NDLI: Towards robust HD EMG pattern recognition: Reducing electrode displacement effect using structural similarity

Content Provider	IEEE Xplore Digital Library
Author	Boschmann, A. Platzner, M.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Paderborn, Paderborn, Germany (Boschmann, A.; Platzner, M.)
Abstract	Even small changes of electrode recording sites after training a classifier heavily influence robustness and usability of traditional pattern recognition-based myoelectric control schemes. This effect occurs during donning and doffing of the prosthesis or when changing the arm position and generally leads to a significant decrease of classification accuracy. On the other hand, image representations taken from high density electromyographic (EMG) signals offer high spatial resolution and only seem to change slightly during electrode shift, preserving most structural information. In this paper, we present a simple one-against-one nearest neighbor classifier based on the Structural Similarity Index (SSIM). SSIM quantifies visual similarity of two images based on decomposition into three components: luminance, contrast and structure. Our experimental results indicate that an SSIM-based classifier can outperform an LDA-based classifier using structural information taken from high density EMG signals during simulated electrode shift.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	4547
Ending Page	4550
File Size	981302
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944635
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrodes Electromyography Indexes Pattern recognition Training Accuracy Robustness
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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