A Novel Non-Parametric Approach Of Tremor Detection Using Wrist-Based Photoplethysmograph

Abstract

Pervasive detection and quantification of tremor for Parkinson’s Disease (PD) patients, using Commercial Off-the-self (COTS) wrist-wearable device is an important problem to investigate. Parkinsonian tremor is one of the earliest and major surrogate biomarker which indicates the progress or status of the disease for patients under treatment using drugs or deep brain stimulation (DBS) therapy. However, it is a challenging issue as tremor occurs at the minor extremities like fingers in some cases such as pill-rolling symptom, the effect of the same on a wrist-worn motion sensor system is not significant enough to be captured. In this paper, we explore the possibility of using the wrist-based photoplethysmography (PPG) as a novel sensor modality in detecting tremor at rest. Our preliminary results gathered from healthy cohorts performing simulations of Parkinsonian tremor elucidates the merit of the proposed method. Also, since PPG acquisition is power-hungry, we have leveraged a conceptual method of compressive sensing to reduce the overall power requirement of the application.