Intramuscular EMG-driven Musculoskeletal Modelling: Towards Implanted Muscle Interfacing in Spinal Cord Injury Patients
Artikel i vetenskaplig tidskrift, 2022

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.

assistive technology

Muscles

Electrodes

Legged locomotion

EMG driven modelling

Kinematics

musculoskeletal model

Electromyography

Torque

spinal cord injury

human-machine interface

Wires

electromyography

Författare

Moon Ki Jung

Imperial College London

Silvia Muceli

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Camila Rodrigues

Instituto Cajal

Alvaro Megia-Garcia

Consejo Superior de Investigaciones Científicas (CSIC)

Alejandro Pascual-Valdunciel

Instituto Cajal

António Del-Ama

Universidad Rey Juan Carlos

Ángel Gil-Agudo

Consejo Superior de Investigaciones Científicas (CSIC)

Juan Moreno

Consejo Nacional de Investigaciones Cientificas y Tecnicas

Filipe O. Barroso

Instituto Cajal

Jose L. Pons

Consejo Superior de Investigaciones Científicas (CSIC)

Dario Farina

Imperial College London

IEEE Transactions on Biomedical Engineering

0018-9294 (ISSN) 15582531 (eISSN)

Vol. 69 1 63-74

Ämneskategorier

Medicinsk laboratorie- och mätteknik

Annan medicinteknik

Reglerteknik

Styrkeområden

Hälsa och teknik

DOI

10.1109/TBME.2021.3087137

PubMed

34097604

Mer information

Senast uppdaterat

2022-03-16