Monitoring Parkinson's disease patients employing biometric sensors and rule-based data processing

Authors:
Paweł Żwan;Katarzyna Kaszuba;Bożena Kostek
Affiliations:
Gdansk University of Technology, Gdansk, Poland;Gdansk University of Technology, Gdansk, Poland;Gdansk University of Technology, Gdansk, Poland
Venue:
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Year:
2010

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Abstract

The paper presents how rule-based processing can be applied to automatically evaluate the motor state of Parkinson's Disease patients. Automatic monitoring of patients by using biometric sensors can provide assessment of the Parkinson's Disease symptoms. All data on PD patients' state are compared to historical data stored in the database and then a rule-based decision is applied to assess the overall illness state. The training procedure based on doctors' questionnaires is presented. These data constitute the input of several rule-based classifiers. It has been proved that the rough-set-based algorithm can be very suitable for automatic assessment of the PD patient's stability/worsening state.