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Detecting freezing of gait with a tri-axial accelerometer in Parkinson’s disease patients

Author
Ahlrichs, C.; Sama, A.; Lawo, M.; Cabestany, J.; Rodriguez-Martin, D.; Perez, C.; Quinlan, L.; ÓLaighin, G.; Counihan, T.; Lewy, H.; Annicchiarico, R.; Bayés, À.; Rodríguez, A.
Type of activity
Journal article
Journal
Medical and biological engineering and computing
Date of publication
2015-10-01
First page
1
Last page
11
DOI
https://doi.org/10.1007/s11517-015-1395-3 Open in new window
Repository
http://hdl.handle.net/2117/86472 Open in new window
URL
http://link.springer.com/article/10.1007/s11517-015-1395-3 Open in new window
Abstract
Freezing of gait (FOG) is a common motor symptom of Parkinson’s disease (PD), which presents itself as an inability to initiate or continue gait. This paper presents a method to monitor FOG episodes based only on acceleration measurements obtained from a waist-worn device. Three approximations of this method are tested. Initially, FOG is directly detected by a support vector machine (SVM). Then, classifier’s outputs are aggregated over time to determine a confidence value, which is used for ...
Citation
Ahlrichs, C., Sama, A., Lawo, M., Cabestany, J., Rodriguez-Martin, D., Perez, C., Quinlan, L., ÓLaighin, G., Counihan, T., Lewy, H., Annicchiarico, R., Bayés, À., Rodríguez, A. Detecting freezing of gait with a tri-axial accelerometer in Parkinson’s disease patients. "Medical and biological engineering and computing", 01 Octubre 2015, p. 1-11.
Keywords
Parkinson’s disease Freezing of Gait Machine learning Support vector machines
Group of research
CETpD - Technical Research Centre for Dependency Care and Autonomous Living
ISSET - Integrated Smart Sensors and Health Technologies

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