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Physical examination, interviews with patients and the results of rating scales for movement disturbances are the basis for the assessment of Parkinson's disease (PD). However, subjectivity in the assessment of the symptoms and the short period of observation are disadvantageous. This paper presents the results of a study to assess the feasibility of using accelerometer data, acquired from smart clothes, to estimate the severity of tremor in patients with PD. Algorithms were implemented to estimate the severity of rest and postural tremor of hands from accelerometer data features. The system developed consists of a pullover with eight integrated accelerometers and a computer. The newly developed system for the detection and assessment of tremor was tested with PD patients. System-based estimates were compared with clinical scores derived via visual inspection of video recordings taken while patients performed a series of standardized motor tasks. A quantifiable objective data acquisition by means of a portable wireless system could evaluate the motor disorders better.

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