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Content Provider | IEEE Xplore Digital Library |
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Author | Gubbi, J. Kumar, D. Rao, A.S. Yan, B. Palaniswami, M. |
Copyright Year | 2013 |
Description | Author affiliation: Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Parkville, VIC, Australia (Gubbi, J.; Kumar, D.; Rao, A.S.; Palaniswami, M.) || Dept. of Med., Univ. of Melbourne, Parkville, VIC, Australia (Yan, B.) |
Abstract | The high incidence of stroke has raised a major concern among health professionals in recent years. Concerted efforts from medical and engineering communities are being exercised to tackle the problem at its early stage. In this direction, a pilot study to analyze and detect the affected arm of the stroke patient based on hand movements is presented. The premise is that the correlation of magnitude of the activities of the two arms vary significantly for stroke patients from controls. Further, the cross-correlation of right and left arms for three axes are differentiable for patients and controls. A total of 22 subjects (15 patients and 7 controls) were included in this study. An overall accuracy of 95.45% was obtained with sensitivity of 1 and specificity of 0.86 using correlation based method. |
Starting Page | 957 |
Ending Page | 960 |
File Size | 388531 |
Page Count | 4 |
File Format | |
ISBN | 9781457702167 |
ISSN | 1557170X |
DOI | 10.1109/EMBC.2013.6609661 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2013-07-03 |
Publisher Place | Japan |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Monitoring Sensors Accelerometers Correlation Accuracy Wireless communication Wireless sensor networks |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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