We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Biometric Digital Health Technology for Measuring Motor Function in Parkinson's Disease: Results from a Feasibility and Patient Satisfaction Study.
- Authors
Mitsi, Georgia; Mendoza, Enrique Urrea; Wissel, Benjamin D.; Barbopoulou, Elena; Dwivedi, Alok K.; Tsoulos, Ioannis; Stavrakoudis, Athanassios; Espay, Alberto J.; Papapetropoulos, Spyros
- Abstract
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 HCs) 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), Movement Disorders Society version of the Unified Parkinson Disease Rating Scale III score 26.3 (±6.7), and Hoehn & Yahr 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% confidence interval: 0.93-1). iMotor use achieved high rates of patient's satisfaction as evaluated by a patient satisfaction survey. Conclusion: iMotor differentiated PD subjects from HCs using simple alternating tasks of motor function. Results of this feasibility study should be replicated in larger, longitudinal, appropriately designed, controlled studies. The impact on patient care of at-home iMotor-assisted remote monitoring also deserves further evaluation.
- Subjects
MEDICAL technology; BIOMETRIC identification; PARKINSON'S disease patients
- Publication
Frontiers in Neurology, 2017, p1
- ISSN
1664-2295
- Publication type
Article
- DOI
10.3389/fneur.2017.00273