NDLI: Development of a Micro-Macro Neural Network to recognize rollover movement

Content Provider	IEEE Xplore Digital Library
Author	Takeshi Ando, Jun Okamoto, Fujie, Masakatsu G.
Copyright Year	2008
Description	Author affiliation: Faculty of Science and Engineering, and the Consolidated Research Institute for Advanced Science and Medical Care, Waseda University, Tokyo, Japan (Fujie, Masakatsu G.) \|\| Graduate School of Science and Engineering, Waseda University, Tokyo 169-8555, Japan (Takeshi Ando,)
Abstract	Bone metastasis patients suffer from pain when their trunks twist during movements such as rollovers. In this overall research project, our ultimate aim is to develop an effective rollover-support system for patients with cancer bone metastasis. The core of this system will be a pneumatic rubber muscle that will be operated based on the EMG signals from the patient's internal abdominal oblique muscle to limit the range of motion of the trunk twist only when the patients will feel the pain. The Time Delay Neural Network (TDNN) is the traditional method for recognizing the movement such as rollover using EMG signals. We have developed a new neural network, called the Micro-Macro Neural Network (MMNN), to recognize the rollover movement earlier and with more accuracy than possible with the TDNN. Recognition using MMNN was 49 (S.D. 45) (msec) faster than that using TDNN. The recognition rate before the rollover started was improved from 38% (TDNN) to 86% (MMNN). Additionally, the number of false recognitions using MMNN fell to only one third of those using TDNN. In addition, by using the unit contribution rate of the neural network, we found that the MMNN effectively accounted for the importance of past EMG data (the data gathered before the current measurement point). We also found that the de-noising performance of the MMNN was effective.
Starting Page	5228
Ending Page	5233
File Size	568647
Page Count	6
File Format	PDF
ISBN	9781424418145
ISSN	1557170X
DOI	10.1109/IEMBS.2008.4650393
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-20
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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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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