NDLI: Extraction of voluntary movement for an EMG controlled exoskeltal robot of tremor patients

Content Provider	IEEE Xplore Digital Library
Author	Ando, T. Watanabe, M. Fujie, M.G.
Copyright Year	2009
Description	Author affiliation: Faculty of Science and Engineering, Waseda University, Tokyo, Japan (Ando, T.; Watanabe, M.; Fujie, M.G.)
Abstract	Tremor is the most common of all involuntary movement. A lot of tremor patients in upper limb have serious difficulties performing daily living activities. We have developed the exoskeleton robot for tremor patient. In this paper, we focused on to develop a signal processing method to extract the voluntary movement from the electromyogram (EMG) signal in which the voluntary movement and tremor were mixed. We have researched about following two methods to recognize the voluntary movement: one is Low pass filter and neural network (NN), the other is Short Time Fourier Transform and NN. The low pass filter and neural network (NN) were effective for recognition of healthy subject's movement. However, these methods were not applied to the tremor patient's movement due to the characteristic oscillation of the EMG signal in the tremor patient. The proposed algorithm, which was composed of the Short Time Fourier Transform and NN, dramatically improved the recognition rate of tremor patient's movement. It was confirmed that the signal processing using STFT and NN is suitable for the recognition of the tremor patients In future, we will develop more accurate algorithm based on this study, and finally conduct the clinical test to show effectiveness of our system.
Starting Page	120
Ending Page	123
File Size	650836
Page Count	4
File Format	PDF
ISBN	9781424420728
DOI	10.1109/NER.2009.5109249
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-29
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fourier transforms Low pass filters Tremor Robot control Exoskeletons STFT Biological neural networks Neural networks Signal processing algorithms Signal processing EMG signal Robot sensing systems Electromyography Exoskeltal robot
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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