Quantitative mobility measures complement the MDS-UPDRS for characterization of Parkinson's disease heterogeneity

Parkinsonism Relat Disord. 2021 Mar:84:105-111. doi: 10.1016/j.parkreldis.2021.02.006. Epub 2021 Feb 10.


Introduction: Emerging technologies show promise for enhanced characterization of Parkinson's Disease (PD) motor manifestations. We evaluated quantitative mobility measures from a wearable device compared to the conventional motor assessment, the Movement Disorders Society-Unified PD Rating Scale part III (motor MDS-UPDRS).

Methods: We evaluated 176 PD subjects (mean age 65, 65% male, 66% H&Y stage 2) during routine clinic visits using the motor MDS-UPDRS and a 10-min motor protocol with a body-fixed sensor (DynaPort MT, McRoberts BV), including the 32-ft walk, Timed Up and Go (TUG), and standing posture with eyes closed. Regression models examined 12 quantitative mobility measures for associations with (i) motor MDS-UPDRS, (ii) motor subtype (tremor dominant vs. postural instability/gait difficulty), (iii) Montreal Cognitive Assessment (MoCA), and (iv) physical functioning disability (PROMIS-29). All analyses included age, gender, and disease duration as covariates. Models iii-iv were secondarily adjusted for motor MDS-UPDRS.

Results: Quantitative mobility measures from gait, TUG transitions, turning, and posture were significantly associated with motor MDS-UPDRS (7 of 12 measures, p < 0.05) and motor subtype (6 of 12 measures, p < 0.05). Compared with motor MDS-UPDRS, several quantitative mobility measures accounted for a 1.5- or 1.9-fold increased variance in either cognition or physical functioning disability, respectively. Among minimally-impaired subjects in the bottom quartile of motor MDS-UPDRS, including subjects with normal gait exam, the measures captured substantial residual motor heterogeneity.

Conclusion: Clinic-based quantitative mobility assessments using a wearable sensor captured features of motor performance beyond those obtained with the motor MDS-UPDRS and may offer enhanced characterization of disease heterogeneity.

Keywords: Device; Parkinson's disease; Wearable sensors; Wearables.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Diagnostic Techniques, Neurological* / instrumentation
  • Female
  • Gait Disorders, Neurologic / diagnosis*
  • Gait Disorders, Neurologic / etiology
  • Humans
  • Male
  • Middle Aged
  • Parkinson Disease / complications
  • Parkinson Disease / diagnosis*
  • Postural Balance* / physiology
  • Severity of Illness Index
  • Tremor / diagnosis*
  • Tremor / etiology
  • Wearable Electronic Devices*