About this Research Topic
The musculoskeletal system is a complex multi-articular structure that provides a relative range of motion for functional activities. The basic principles of lower limb biomechanics focus on understanding the performance, the effect of injuries or diseases; however, there is still lack of knowledge in this research field particularly at the level of muscle function, control and instability. Hence, studying the biomechanical response of diseased lower limb (such as knee osteoarthritis, ACL/PCL injuries, Iliotibial Band Syndrome, Achilles Tendinitis and etc.) has always been of great interest to clinicians and researchers. Numerous experimental, theoretical, as well as computational biomechanical studies have been conducted in the hope of understanding the underlying mechanisms involved in lower limb biomechanics. While some studies have been geared towards the prevention of injuries, others deal with more effective diagnostic and treatment modalities. Experimental clinical studies, using both in-vitro and in-vivo platforms, have the ability to provide relevant information regarding the biomechanical behavior and response of the lower extremities. However, these studies are mostly costly and limited by their inability to estimate the detailed microstructural phenomenon.
In the past few decades, different approaches of modeling have emerged as powerful and practical tools for non-invasive biomechanical investigations. These modeling approaches can explore the various aspects of the lower extremities, from the response of the healthy conditions in different movements, to evaluations of the effects of different pathologies, injuries and to relevant treatment modalities and techniques. Therefore, the major goal of this Research Topic is to provide an exclusive collection of knowledge and discussions for enhancing the current methodologies and techniques for developing biomechanical models of lower limb diseases, injuries, diagnosis, rehabilitation, surgical interventions, and developing exoskeletal or assistive devices. We aim to assemble a collection of cutting-edge communications and the topics of interest include but are not limited to the following:
- Finite element analyses or EMG-driven musculoskeletal modelling for biomechanical study of diseased or treated knee / ankle joints.
- Machine-learning-based approaches (e.g., Artificial neural network, Decision tree, Random Forest, Naive Bayesian, K-nearest neighbors) for classification of diseases/injuries of lower extremities.
- Exploration of deep learning capabilities to learn representations to model disease progression.
- Computational lower limb modeling for injuries related to traffic accidents, sports, assaults, and accidents.
This Research Topic aims to attract Original Research, Methods, and Review papers from worldwide researchers in the field of lower limb biomechanics modeling. This Research Topic encourages the exchange of important research, instruction, ideas and information on all aspects of the rapidly expanding area of computer usage in biomechanics of lower extremities and focuses on their applications for evaluations of disease impact, diagnosis protocol, rehabilitation outcome, and surgical approaches.
All submissions and contributions to this Research Topic must be in line with the scope of Frontiers in Bioengineering and Biotechnology as well.
In the past few decades, different approaches of modeling have emerged as powerful and practical tools for non-invasive biomechanical investigations. These modeling approaches can explore the various aspects of the lower extremities, from the response of the healthy conditions in different movements, to evaluations of the effects of different pathologies, injuries and to relevant treatment modalities and techniques. Therefore, the major goal of this Research Topic is to provide an exclusive collection of knowledge and discussions for enhancing the current methodologies and techniques for developing biomechanical models of lower limb diseases, injuries, diagnosis, rehabilitation, surgical interventions, and developing exoskeletal or assistive devices. We aim to assemble a collection of cutting-edge communications and the topics of interest include but are not limited to the following:
- Finite element analyses or EMG-driven musculoskeletal modelling for biomechanical study of diseased or treated knee / ankle joints.
- Machine-learning-based approaches (e.g., Artificial neural network, Decision tree, Random Forest, Naive Bayesian, K-nearest neighbors) for classification of diseases/injuries of lower extremities.
- Exploration of deep learning capabilities to learn representations to model disease progression.
- Computational lower limb modeling for injuries related to traffic accidents, sports, assaults, and accidents.
This Research Topic aims to attract Original Research, Methods, and Review papers from worldwide researchers in the field of lower limb biomechanics modeling. This Research Topic encourages the exchange of important research, instruction, ideas and information on all aspects of the rapidly expanding area of computer usage in biomechanics of lower extremities and focuses on their applications for evaluations of disease impact, diagnosis protocol, rehabilitation outcome, and surgical approaches.
All submissions and contributions to this Research Topic must be in line with the scope of Frontiers in Bioengineering and Biotechnology as well.
Keywords: Biomechanics of Lower Extremities, Finite Element Modeling, Mathematical Musculoskeletal Modeling, Machine Learning Modeling, Diagnosis Enhancement, Rehabilitation Facilitation, Sport Injuries, Prosthetics, Orthotics, and Assistive Devices, Surgical Planning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
