Development and validation of gait digital outcomes as clinical endpoints in Parkinson's Disease

Abstract

A promising solution to the limited, clinical assessment of Parkinson’s (PD), has emerged through quantification of real-world walking speed (RWS) from wearable devices. RWS can be remotely assessed across consecutive days, measuring change in aspects of quality of life that are of importance to patients which can complement the existing clinical assessment of PD. The aims of this thesis were to address several gaps in the literature and explore, validate, and characterise RWS as a digital mobility outcome (DMO), to understand what complementary information it can provide to enhance the existing clinical assessment of mobility in PD. PD and older adults (OA) participants were recruited from two separate studies: the Incidence of Cognitive Impairment with Longitudinal Evaluation – GAIT (ICICLE-GAIT) and the Mobilise-D Technical Validation Study (TVS). Participants underwent mobility assessments in supervised and real-world environments over seven days, wearing a single lower-back wearable device. Algorithms were applied to estimate various macro and micro-level DMOs, including RWS within short, medium, and long walking bouts (WBs). In comparison to OAs, RWS was significantly slower in PD cross-sectionally and declined more rapidly longitudinally. At medium WBs, RWS was significantly related with MDS-UPDRS III score. In contrast to PD, OAs appeared to modulate their RWS differently between indoor and outdoor locations. Walking modulation was further characterised as three selected walking speeds, modelled as the number of modes within the distribution. Within short WBs, a larger number of selected walking speeds were associated with larger medication dosage and FOG score. This thesis provides evidence that digital assessment of RWS can provide novel complementary information about changes in gait that relate to real-world mobility and are of importance to patients. Inclusion of contextual data and novel statistical techniques can improve understanding of the impact of PD upon safe modulation of walking between different real-world scenarios and within a single bout of walking.