TY - JOUR
T1 - Digital gait biomarkers in Parkinson’s disease
T2 - susceptibility/risk, progression, response to exercise, and prognosis
AU - Mancini, Martina
AU - Afshari, Mitra
AU - Almeida, Quincy
AU - Amundsen-Huffmaster, Sommer
AU - Balfany, Katherine
AU - Camicioli, Richard
AU - Christiansen, Cory
AU - Dale, Marian L.
AU - Dibble, Leland E.
AU - Earhart, Gammon M.
AU - Ellis, Terry D.
AU - Griffith, Garett J.
AU - Hackney, Madeleine E.
AU - Hopkins, Jammie
AU - Horak, Fay B.
AU - Jones, Kelvin E.
AU - Ling, Leah
AU - O’Keefe, Joan A.
AU - Kwei, Kimberly
AU - Olivier, Genevieve
AU - Rao, Ashwini K.
AU - Sivaramakrishnan, Anjali
AU - Corcos, Daniel M.
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/105000519933
U2 - 10.1038/s41531-025-00897-1
DO - 10.1038/s41531-025-00897-1
M3 - Review article
C2 - 40118834
AN - SCOPUS:105000519933
SN - 2373-8057
VL - 11
JO - npj Parkinson's Disease
JF - npj Parkinson's Disease
IS - 1
M1 - 51
ER -