Category: Technology
Objective: To determine the reliability and preliminary validity of passively acquired smartwatch-based sensor features of hand gestures in early Parkinson’s disease (PD).
Background: Hand movements of individuals with PD may harbor relevant signals to quantify motor symptom severity and track disease progression. Digital health technologies provide the means to unobtrusively measure motor behavior at high frequency and minimal burden. We compare sensor features derived from a smartwatch worn during daily life to relevant MDS-UPDRS items and sensor features from controlled smartphone-based active tests.
Method: Data from 316 individuals with early PD (<2y) participating in a phase II clinical trial (PASADENA, NCT03100149) were analyzed. Sensor feature data were extracted from smartphones during the performance of active motor tests and from smartwatches during daily passive monitoring (PM) of hand gestures when not walking and averaged around the two weeks around baseline. Partial spearman’s correlations assessed associations between PM sensor features and active test sensor features and MDS-UPDRS items, controlling for age and gender.
Results: Most patients (72%) wore the smartwatch on their non-dominant hand. PM hand gesture features correlated with active test sensor features requiring hand movements and corresponding MDS-UPDRS items: e.g., PM median absolute deviation in gesture power positively correlated with active test median speed of the non-dominant hand in the pronation-supination task (both ICC≥ .93, rs[258]=.45, p<.001) and negatively correlated with MDS-UPDRS III (rs[252]=-.31, p<.001). Gesture length (reduction in 25th percentile) negatively correlated with performance on an active drawing task (i.e. hitting all waypoints while drawing a square with non-dominant hand; ICC=.82, .57 respectively, rs[252]= -.36, p<.001) and with MDS-UPDRS Apathy (rs[251]=-.33, p<.001).
Conclusion: Gesture motor behavior in daily life can be quantified with smartwatches and correlate with corresponding MDS-UPDRS scores and app-based motor tasks designed to induce optimal motor performance. These findings support the construct validity of passively monitored gestures and further indicate that sensor features from app-based active tests are related to motor behaviors in daily life, supporting their ecological validity.
To cite this abstract in AMA style:
E. Volkova-Volkmar, A. Thomann, B. van Lier, D. Wolf, G. Pointeau, Y.P Zhang Schärer, W.Y Cheng, C. Simillion, G. Pagano, W. Zago, C. Gossens, F. Lipsmeier, K. Taylor, M. Lindemann. Association between actively and passively monitored hand gestures in early Parkinson’s disease [abstract]. Mov Disord. 2020; 35 (suppl 1). https://www.mdsabstracts.org/abstract/association-between-actively-and-passively-monitored-hand-gestures-in-early-parkinsons-disease/. Accessed June 15, 2025.« Back to MDS Virtual Congress 2020
MDS Abstracts - https://www.mdsabstracts.org/abstract/association-between-actively-and-passively-monitored-hand-gestures-in-early-parkinsons-disease/