Scientific Reports · 2022 · 111 citations · 54 references
MedicineNeurologyAssistive TechnologyFunctional Movement AssessmentMovement DisordersClinical Movement AssessmentGait AnalysisMobile Health Data CollectionParkinson DiseaseParkinsonian DisordersWearable Health TechnologiesClinical Diagnosis Of ParkinsonismMovement Disorder AssessmentRemote Home MonitoringTest-retest ReliabilityTremor Severity AssessmentTremor Severity RatingUnified Parkinson's Disease Rating ScaleWearable Sensor-based Assessment
Digital health technologies enable remote and therefore frequent measurement of motor signs, potentially providing reliable and valid estimates of motor sign severity and progression in Parkinson's disease (PD). The Roche PD Mobile Application v2 was developed to measure bradykinesia, bradyphrenia and speech, tremor, gait and balance. It comprises 10 smartphone active tests (with ½ tests administered daily), as well as daily passive monitoring via a smartphone and smartwatch. It was studied in 316 early-stage PD participants who performed daily active tests at home then carried a smartphone and wore a smartwatch throughout the day for passive monitoring (study NCT03100149). Here, we report baseline data. Adherence was excellent (96.29%). All pre-specified sensor features exhibited good-to-excellent test-retest reliability (median intraclass correlation coefficient = 0.9), and correlated with corresponding Movement Disorder Society-Unified Parkinson's Disease Rating Scale items (rho: 0.12-0.71). These findings demonstrate the preliminary reliability and validity of remote at-home quantification of motor sign severity with the Roche PD Mobile Application v2 in individuals with early PD.
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Christopher G. Goetz, Barbara C. Tilley, Stephanie R. Shaftman et al. · Movement Disorders · 2008 · 7.5K citations · Full text
The mPower study, Parkinson disease mobile data collected using ResearchKit
Brian M. Bot, Christine Suver, Elias Chaibub Neto et al. · Scientific Data · 2016 · 641 citations · Full text