Fan, X., Sun, W., Ren, A. , Fan, D., Zhao, N., Haider, D., Yang, X. and Abbasi, Q. H. (2018) Detection and diagnosis of paralysis agitans. IEEE Access, 6, pp. 73023-73029. (doi: 10.1109/ACCESS.2018.2882134)
|
Text
173525.pdf - Published Version 6MB |
Abstract
Humans’ daily behavior can reflect the main physiological characteristics of neurological diseases. Human gait is a complex behavior produced by the coordination of multiple physiological systems such as the nervous system and the muscular system. It can reflect the physiological state of human health, and its abnormality is an important basis for diagnosing some nervous system diseases. However, many early gait anomalies have not been effectively discovered because of medical costs and people's living customs. This paper proposes an effective, economical, and accurate non-contact cognitive diagnosis system to help early detection and diagnosis of paralysis agitans under daily life conditions. The proposed system extract data from wireless state information obtained from antenna-based data gathering module. Further, we implement data processing and gait classification systems to detect abnormal gait based on the acquired wireless data. In the experiment, the proposed system can detect the state of human gait and carries high classification accuracy up to 96.7 %. The experimental results demonstrate that the proposed technique is feasible and cost-effective for healthcare applications.
| Item Type: | Articles |
|---|---|
| Additional Information: | The work was supported in part by the Fundamental Research Funds for the Central Universities (No. JB180205), International Scientific and Technological Cooperation and Exchange Projects in Shaanxi Province (No. 2017KW-005), and China Postdoctoral Science Foundation Funded Project (No. 2018T111023). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Abbasi, Professor Qammer and Ren, Dr Aifeng |
| Authors: | Fan, X., Sun, W., Ren, A., Fan, D., Zhao, N., Haider, D., Yang, X., and Abbasi, Q. H. |
| College/School: | College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
| Journal Name: | IEEE Access |
| Publisher: | IEEE |
| ISSN: | 2169-3536 |
| ISSN (Online): | 2169-3536 |
| Published Online: | 19 November 2018 |
| Copyright Holders: | Copyright © 2018 IEEE |
| First Published: | First published in IEEE Access 6: 73023-73029 |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
University Staff: Request a correction | Enlighten Editors: Update this record
Deposit and Record Details
Deposit and Record Details