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Frontiers in NeuroroboticsNeurosciencePeer-reviewed journal article

EEG Spectral Feature Modulations Associated with Fatigue in Robot-Mediated Upper Limb Gross Motor and Fine Motor Interactions

Udeshika Chaturangee DissanayakeiD, Volker SteuberiD, Farshid AmirabdollahianiD

PDFDOIPreprint

Abstract

This paper investigates the EEG spectral feature modulations associated with fatigue induced by robot-mediated upper limb gross motor and fine motor interactions. Twenty healthy participants were randomly assigned to either perform a gross motor interaction with HapticMASTER or a fine motor interaction with SCRIPT passive orthosis for 20 minutes or until volitional fatigue. EEG relative and ratio band power measures were estimated from the data recorded before and after the interactions. Paired-samples t-tests found a significant increase in relative alpha band power on FC3, C3, P3 electrodes, and ({theta} + )/{beta} and /{beta} on C3 electrode following the gross motor interaction. Conversely, relative delta band power on C3 significantly decreased. A significant increase in relative alpha band power on FP1, C3 electrodes and relative theta band power on C4 electrode were found following the fine motor interaction whereas relative delta band power on FP1 electrode significantly decreased. Most participants reported an increase in their physical fatigue level following the gross movements and an increase in their mental fatigue level following the fine movements. Findings affirm that changes to localised brain activity patterns are an indication of fatigue developed from the robot-mediated interactions. It can be concluded that regional differences in the prominent EEG spectral features are most likely due to the differences in the nature of the task (fine/gross motor and distal/proximal upper limb) that may have differently altered an individuals physical and mental fatigue level. The findings could potentially be utilised to monitor and moderate fatigue during robot-mediated post-stroke therapies.

Citations
19
FWCI
2.32
Field percentile
top 12%

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