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Parkinson's disease is classified as a chronic movement disorder. The incidence of Parkinson's disease is proportional to age. The status of Parkinson's disease is characterized through the Unified Parkinson's Disease Rating Scale. The Unified Parkinson's Disease Rating Scale is an ordinal scale, for which the scale is qualitatively evaluated. The inherent issue of the ordinal scale is the lack of a temporal parameter to evaluate the attributes of the movement disorder. The evaluation of the Parkinson's Disease Rating Scale requires clinical specialization, occurring in a clinical environment. Accelerometers, through the advent of miniaturization, have reached a capacity to advance the evaluation of Parkinson's disease. Tremor characteristics and temporal attributes of Parkinson's disease can be readily quantified. Accelerometer systems have been tested and evaluated for ascertaining general status, drug therapy efficacy, and amelioration of Parkinson's disease based on deep brain stimulation parameter settings. Further advance of the accelerometer characterization of Parkinson's disease attributes involves the incorporation of a fully wearable system. Such a system is possible with the integration of wireless 3D MEMS accelerometers. The device proposed incorporates a wireless and potentially wearable 3D MEMS accelerometer mounted on the dorsum of the hand. The wireless 3D MEMS accelerometer system can potentially track the Parkinson's disease status through out real time for a subject at the home-based setting of the subject. An implication of the device is a subject database can be generated quantifying the progression of Parkinson's disease. Drug therapy dosage may be optimized with quantified feedback from the wireless 3D MEMS accelerometer system. Deep brain stimulation parameters may be further refined, and the conceptual foundation for real time deep brain stimulation parameter optimization is established. Enclosed is the initial test and evaluati- - on of the wireless 3D MEMS accelerometer system through the quantification of simulated tremor.
Date of Conference: 9-11 April 2009