Accelerometer data collected with a minimum set of wearable sensors from subjects with Parkinson’s disease

Author:

Daneault Jean-Francois,Vergara-Diaz Gloria,Parisi Federico,Admati Chen,Alfonso Christina,Bertoli Matilde,Bonizzoni Edoardo,Carvalho Gabriela Ferreira,Costante Gianluca,Fabara Eric Eduardo,Fixler Naama,Golabchi Fatemah Noushin,Growdon John,Sapienza Stefano,Snyder PhilORCID,Shpigelman Shahar,Sudarsky Lewis,Daeschler Margaret,Bataille Lauren,Sieberts Solveig K.ORCID,Omberg Larsson,Moore StevenORCID,Bonato PaoloORCID

Abstract

AbstractParkinson’s disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository.

Funder

The Michael J Fox Foundation for Parkinson's Research

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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