Objective: To determine the the reliability and preliminary validity of passively acquired sensor features of gait in individuals with early Parkinson’s disease (PD).

Background: Passive and remote digital monitoring of gait with smartphones and -watches may provide high-frequency and objective quantification of PD impacts on daily gait at relatively low burden. Since these data are not acquired in controlled experimental settings, the utility of passively monitored gait features remains to be determined. Hence, we compare passively monitored (PM) sensor gait features to those acquired from smartphones and -watches while patients performed controlled “active tests”, e.g. a U-turn test, as well as relevant MDS-UPDRS items.

Method: Data from 316 individuals with early PD (<2y) participating in a phase II clinical trial (PASADENA, NCT03100149) were analyzed. Sensor feature data from two weeks around baseline were extracted from smartphones and -watches during the performance of active motor tests and from daily PM. Partial Spearman’s rank order correlations assessed associations between averaged passive and active sensor features and with gait-related MDS-UPDRS items, controlling for age and gender.

Results: PM sensor features of gait correlated with corresponding sensor active test features and MDS-UPDRS items, e.g. average PM turn speed positively correlated with active test median U-turn turn speed (ICC=.72, .95 respectively, rs[266]=.52, p<.001) and negatively correlated with MDS-UPDRS Body Bradykinesia (rs[256]=-.27, p<.001). Further, the number of sharp turns per walking minute positively correlated with an active test U-turn sensor feature (gait power variance; ICC=.8, .9 respectively, rs[266]=.41, p<.001) and negatively correlated with MDS-UPDRS Postural Stability (rs[254]=-.36, p<.001).

Conclusion: Active tests are designed to induce optimal motor performance, while passive monitoring captures typical motor behavior in daily life. The correlations observed between related active and passive measures and the with corresponding MDS-UPDRS items support the construct validity and utility of passively monitored gait features. The present results indicate that active test sensor features indeed reflect motor behavior in daily life, supporting the ecological validity of remotely administered active tests on smartphones.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/association-between-actively-and-passively-monitored-gait-in-early-parkinsons-disease/