Influence of Muscle Fatigue on Electromyogram-Kinematic Correlation During Robot-Assisted Upper Limb Training

Azeemsha Thacham-Poyil, Volker Steuber, Farshid Amirabdollahian

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Introduction: Studies on adaptive robot-assisted upper limb training interactions do not often consider the implications of muscle fatigue sufficiently.
Methods: In order to explore this, we initially assessed muscle fatigue in 10 healthy subjects using electromyogram features (average power and median power frequency) during an assist-as-needed interaction with HapticMASTER robot. Spearman’s correlation study was conducted between EMG average power and kinematic force components. Since the 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 0.8-2.5Hz and median frequency in the band of 20-450Hz are potential fatigue indicators. Also, comparing the correlation coefficients across trials indicated that correlation was reduced as the muscles were fatigued.
Conclusions: Robotic assistance based on user’s performance has resulted in lesser muscle fatigue, which caused an increase in the EMG-force correlation. We now intend to utilize the electromyogram and kinematic features for the auto-adaptation of therapeutic human-robot interactions.
Original languageEnglish
JournalJournal of Rehabilitation and Assistive Technologies Engineering
Early online date16 Mar 2020
Publication statusE-pub ahead of print - 16 Mar 2020


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