Differentiating essential tremor and Parkinson's disease using a wearable sensor — A pilot study

Abstract

Essential tremor is the most common form of tremors presenting an outpatient neurology practice and yet it may be often difficult to differentiate with tremors in Parkinson's disease — one of the commonest neurodegenerative disease. Since using appropriate medication is fundamental for efficacy and avoiding serious side effects, precise diagnoses are recommended. Single photon emission computerized tomography (SPECT) of the dopamine transporter (DAT) is a sensitive and specific imaging tool, but expensive and not advisable as screening means. Wearable devices are developing such effective and affordable supports for clinicians. This work aims to be a pilot study of future tremor classification. A low-cost miniaturized wearable device was exploited to collect movements of subject's hand during resting, postural and kinetic tasks. Data were analyzed to extract parameters describing tremors frequency distribution. Results confirm that PD and ET are well separated in the frequency domain, laying the basis for accurate classification.