Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis
Martina Mancini, Mitra Afshari, Quincy J. Almeida, Sommer L. Amundsen Huffmaster, Katherine Balfany, Richard Camicioli, Cory L. Christiansen, Marian L. Dale, Leland E. Dibble, Gammon M. Earhart, Terry D. Ellis, Garett Griffith, Madeleine E. Hackney, Jammie Hopkins, Fay B. Horak, Kelvin E. Jones, Ling Li, Joan A. O’Keefe, Kimberly Kwei, Geneviève N. Olivier, Ashwini K. Rao, Anjali Sivaramakrishnan, Daniel M. Corcos
Abstract
This narrative review examines the utility of gait digital biomarkers in Parkinson's disease (PD) research and clinical trials across four contexts: disease susceptibility/risk, disease progression, response to exercise, and fall prediction. The review of the literature to date suggests that upper body characteristics of gait (e.g., arm swing, trunk motion) may indicate susceptibility/risk of PD, while pace aspects (e.g., gait speed, stride length) are informative for tracking disease progression, exercise response, and fall likelihood. Dynamic stability aspects (e.g., trunk regularity, double-support time) worsen with disease progression but can improve with exercise. Gait variability emerges as a sensitive biomarker across all 4 contexts but with low specificity. The lack of standardized gait testing protocols and the lack of a minimum set of quantified digital gait biomarkers limit data harmonization across studies. Future studies, using a commonly agreed upon protocol, could be used to demonstrate the utility of specific gait biomarkers for clinical practice.