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- Publisher Website: 10.1142/S0219519417500695
- Scopus: eid_2-s2.0-85020885043
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Article: Estimating muscle forces and knee joint torque using surface electromyography: A musculoskeletal biomechanical model
Title | Estimating muscle forces and knee joint torque using surface electromyography: A musculoskeletal biomechanical model |
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Authors | |
Keywords | joint torque model calibration muscle contraction Musculoskeletal model surface EMG |
Issue Date | 2017 |
Citation | Journal of Mechanics in Medicine and Biology, 2017, v. 17, n. 4, article no. 1750069 How to Cite? |
Abstract | Surface electromyography (sEMG) is a useful tool for revealing the underlying musculoskeletal dynamic properties in the human body movement. In this paper, a musculoskeletal biomechanical model which relates the sEMG and knee joint torque is proposed. First, the dynamic model relating sEMG to skeletal muscle activation considering frequency and amplitude is built. Second, a muscle contraction model based on sliding-filament theory is developed to reflect the physiological structure and micro mechanical properties of the muscle. The muscle force and displacement vectors are determined and the transformation from muscle force to knee joint moment is realized, and finally a genetic algorithm-based calibration method for the Newton-Euler dynamics and overall musculoskeletal biomechanical model is put forward. Following the model calibration, the flexion/extension (FE) knee joint torque of eight subjects under different walking speeds was predicted. Results show that the forward biomechanical model can capture the general shape and timing of the joint torque, with normalized mean residual error (NMRE) of ∼10.01%, normalized root mean square error (NRMSE) of ∼12.39% and cross-correlation coefficient of ∼0.926. The musculoskeletal biomechanical model proposed and validated in this work could facilitate the study of neural control and how muscle forces generate and contribute to the knee joint torque during human movement. |
Persistent Identifier | http://hdl.handle.net/10722/327147 |
ISSN | 2023 Impact Factor: 0.8 2023 SCImago Journal Rankings: 0.189 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Chen, Jiangcheng | - |
dc.contributor.author | Zhang, Xiaodong | - |
dc.contributor.author | Gu, Linxia | - |
dc.contributor.author | Nelson, Carl | - |
dc.date.accessioned | 2023-03-31T05:29:14Z | - |
dc.date.available | 2023-03-31T05:29:14Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Journal of Mechanics in Medicine and Biology, 2017, v. 17, n. 4, article no. 1750069 | - |
dc.identifier.issn | 0219-5194 | - |
dc.identifier.uri | http://hdl.handle.net/10722/327147 | - |
dc.description.abstract | Surface electromyography (sEMG) is a useful tool for revealing the underlying musculoskeletal dynamic properties in the human body movement. In this paper, a musculoskeletal biomechanical model which relates the sEMG and knee joint torque is proposed. First, the dynamic model relating sEMG to skeletal muscle activation considering frequency and amplitude is built. Second, a muscle contraction model based on sliding-filament theory is developed to reflect the physiological structure and micro mechanical properties of the muscle. The muscle force and displacement vectors are determined and the transformation from muscle force to knee joint moment is realized, and finally a genetic algorithm-based calibration method for the Newton-Euler dynamics and overall musculoskeletal biomechanical model is put forward. Following the model calibration, the flexion/extension (FE) knee joint torque of eight subjects under different walking speeds was predicted. Results show that the forward biomechanical model can capture the general shape and timing of the joint torque, with normalized mean residual error (NMRE) of ∼10.01%, normalized root mean square error (NRMSE) of ∼12.39% and cross-correlation coefficient of ∼0.926. The musculoskeletal biomechanical model proposed and validated in this work could facilitate the study of neural control and how muscle forces generate and contribute to the knee joint torque during human movement. | - |
dc.language | eng | - |
dc.relation.ispartof | Journal of Mechanics in Medicine and Biology | - |
dc.subject | joint torque | - |
dc.subject | model calibration | - |
dc.subject | muscle contraction | - |
dc.subject | Musculoskeletal model | - |
dc.subject | surface EMG | - |
dc.title | Estimating muscle forces and knee joint torque using surface electromyography: A musculoskeletal biomechanical model | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1142/S0219519417500695 | - |
dc.identifier.scopus | eid_2-s2.0-85020885043 | - |
dc.identifier.volume | 17 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | article no. 1750069 | - |
dc.identifier.epage | article no. 1750069 | - |
dc.identifier.isi | WOS:000403716700007 | - |