Real-time gait cycle parameters recognition using a wearable motion detector

Che Chang Yang, Yeh Liang Hsu, Jun Ming Lu, Kao Shang Shih, Lung Chan

研究成果: 書貢獻/報告類型會議貢獻

8 引文 (Scopus)

摘要

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.
原文英語
主出版物標題Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011
頁面498-502
頁數5
DOIs
出版狀態已發佈 - 八月 24 2011
對外發佈Yes
事件2011 International Conference on System Science and Engineering, ICSSE 2011 - Macao, 中国
持續時間: 六月 8 2011六月 10 2011

會議

會議2011 International Conference on System Science and Engineering, ICSSE 2011
國家中国
城市Macao
期間6/8/116/10/11

指紋

Detectors
Accelerometers
Autocorrelation

ASJC Scopus subject areas

  • Control and Systems Engineering

引用此文

Yang, C. C., Hsu, Y. L., Lu, J. M., Shih, K. S., & Chan, L. (2011). Real-time gait cycle parameters recognition using a wearable motion detector. 於 Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011 (頁 498-502). [5961954] https://doi.org/10.1109/ICSSE.2011.5961954

Real-time gait cycle parameters recognition using a wearable motion detector. / Yang, Che Chang; Hsu, Yeh Liang; Lu, Jun Ming; Shih, Kao Shang; Chan, Lung.

Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011. 2011. p. 498-502 5961954.

研究成果: 書貢獻/報告類型會議貢獻

Yang, CC, Hsu, YL, Lu, JM, Shih, KS & Chan, L 2011, Real-time gait cycle parameters recognition using a wearable motion detector. 於 Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011., 5961954, 頁 498-502, 2011 International Conference on System Science and Engineering, ICSSE 2011, Macao, 中国, 6/8/11. https://doi.org/10.1109/ICSSE.2011.5961954
Yang CC, Hsu YL, Lu JM, Shih KS, Chan L. Real-time gait cycle parameters recognition using a wearable motion detector. 於 Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011. 2011. p. 498-502. 5961954 https://doi.org/10.1109/ICSSE.2011.5961954
Yang, Che Chang ; Hsu, Yeh Liang ; Lu, Jun Ming ; Shih, Kao Shang ; Chan, Lung. / Real-time gait cycle parameters recognition using a wearable motion detector. Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011. 2011. 頁 498-502
@inproceedings{ed2cc1027479406f945b97de92bdfd94,
title = "Real-time gait cycle parameters recognition using a wearable motion detector",
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.",
keywords = "accelerometer, accelerometry, gait, mobility, Parkinson's disease",
author = "Yang, {Che Chang} and Hsu, {Yeh Liang} and Lu, {Jun Ming} and Shih, {Kao Shang} and Lung Chan",
year = "2011",
month = "8",
day = "24",
doi = "10.1109/ICSSE.2011.5961954",
language = "English",
isbn = "9781612844718",
pages = "498--502",
booktitle = "Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011",

}

TY - GEN

T1 - Real-time gait cycle parameters recognition using a wearable motion detector

AU - Yang, Che Chang

AU - Hsu, Yeh Liang

AU - Lu, Jun Ming

AU - Shih, Kao Shang

AU - Chan, Lung

PY - 2011/8/24

Y1 - 2011/8/24

N2 - 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.

AB - 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.

KW - accelerometer

KW - accelerometry

KW - gait

KW - mobility

KW - Parkinson's disease

UR - http://www.scopus.com/inward/record.url?scp=84860421421&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84860421421&partnerID=8YFLogxK

U2 - 10.1109/ICSSE.2011.5961954

DO - 10.1109/ICSSE.2011.5961954

M3 - Conference contribution

SN - 9781612844718

SP - 498

EP - 502

BT - Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011

ER -