Biomechanical modeling for the estimation of muscle forces: toward a common language in biomechanics, medical engineering, and neurosciences

• Published in: Journal of neuroengineering and rehabilitation Vol. 20; no. 1; pp. 1 - 11
• Main Authors: Mathieu, Emilie, Crémoux, Sylvain, Duvivier, David, Amarantini, David, Pudlo, Philippe
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 26.09.2023; BioMed Central; BMC
• Subjects: Analysis; Biomechanical engineering; Biomechanics; Biomedical engineering; Data collection; Dynamic optimization; Electromyography; Force; Forward modeling; Heterogeneity; Inverse modeling; Jargon; Kinematics; Language; Life Sciences; Modelling; Muscle forces; Muscles; Musculoskeletal modeling; Neural networks; Neurological research; Neurophysiology; Neurosciences; Optimization; Physiology; Prostheses; Review; Static optimization; Terminology; Therapeutics, Experimental; France; Forward modeling; Static optimization; Data tracking; Dynamic optimization; Musculoskeletal modeling; Muscle forces; Inverse modeling; Terminology homogenization
• ISSN: 1743-0003; 1743-0003
• DOI: 10.1186/s12984-023-01253-1

Different research fields, such as biomechanics, medical engineering or neurosciences take part in the development of biomechanical models allowing for the estimation of individual muscle forces involved in motor action. The heterogeneity of the terminology used to describe these models according to the research field is a source of confusion and can hamper collaboration between the different fields. This paper proposes a common language based on lexical disambiguation and a synthesis of the terms used in the literature in order to facilitate the understanding of the different elements of biomechanical modeling for force estimation, without questioning the relevance of the terms used in each field or the different model components or their interest. We suggest that the description should start with an indication of whether the muscle force estimation problem is solved following the physiological movement control (from the nervous drive to the muscle force production) or in the opposite direction. Next, the suitability of the model for force production estimation at a given time or for monitoring over time should be specified. Authors should pay particular attention to the method description used to find solutions, specifying whether this is done during or after data collection, with possible method adaptations during processing. Finally, the presence of additional data must be specified by indicating whether they are used to drive, assist, or calibrate the model. Describing and classifying models in this way will facilitate the use and application in all fields where the estimation of muscle forces is of real, direct, and concrete interest.