Markerless Motion Capture to Quantify Functional Performance in Neurodegeneration: Systematic Review (Preprint)

Abstract

BACKGROUND Markerless motion capture (MMC) uses video cameras and/or depth sensors for full body tracking and presents a promising approach for objectively and unobtrusively monitoring functional performance within community settings, to aid clinical decision-making in neurodegenerative diseases such as dementia. OBJECTIVE The primary objective of our systematic review was to investigate the application of MMC using full-body tracking to quantify functional performance in people with dementia, mild cognitive impairment (MCI) and Parkinson’s disease (PD) METHODS We systematically searched for relevant articles which yielded a total of 1595 results. Inclusion criteria were MMC and full-body tracking. A total of 157 studies were included for full article screening out of which 26 eligible studies that met the selection criteria were included in the review. RESULTS Primarily, the selected studies focused on gait analysis, while other functional tasks, such as sit-to-stand and stepping in place, were also explored. However, activities of daily living were not evaluated in any of the studies. MMC models varied across the studies encompassing depth cameras vs standard video cameras or mobile phone cameras with postprocessing using deep-learning model. However, only a few studies conducted rigorous comparisons with established ground-truths. CONCLUSIONS Despite its potential as an effective tool for analysing movement and posture in individuals with dementia, MCI, and PD, further research is required to establish the clinical usefulness of MMC in quantifying mobility and functional performance in the real-world.