Influence of muscle fatigue on electromyogram–kinematic correlation during robot-assisted upper limb training. (March 2020)

• Record Type: Journal Article
• Authors: Poyil, Azeemsha T; Steuber, Volker; Amirabdollahian, Farshid
• Is Part Of: Journal of rehabilitation and assistive technologies engineering. Volume 7(2020)
• Publication Date: 2020-03
• Subjects: Human–robot interaction -- upper limb training -- muscle fatigue -- electromyogram -- kinematic correlation; Rehabilitation technology -- Periodicals; 617.03
• DOI: 10.1177/2055668320903014
• Languages: English
• ISSNs: 2055-6683

Abstract

Introduction: Studies on adaptive robot-assisted upper limb training interactions do not often consider the implications of muscle fatigue sufficiently. Methods: To explore this, we initially assessed muscle fatigue in 10 healthy subjects using two electromyogram features, namely average power and median power frequency, during an assist-as-needed interaction with HapticMaster robot. Since robotic assistance resulted in a variable fatigue profile across participants, a completely tiring experiment, without a robot in the loop, was also designed to confirm the results. Results: A significant increase in average power and a decrease in median frequency were observed in the most active muscles. Average power in the frequency band of 0.8–2.5 Hz and median frequency in the band of 20–450 Hz are potential fatigue indicators. Also, comparing the Spearman's correlation coefficients (between the electromyogram average power and the kinematic force) across trials indicated that correlation was reduced as individual muscles were fatigued. Conclusions: Confirming fatigue indicators, this study concludes that robotic assistance based on user's performance resulted in lesser muscle fatigue, which caused an increase in electromyogram–force correlation. We now intend to utilise the electromyogram and kinematic features for auto-adaptation of therapeutic human–robot interactions.