DocumentCode :
637718
Title :
REMPARK: When AI and technology meet Parkinson Disease assessment
Author :
Cabestany, J. ; Perez Lopez, Carlos ; Sama, A. ; Moreno, Juan Manuel ; Bayes, Angels ; Rodriguez-Molinero, A.
Author_Institution :
CETpD-Tech. Centre for Dependency Care & Autonomous Living, Univ. Politec. de Catalunya-UPC, Vilanova i la Geltru, Spain
fYear :
2013
fDate :
20-22 June 2013
Firstpage :
562
Lastpage :
567
Abstract :
REMPARK project objective is to develop a personal health system with closed loop detection, response and action capabilities for the assessment and possible management of Parkinson´s Disease (PD) patients. The project is developing a wearable monitoring system able to identify in real time the motor status of the PD patients and evaluating ON/OFF/Dyskinesia status with a very high sensitivity and specificity degree (>80%) in operation during ambulatory conditions. Identification of the motor status is based on the knowledge included in a large database obtained with the collaboration of a number of volunteer PD patients, according a specific defined protocol in ambulatory conditions. Artificial Intelligence (AI) methods are applied to the database information for the automatic detection of motor symptoms.
Keywords :
artificial intelligence; closed loop systems; patient diagnosis; wearable computers; ON/OFF/Dyskinesia status; Parkinson Disease assessment; REMPARK; artificial intelligence methods; automatic detection; closed loop detection; database information; motor symptoms; personal health system; wearable monitoring system; Artificial intelligence; Databases; Diseases; Fluctuations; Monitoring; Real-time systems; Sensors; ON and OFF states automatic detection; Parkinson disease; management and assessment of the disease; personal health device;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mixed Design of Integrated Circuits and Systems (MIXDES), 2013 Proceedings of the 20th International Conference
Conference_Location :
Gdynia
Print_ISBN :
978-83-63578-00-8
Type :
conf
Filename :
6613416
Link To Document :
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