Biometric Digital Health Technology for Measuring Motor Function in Parkinson’s Disease: Results from a Feasibility and Patient Satisfaction Study - Mitsi, Georgia; Mendoza, Enrique Urrea; Wissel, Benjamin D.; Barbopoulou, Elena; Dwivedi, Alok K.; Tsoulos, Ioannis; Stavrakoudis, Athanassios; Espay, Alberto J.; Papapetropoulos, Spyros (Frontiers in Neurology, 2017)
Objectives: To assess the feasibility, predictive value, and user satisfaction of objectively quantifying motor function in Parkinson’s disease (PD) through a tablet-based application (iMotor) using self-administered tests. Methods: PD and healthy controls (HCs) performed finger tapping, hand pronation-supination and reaction time tasks using the iMotor application. Results: Thirty-eight participants (19 with PD and 17 HC) were recruited in the study. PD subjects were 53% male, with a mean age of 67.8 years (8.8), mean disease duration of 6.5 years (4.6), MDS-UPDRS-III score 26.3 (6.7) and H&Y stage 2. In the univariate analysis, most tapping variables were significantly different in PD compared to HC. Tap interval provided the highest predictive ability (90%). In the multivariable logistic regression model reaction time (reaction time test) (p=0.021) and total taps (two-target test) (p=0.026) were associated with PD. A combined model with two-target (total taps and accuracy) and reaction time produced maximum discriminatory performance between HC and PD. The overall accuracy of the combined model was 0.98 (95%CI:0.93-1). iMotor use achieved high rates of patients’ satisfaction as evaluated by a patient satisfaction survey. Conclusion: iMotor accurately differentiated PD subjects from HCs using simple alternating tasks of motor function. The impact on patient care of at-home iMotor-assisted remote monitoring deserves further evaluation.