Digital biomarkers of mobility and quality of life in Parkinson's disease based on a wearable motion analysis LAB

Abstract

Background and objective: Functional mobility, an indicator of the quality of life (QoL), requires fast and flexible changes during motion, which are limited in Parkinson's disease (PD). Recent body-worn sensors have emerged in the last decades as potential solutions to produce digital biomarkers able to quantify mobility outside routine consultations and during real-life scenarios for multiple days at a time. The proposed research aims to study the ability of a wearable motion analysis lab, developed by our team, to produce digital biomarkers of mobility and QoL levels in patients with PD.

Methods: A cross-sectional study was followed, including 40 patients stratified into three subgroups according to a clinic motor examination and a QoL questionnaire.

Results: The achieved outcomes demonstrate the ability of the proposed high-tech solution to measure prototypical gait impairments and discriminate motor condition (AUC=0,890) and patients' QoL levels (AUC=0,950). Also, from the measured multiple gait-associated parameters, we identified the variables with the most potential to be applied as digital biomarkers of mobility (67 % of the metrics) and QoL (72 % of the metrics) in PD.

Conclusions: Overall, we confirmed our hypothesis of using our body-worn sensor-based solution for passive or active monitoring of mobility and QoL in PD to produce objective, feasible, and continuous digital biomarkers.

Keywords: Body-worn sensors; Digital biomarkers; Functional mobility; Machine learning; Parkinson's disease; Quality of life.