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Estimating bradykinesia severity in Parkinson's disease by analysing gait through a waist-worn sensor

Author
Sama, A.; Perez, C.; Rodriguez-Martin, D.; Catala, A.; Moreno, J.; Cabestany, J.; De Mingo, E.; Rodríguez, A.
Type of activity
Journal article
Journal
Computers in biology and medicine
Date of publication
2017-05-01
Volume
84
First page
114
Last page
123
DOI
https://doi.org/10.1016/j.compbiomed.2017.03.020 Open in new window
Repository
http://hdl.handle.net/2117/103824 Open in new window
https://www.ncbi.nlm.nih.gov/pubmed/28351715 Open in new window
URL
http://www.computersinbiologyandmedicine.com/article/S0010-4825(17)30075-6/fulltext Open in new window
Abstract
Bradykinesia is a cardinal symptom of Parkinson's disease (PD) and describes the slowness of movement revealed in patients. Current PD therapies are based on dopamine replacement, and given that bradykinesia is the symptom that best correlates with the dopaminergic deficiency, the knowledge of its fluctuations may be useful in the diagnosis, treatment and better understanding of the disease progression. This paper evaluates a machine learning method that analyses the signals provided by a triaxi...
Citation
Sama, A., Perez, C., Rodriguez-Martin, D., Catala, A., Moreno, J., Cabestany, J., De Mingo, E., Rodríguez, A. Estimating bradykinesia severity in Parkinson's disease by analysing gait through a waist-worn sensor. "Computers in biology and medicine", 1 Maig 2017, vol. 84, p. 114-123.
Keywords
Bradykinesia, Inertial sensors, Parkinson's disease, Support Vector Machines
Group of research
CETpD - Technical Research Centre for Dependency Care and Autonomous Living
ISSET - Integrated Smart Sensors and Health Technologies

Participants