A Fair and EMG‑Validated Comparison of Recruitment Criteria, Musculotendon Models and Muscle Coordination Strategies, for the Inverse‑Dynamics Based Optimization of Muscle Forces During Gait
| Autor: | Javier Cuadrado, Florian Michaud, Mario Lamas, Urbano Lugrís |
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| Rok vydání: | 2021 |
| Předmět: |
Adult
Male Computer science 0206 medical engineering Health Informatics 02 engineering and technology Kinematics Models Biological Inverse dynamics lcsh:RC321-571 03 medical and health sciences 0302 clinical medicine Gait (human) Control theory Humans Muscle Skeletal Static optimization Musculotendon models lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Gait Electromyography Research Rehabilitation EMG validation Function (mathematics) 020601 biomedical engineering Motor coordination Biomechanical Phenomena Moment (mathematics) Lower Extremity Motor unit recruitment Muscle forces Actuator 030217 neurology & neurosurgery Algorithms Psychomotor Performance |
| Zdroj: | RUC. Repositorio da Universidade da Coruña Universitat Oberta de Catalunya (UOC) RUC: Repositorio da Universidade da Coruña Universidade da Coruña (UDC) Journal of NeuroEngineering and Rehabilitation, Vol 18, Iss 1, Pp 1-15 (2021) Journal of NeuroEngineering and Rehabilitation |
| Popis: | [Abstract] Experimental studies and EMG collections suggest that a specific strategy of muscle coordination is chosen by the central nervous system to perform a given motor task. A popular mathematical approach for solving the muscle recruitment problem is optimization. Optimization-based methods minimize or maximize some criterion (objective function or cost function) which reflects the mechanism used by the central nervous system to recruit muscles for the movement considered. The proper cost function is not known a priori, so the adequacy of the chosen function must be validated according to the obtained results. In addition of the many criteria proposed, several physiological representations of the musculotendon actuator dynamics (that prescribe constraints for the forces) along with different musculoskeletal models can be found in the literature, which hinders the selection of the best neuromusculotendon model for each application. Seeking to provide a fair base for comparison, this study measures the efficiency and accuracy of: (i) four different criteria within the static optimization approach (where the physiological character of the muscle, which affects the constraints of the forces, is not considered); (ii) three physiological representations of the musculotendon actuator dynamics: activation dynamics with elastic tendon, simplified activation dynamics with rigid tendon and rigid tendon without activation dynamics; (iii) a synergy-based method; all of them within the framework of inverse-dynamics based optimization. Motion/force/EMG gait analyses were performed on ten healthy subjects. A musculoskeletal model of the right leg actuated by 43 Hill-type muscles was scaled to each subject and used to calculate joint moments, musculotendon kinematics and moment arms. Muscle activations were then estimated using the different approaches, and these estimates were compared with EMG measurements. Although no significant differences were obtained with all the methods at statistical level, it must be pointed out that a higher complexity of the method does not guarantee better results, as the best correlations with experimental values were obtained with two simplified approaches: the static optimization and the physiological approach with simplified activation dynamics and rigid tendon, both using the sum of the squares of muscle forces as objective function. This work was funded by the Spanish MICIU under project PGC2018-095145-B-I00, co-financed by the EU through the EFRD program, and by the Galician Government under grant ED431C2019/29. Moreover, F. Michaud would like to acknowledge the support of the Spanish MINECO by means of the doctoral research contract BES-2016–076901, co-financed by the EU through the ESF program Xunta de Galicia; ED431C2019/29 |
| Databáze: | OpenAIRE |
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