NDLI: Motion recognition for unsupervised hand rehabilitation using support vector machine

Content Provider	IEEE Xplore Digital Library
Author	Liquan Guo Jiping Wang Qiang Fang Xudong Gu Jianming Fu
Copyright Year	2012
Description	Author affiliation: Rehabilitation Med. Center, Second Hosp. of Jiaxing, Jiaxing, China (Xudong Gu; Jianming Fu) \|\| Suzhou Inst. of Biomed. Eng. & Technol., Suzhou, China (Liquan Guo; Jiping Wang; Qiang Fang)
Abstract	In recent years, with the rapid increase in stroke patients and the associated cost, efficient stroke rehabilitation especially unsupervised and remote stroke rehabilitation have become hot research topics. It has been proved that unsupervised stroke rehabilitation was effective and necessary for stroke patients. However, an accurate and robust classification system for hand motion recognition is essential for such an unsupervised system. In this paper, we present a support-vector-machine-based finger and wrist movement recognition system designed to identify typical hand training movements such as finger docking, cylinder grabbing and sphere grabbing. Three stroke patients were involved in this clinical research. For each training movement, 35 different movements from those three patients were recorded respectively to verify and validate this system. The data were separated into two groups; one training and one testing group. After preprocessing and feature extraction of the acquired motion data, the support vector machine recognition approach was employed to establish a small sample identification model. Finally, the data of testing group were used to verify the developed model. It was found that the recognition accuracy of the developed model was 96.67. This research paves the way for development of an automated system for stroke patient rehabilitation.
Sponsorship	Circuits & Syst. Soc.
Starting Page	104
Ending Page	107
File Size	386957
Page Count	4
File Format	PDF
ISBN	9781467322911
e-ISBN	9781467322935
e-ISBN	9781467322928
DOI	10.1109/BioCAS.2012.6418485
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-28
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Wrist Support vector machines Tracking Thumb Sensors
Content Type	Text
Resource Type	Article

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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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