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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.
Afiliação
  • Mitsi G; Apptomics Inc., Wellesley, MA, United States.
  • Mendoza EU; Neuroscience Associates, Greenville Health System, Greenville, SC, United States.
  • Wissel BD; Gardner Family Center for Parkinson's Disease and Movement Disorders, Department of Neurology, University of Cincinnati, Cincinnati, OH, United States.
  • Barbopoulou E; Department of Mathematics, City University London, London, United Kingdom.
  • Dwivedi AK; Department of Computer Science and Engineering, City University London, London, United Kingdom.
  • Tsoulos I; Division of Biostatistics and Epidemiology, Department of Biomedical Sciences, Texas Tech University Health Sciences Center, El Paso, TX, United States.
  • Stavrakoudis A; Department of Informatics and Telecommunications, Technological Educational Institute of Epirus, Epirus, Greece.
  • Espay AJ; Department of Economics, University of Ioannina, Ioannina, Greece.
  • Papapetropoulos S; Gardner Family Center for Parkinson's Disease and Movement Disorders, Department of Neurology, University of Cincinnati, Cincinnati, OH, United States.
Front Neurol ; 8: 273, 2017.
Article em En | MEDLINE | ID: mdl-28659858
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 patients' 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article