NDLI: Vision-based Segmentation of Continuous Mechanomyographic Grasping Sequences for Training Multifunction Prostheses

Content Provider	IEEE Xplore Digital Library
Author	Alves, N. Chau, T.
Copyright Year	2006
Description	Author affiliation: Toronto Univ., Ont. (Alves, N.; Chau, T.)
Abstract	In designing mechanomyographic (MMG) signal classifiers for prosthetic control, the acquisition of long, continuous streams of MMG signals is typically preferred over the painstaking collection of individual, isolated contractions. However, a major challenge with continuous collection is the subsequent separation of the MMG data stream into segments representing individual contractions. This paper proposes an automatic, vision-based segmentation method for continuously recorded MMG data streams. MMG data acquisition was synchronized with transverse plane video acquisition of functional grip sequences. The automatic segmentation system can track a hand, recognize grips and detect grip transition times as well as extraneous hand movements. The system recognizes two grips with an average accuracy of 97.8plusmn4%, and seven grips with an accuracy of 73plusmn20%. The contraction initiation and termination times agree closely (within 1.3plusmn1 frames) with values obtained manually
Sponsorship	IEEE EMB
Starting Page	3624
Ending Page	3627
File Size	215267
Page Count	4
File Format	PDF
ISBN	1424400325
ISSN	1557170X
DOI	10.1109/IEMBS.2006.260368
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Prosthetics Muscles Streaming media Data acquisition Image segmentation Fatigue Signal detection Data mining Frequency synchronization Testing
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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Vision-Based Segmentation of Continuous Mechanomyographic Grasping Sequences

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