Paper Info
Title
On Muscle Activation For Improving Robotic Rehabilitation After Spinal Cord Injury
Abstract
Spinal cord stimulation (SCS) has recently enabled humans with motor complete spinal cord injury (SCI) to independently stand and recover some lost autonomic function. However, the nature of the recovered motor activity and the interplay between SCS and motor training are not well understood. Understanding the effect of stand training and spinal stimulation on motor activity during bipedal standing is important for designing spinal rehabilitation therapies that seek to combine spinal stimulation and rehabilitative robots. In this study, we examined electromyography (EMG) data gathered from two SCI patients and six healthy subjects as they attempted standing. We analyzed the muscle activation patterns and EMG waveform shape to quantify both the changes in SCI patient motor activity with training, and the differences between healthy motor activity and SCI patient motor activity under stimulation. We also looked for correlations between the similarity in SCI patients' motor activity to healthy subjects and their overall standing ability. We found that good standing in SCI patients does not emulate healthy standing muscle activity. Furthermore, patient stand training heavily influenced motor activation patterns, but not in ways that improved standing ability. These results indicate that current training techniques do not optimally influence motor activity, and robotic rehabilitation strategies for SCI patients should target essential features of motor activity to optimize functional performance, rather than emulate healthy activity.
Year
DOI
Venue
2018
10.1109/IROS.2018.8593973
2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
Field
DocType
ISSN
Muscle activity,Rehabilitation,Spinal cord injury,Computer vision,Motor activity,Computer science,Electromyography,Muscle activation,Artificial intelligence,Physical medicine and rehabilitation,Spinal cord stimulation,Stimulation
Conference
2153-0858
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Richard Cheng1212.41
Yanan Sui2305.85
Dimitry Sayenko3131.82
Burdick, J.W.42988516.87