Intramuscular EMG-driven Musculoskeletal Modelling: Towards Implanted Muscle Interfacing in Spinal Cord Injury Patients
Journal article, 2021

Objective: Surface EMG-driven modelling has been proposed as a means to control assistive devices by estimating joint torques. Implanted EMG sensors have several advantages over wearable sensors but provide a more localized information on muscle activity, which may impact torque estimates. Here, we tested and compared the use of surface and intramuscular EMG measurements for the estimation of required assistive joint torques using EMG driven modelling. Methods: Four healthy subjects and three incomplete spinal cord injury (SCI) patients performed walking trials at varying speeds. Motion capture marker trajectories, surface and intramuscular EMG, and ground reaction forces were measured concurrently. Subject-specific musculoskeletal models were developed for all subjects, and inverse dynamics analysis was performed for all individual trials. EMG-driven modelling based joint torque estimates were obtained from surface and intramuscular EMG. Results: The correlation between the experimental and predicted joint torques was similar when using intramuscular or surface EMG as input to the EMG-driven modelling estimator in both healthy individuals and patients. Conclusion: We have provided the first comparison of non-invasive and implanted EMG sensors as input signals for torque estimates in healthy individuals and SCI patients. Significance: Implanted EMG sensors have the potential to be used as a reliable input for assistive exoskeleton joint torque actuation.


Legged locomotion

assistive technology


musculoskeletal model

human-machine interface




EMG driven modelling

spinal cord injury




Moon Ki Jung

Imperial College London

Silvia Muceli

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Biomedical Signals and Systems

Camila Rodrigues

Cajal Institute

Alvaro Megia-Garcia

Spanish National Research Council (CSIC)

Alejandro Pascual-Valdunciel

Cajal Institute

António Del-Ama

Universidad Rey Juan Carlos

Ángel Gil-Agudo

Spanish National Research Council (CSIC)

Juan Moreno

Consejo Nacional de Investigaciones Cientificas y Tecnicas

Filipe O. Barroso

Cajal Institute

Jose L. Pons

Spanish National Research Council (CSIC)

Dario Farina

Imperial College London

IEEE Transactions on Biomedical Engineering

0018-9294 (ISSN)

Vol. In Press

Subject Categories

Medical Laboratory and Measurements Technologies

Other Medical Engineering

Control Engineering

Areas of Advance

Health Engineering





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Latest update

8/9/2021 7