Title :
An analysis of physiological signals as a measure of task engagement in a multi-limb-coordination motor-learning task
Author :
Spencer A. Murray;Michael Goldfarb
Author_Institution :
Vanderbilt University, Nashville, TN, 37212 USA
Abstract :
There is widespread agreement in the physical rehabilitation community that task engagement is essential to effective neuromuscular recovery. Despite this, there are no clear measures of such task engagement. This paper assesses the extent to which certain physiological measurements might provide a measure of task engagement. In previous studies, correlations between mental focus and certain physiological measurements have been observed in subjects performing tasks requiring mental effort. In this study, the authors analyzed whether these signals showed similar correlation when subjects performed a multi-limb-coordination motor-learning task. Subjects played a video game which required the use of both arms and one leg to play a simplified electronic drum set with varying difficulty. Heart rate (HR), skin conductance level (SCL), and facial electromyogram (EMG) were recorded while the subjects played. Analysis of the recordings showed statistically significant correlations relating task difficulty to SCL, HR and EMG amplitude in corrugator supercilii. No statistically significant correlation was observed between task difficulty and EMG in frontalis.
Keywords :
"Electromyography","Heart rate","Physiology","Correlation","Robots","Medical treatment","Skin"
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
Electronic_ISBN :
1558-4615
DOI :
10.1109/EMBC.2015.7318803