Graph Convolutional Networks
by Xin Han, Norihiro Nishida, Minoru Morita, Takashi Sakai and Zhongwei Jiang
Bioengineering 2024, 11(2), 127; https://doi.org/10.3390/bioengineering11020127 - 29 Jan 2024
Viewed by 789
Abstract
With the increasing aging population, nursing care providers have been facing a substantial risk of work-related musculoskeletal disorders (WMSDs). Visual-based pose estimation methods, like OpenPose, are commonly used for ergonomic posture risk assessment. However, these methods face difficulty when identifying overlapping and interactive [...] Read more.
With the increasing aging population, nursing care providers have been facing a substantial risk of work-related musculoskeletal disorders (WMSDs). Visual-based pose estimation methods, like OpenPose, are commonly used for ergonomic posture risk assessment. However, these methods face difficulty when identifying overlapping and interactive nursing tasks, resulting in missing and misidentified skeletons. To address this, we propose a skeleton compensation method using improved spatial temporal graph convolutional networks (ST-GCN), which integrates kinematic chain and action features to assess skeleton integrity and compensate for it. The results verified the effectiveness of our approach in optimizing skeletal loss and misidentification in nursing care tasks, leading to improved accuracy in calculating both skeleton joint angles and REBA scores. Moreover, comparative analysis against other skeleton compensation methods demonstrated the superior performance of our approach, achieving an 87.34% REBA accuracy score. Collectively, our method might hold promising potential for optimizing the skeleton loss and misidentification in nursing care tasks. Full article
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17 pages, 5057 KiB  
Article
Modeling and Analysis of Foot Function in Human Gait Using a Two-Degrees-of-Freedom Inverted Pendulum Model with an Arced Foot
by Qian Xiang, Shijie Guo, Jiaxin Wang, Kazunobu Hashimoto, Yong Liu and Lei Liu
Bioengineering 2023, 10(12), 1344; https://doi.org/10.3390/bioengineering10121344 - 22 Nov 2023
Viewed by 936
Abstract
Gait models are important for the design and control of lower limb exoskeletons. The inverted pendulum model has advantages in simplicity and computational efficiency, but it also has the limitations of oversimplification and lack of realism. This paper proposes a two-degrees-of-freedom (DOF) inverted [...] Read more.
Gait models are important for the design and control of lower limb exoskeletons. The inverted pendulum model has advantages in simplicity and computational efficiency, but it also has the limitations of oversimplification and lack of realism. This paper proposes a two-degrees-of-freedom (DOF) inverted pendulum walking model by considering the knee joints for describing the characteristics of human gait. A new parameter, roll factor, is defined to express foot function in the model, and the relationships between the roll factor and gait parameters are investigated. Experiments were conducted to verify the model by testing seven healthy adults at different walking speeds. The results demonstrate that the roll factor has a strong relationship with other gait kinematics parameters, so it can be used as a simple parameter for expressing gait kinematics. In addition, the roll factor can be used to identify walking styles with high accuracy, including small broken step walking at 99.57%, inefficient walking at 98.14%, and normal walking at 99.43%. Full article
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