DocumentCode :
62424
Title :
Artificial Proprioceptive Feedback for Myoelectric Control
Author :
Pistohl, Tobias ; Joshi, Deepak ; Ganesh, Gowrishankar ; Jackson, Andrew ; Nazarpour, Kianoush
Author_Institution :
Inst. ofNeuroscience, Newcastle Univ., Newcastle upon Tyne, UK
Volume :
23
Issue :
3
fYear :
2015
fDate :
May-15
Firstpage :
498
Lastpage :
507
Abstract :
The typical control of myoelectric interfaces, whether in laboratory settings or real-life prosthetic applications, largely relies on visual feedback because proprioceptive signals from the controlling muscles are either not available or very noisy. We conducted a set of experiments to test whether artificial proprioceptive feedback, delivered noninvasively to another limb, can improve control of a two-dimensional myoelectrically-controlled computer interface. In these experiments, participants were required to reach a target with a visual cursor that was controlled by electromyogram signals recorded from muscles of the left hand, while they were provided with an additional proprioceptive feedback on their right arm by moving it with a robotic manipulandum. Provision of additional artificial proprioceptive feedback improved the angular accuracy of their movements when compared to using visual feedback alone but did not increase the overall accuracy quantified with the average distance between the cursor and the target. The advantages conferred by proprioception were present only when the proprioceptive feedback had similar orientation to the visual feedback in the task space and not when it was mirrored, demonstrating the importance of congruency in feedback modalities for multi-sensory integration. Our results reveal the ability of the human motor system to learn new inter-limb sensory-motor associations; the motor system can utilize task-related sensory feedback, even when it is available on a limb distinct from the one being actuated. In addition, the proposed task structure provides a flexible test paradigm by which the effectiveness of various sensory feedback and multi-sensory integration for myoelectric prosthesis control can be evaluated.
Keywords :
artificial limbs; computer interfaces; electromyography; medical robotics; medical signal processing; angular accuracy; artificial proprioceptive feedback; electromyogram signal recording; feedback modalities; flexible test paradigm; human motor system; interlimb sensory-motor associations; laboratory settings; multisensory integration; muscles; myoelectric interfaces; proprioceptive signals; real-life prosthetic applications; robotic manipulandum; task-related sensory feedback; two-dimensional myoelectrically-controlled computer interface; visual cursor; visual feedback; Accuracy; Electromyography; Muscles; Robot sensing systems; Thumb; Trajectory; Visualization; Electromyogram signal; proprioceptive feedback; sensorimotor integration;
fLanguage :
English
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2014.2355856
Filename :
6894608
Link To Document :
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