Abstract

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. 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. 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. 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. Implanted EMG sensors have the potential to be used as a reliable input for assistive exoskeleton joint torque actuation.

Highlights

  • THERE has been growing interest in powered wearable assistive devices that can increase the physical performance of users

  • The results showed that the correlation between experimental and predicted joint torques was similar when using intramuscular or surface EMG as input to our model

  • These results show that intramuscular EMG (iEMG) can be used as a potential input for NMS model-based joint torque estimation, with performance similar to that of surface EMG

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Summary

Introduction

THERE has been growing interest in powered wearable assistive devices that can increase the physical performance of users. Among various myoelectric HMIs, EMGdriven neuromusculoskeletal (NMS) modelling approaches have been developed to estimate user-intended joint moments [5], [6], [7], [8], [9], [10]. These systems can operate in realtime [11] and be applied to control exoskeletons and prostheses [12], [13], [14]

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