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

Emily J. Hill, C. Grant Mangleburg, Isabel Alfradique-Dunham, Brittany Ripperger, Amanda Stillwell, Hiba Saade, Sindhu Rao, Oluwafunmiso Fagbongbe, Rainer von Coelln, Arjun Tarakad, Christine Hunter, Robert J. Dawe, Joseph Jankovic, Lisa M. Shulman, Aron S. Buchman, Joshua M. Shulman

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish
Pages (from-to)105-111
Number of pages7
JournalParkinsonism and Related Disorders
StatePublished - Mar 2021


  • Device
  • Parkinson's disease
  • Wearable sensors
  • Wearables


Dive into the research topics of 'Quantitative mobility measures complement the MDS-UPDRS for characterization of Parkinson's disease heterogeneity'. Together they form a unique fingerprint.

Cite this