Research Article| Volume 345, ISSUE 1-2, P131-138, October 15, 2014

Automated gait and balance parameters diagnose and correlate with severity in Parkinson disease


      • We evaluated the APDM® Mobility Lab in Parkinson's disease.
      • We employed a statistical method to reduce the variables of interest.
      • We found a set of 20 variables that differentiate PD from controls.
      • Another set of 20 variables correlates with symptom severity.
      • This device may be useful for objectively tracking disease progression.



      To assess the suitability of instrumented gait and balance measures for diagnosis and estimation of disease severity in PD.


      Each subject performed iTUG (instrumented Timed-Up-and-Go) and iSway (instrumented Sway) using the APDM® Mobility Lab. MDS-UPDRS parts II and III, a postural instability and gait disorder (PIGD) score, the mobility subscale of the PDQ-39, and Hoehn & Yahr stage were measured in the PD cohort. Two sets of gait and balance variables were defined by high correlation with diagnosis or disease severity and were evaluated using multiple linear and logistic regressions, ROC analyses, and t-tests.


      135 PD subjects and 66 age-matched controls were evaluated in this prospective cohort study. We found that both iTUG and iSway variables differentiated PD subjects from controls (area under the ROC curve was 0.82 and 0.75 respectively) and correlated with all PD severity measures (R2 ranging from 0.18 to 0.61). Objective exam-based scores correlated more strongly with iTUG than iSway. The chosen set of iTUG variables was abnormal in very mild disease. Age and gender influenced gait and balance parameters and were therefore controlled in all analyses.


      Our study identified sets of iTUG and iSway variables which correlate with PD severity measures and differentiate PD subjects from controls. These gait and balance measures could potentially serve as markers of PD progression and are under evaluation for this purpose in the ongoing NIH Parkinson Disease Biomarker Program.


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