Abstract
This paper presents the use of an accelerometry-based wearable motion detector for real-time recognizing gait cycle parameters of Parkinson's disease (PD) patients. The wearable motion detector uses a tri-axial accelerometer to measure trunk accelerations during walking. By using the autocorrelation procedure, several gait cycle parameters including cadence, gait regularity, and symmetry can be derived in real-time from the measured trunk acceleration data. The gait cycle parameters derived from 5 elder PD patients and 5 young healthy subjects are also compared. The measures of the gait cycle parameters between the PD patients and the healthy subjects are distinct and therefore can be quantified and distinguished, which indicates that detection of abnormal gaits of PD patients in real-time is also possible. The wearable motion detector developed in this paper is a practical system that enables quantitative and objective mobility assessment. The possible applications of this system are also discussed.
Original language | English |
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Title of host publication | Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011 |
Pages | 498-502 |
Number of pages | 5 |
DOIs | |
Publication status | Published - Aug 24 2011 |
Externally published | Yes |
Event | 2011 International Conference on System Science and Engineering, ICSSE 2011 - Macao, China Duration: Jun 8 2011 → Jun 10 2011 |
Conference
Conference | 2011 International Conference on System Science and Engineering, ICSSE 2011 |
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Country | China |
City | Macao |
Period | 6/8/11 → 6/10/11 |
Keywords
- accelerometer
- accelerometry
- gait
- mobility
- Parkinson's disease
ASJC Scopus subject areas
- Control and Systems Engineering