Category: Parkinson’s Disease: Clinical Trials
Objective: This study aimed to identify gait metrics capable of capturing disease progression in individuals with early Parkinson’s disease (PD).
Background: Digital gait assessments have demonstrated greater sensitivity than clinical rating scales in cross-sectional studies. However, to serve as reliable early disease progression endpoints, these measures must also detect longitudinal changes over short periods (e.g., one year).
Method: Nineteen individuals diagnosed with PD (mean age: 53 ± 12 years, MDS-UPDRS Part III total score: 27 ± 7) participated in this study. Participants continuously wore instrumented socks embedded with Opal sensors on each foot, along with a waist-mounted sensor, for at least 8 hours per day over a week. In addition to monitoring daily activity, MDS-UPDRS assessments were conducted at baseline and repeated after one year. The standardized response mean (SRM) was used to compare effect sizes between baseline and follow-up for both clinical scores and digital gait/activity metrics.
Results: Multiple gait and activity metrics exhibited statistically significant changes over 12 months, with larger effect sizes than clinical scores. Notably, the median walking bout length decreased significantly over time, with a stronger effect size than the MDS-UPDRS Part III total score (SRM = -0.61 vs. 0.05). Additionally, gait variability measures, including stride length variability (SRM = 0.59) and foot pitch angle variability (SRM = 0.55), demonstrated medium effect sizes, whereas the MDS-UPDRS Part II total score showed a lower effect size (SRM = 0.19).
Conclusion: Wearable sensor-derived gait metrics effectively captured disease progression in early PD within a one-year period, whereas conventional MDS-UPDRS Part II & III scores did not. These findings highlight the potential of digital mobility biomarkers for use in future early intervention clinical trials.
To cite this abstract in AMA style:
V. Shah, C. Silva-Batista, D. Engel, A. Ragothaman, P. Burgos, P. Carlson-Kuhta, F. Horak, M. Mancini. Harnessing Digital Biomarkers to Monitor Early Parkinson’s Disease Progression [abstract]. Mov Disord. 2025; 40 (suppl 1). https://www.mdsabstracts.org/abstract/harnessing-digital-biomarkers-to-monitor-early-parkinsons-disease-progression/. Accessed October 5, 2025.« Back to 2025 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/harnessing-digital-biomarkers-to-monitor-early-parkinsons-disease-progression/