Real-time quantification of resting tremor in the Parkinson's disease

Resting tremor (RT) is one of the most frequent signs of the Parkinson's disease (PD), occurring with various severities in about 75% of the patients. Current diagnosis is based on subjective clinical assessment, which is not always easy to capture subtle, mild and intermittent tremors. The aim of the present study is to assess the suitability and clinical value of a computer based real-time system as an aid to diagnosis of PD, in particular the presence of RT. Five healthy subjects were asked to simulate several severities of RT in hands and feet in three static activities. The behaviour of the subjects is measured using tri-axial accelerometers, which are placed at four different positions on the body. Frequency-domain features, strongly correlated with the RT activity, are extracted from the accelerometer data. The classification of RT severity based on those features, provided accuracy 76%. The real-time system designed for efficient extraction of those features and the provision of a continuous RT severity measure is described.