Quantifying Parkinson's disease severity using mobile wearable devices and machine learning: the ParkApp pilot study protocol.

ABSTRACT:

Introduction

The clinical assessment of Parkinson's disease (PD) symptoms can present reliability issues and, with visits typically spaced apart 6 months, can hardly capture their frequent variability. Smartphones and smartwatches along with signal processing and machine learning can facilitate frequent, remote, reliable and objective assessments of PD from patients' homes.

Aim

To investigate the feasibility, compliance and user experience of passively and actively measuring symptoms from home environments using data from sensors embedded in smartphones and a wrist-wearable device.

Methods and analysis

In an ongoing clinical feasibility study, participants with a confirmed PD diagnosis are being recruited. Participants perform activity tests, including Timed Up and Go

SUBMITTER: Ymeri G 

PROVIDER: S-EPMC10759062 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature