Applied Bionics and Biomechanics

Integrating Wearable and AI Techniques to Predict and Prevent Musculoskeletal Injury and Assist Rehabilitation

Publishing date
01 Jan 2023
Submission deadline
02 Sep 2022

Lead Editor
Guest Editors

1Auckland University, Auckland, New Zealand

2University of Tokyo, Tokyo, Japan

3Sun Yat-Sen University, Guangzhou, China

This issue is now closed for submissions.

Integrating Wearable and AI Techniques to Predict and Prevent Musculoskeletal Injury and Assist Rehabilitation

This issue is now closed for submissions.


Biomechanical investigations have been extensively employed to analyse the neuro-musculoskeletal control and mechanical mechanism of sports injuries, clinical pathology, and rehabilitative interventions and functional evaluation. Current approaches include (but not limit) the techniques of traditional lab-based experimental motion capture studies and mathematical modelling, rigid musculoskeletal modelling using several software or platforms, and continuum Finite Element (FE) mechanics simulation. However, the techniques are often employed solely in the past literature. Current development of wearable technologies and advanced machine learning or artificial intelligence (AI) techniques should promise to correlate all these factors. Integration of wearables and statistical techniques with experimental and computational approaches would be a promising development and advance for the understanding of injury and rehabilitation mechanisms in the human musculoskeletal system.

Researchers of different fields, such as sports scientists, bioengineers, clinicians, and physical therapists, may adopt different approaches as per the skills acquired from their education and research background. However, a simple approach may lack a comprehensive investigation of the biological system in the musculoskeletal complex. For example, mathematical modelling may lack the dynamic parameters of experiments or wearable data collected from real-life scenarios. These barriers may be overcome via measurement and data collection with wearable sensors. Lab-based experiments may reveal in-vitro biomechanical loadings while lacking in-vivo tissue loadings. Furthermore, the computational FE analysis could simulate the internal tissue (bone, cartilage, or ligament) loadings but shall consider the input parameters (boundary conditions and loadings) from experimental or wearables for validation. With the development of cross-disciplinary collaboration, the integration of interdisciplinary skills and techniques may provide knowledge for sports, clinical and rehabilitation biomechanics from different perspectives, thus contributing to a comprehensive understanding of the injury and rehabilitation in the musculoskeletal system.

The primary aim of this Special Issue is to collect the original research articles and review articles with the integration of either (but not limited to) above-mentioned approaches to investigate the complex biomechanical mechanisms of injury and rehabilitation in the musculoskeletal system. Specifically, this Special Issue would like to publish studies on experiment-driven (collected from lab or wearables) computational MSK and FE modelling of neuro-muscular, tendon, bone, and joint (ligament and cartilage) tissues for the injury and rehabilitation of the musculoskeletal system.

Potential topics include but are not limited to the following:

  • Biomechanical mechanism of sports performance and injury
  • Neuro-muscular contribution of human movement
  • Computational biomechanics of FE and MSK modelling
  • Neuromechanical interface in clinical biomechanics
  • Muscle and tendon biomechanics
  • Bone and joint biomechanics
  • Orthopaedic biomechanics
  • Wearable technology and machine learning
  • Form and function in the musculoskeletal system
Applied Bionics and Biomechanics
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.