Test and Validation of a Smart Exercise Bike for Motor Rehabilitation in Individuals With Parkinson's Disease

Abstract

To assess and validate the Smart Exercise Bike designed for Parkinson's Disease (PD) rehabilitation, 47 individuals with PD were randomly assigned to either the static or dynamic cycling group, and completed three sessions of exercise. Heart rate, cadence and power data were captured and recorded for each patient during exercise. Motor function for each subject was assessed with the UPDRS Motor III test before and after the three exercise sessions to evaluate the effect of exercise on functional abilities. Individuals who completed three sessions of dynamic cycling showed an average of 13.8% improvement in the UPDRS, while individuals in the static cycling group worsened by 1.6% in UPDRS. To distinguish the static and dynamic cycling groups by biomechanical and physiological features, the complexity of the recorded signals (cadence, power, and heart rate) was examined using approximate entropy (ApEn), sample entropy (SaEn) and spectral entropy (SpEn) as measures of variability. A multiple linear regression (MLR) model was used to relate these features to changes in motor function as measured by the UPDRS Motor III scale. Pattern variability in cadence was greater in the dynamic group when compared to the static group. In contrast, variability in power was greater for the static group. UPDRS Motor III scores predicted from the pattern variability data were correlated to measured scores in both groups. These results support our previous study which explained how variability analysis results for biomechanical and physiological parameters of exercise can be used to predict improvements in motor function.

Figures

Fig. 1

Duplicating the tandem cycling with Smart Exercise Bike.

Fig. 2

Smart exercise bike, completed system.

Fig. 3

Correlation analysis of real (measured) versus predicted UPDRS values for linear MLR model. A: Static group (voluntary exercise). B: Dynamic group (active assisted exercise). C: Combined static and dynamic data. There was a positive, but small correlation of the real and predicted UPDRS Motor III scores in both the static (r=0.39) and dynamic (r=0.30) groups. Combined scores also maintained a positive, but not significant correlation(r=0.39) between real and predicted scores.

Fig. 4

Correlation analysis of real (measured) versus predicted UPDRS values for linear model with interactions. A: Static group (voluntary exercise). B: Dynamic group (active-assisted exercise). C: Combined static and dynamic data. There was a positive and significant correlation between real and predicted UPDRS Motor III scores in both the static (r=0.81) and dynamic groups (r=0.87). Combined scores also maintained a positive and significant correlation between real and predicted scores (r=0.63).