Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial

Abstract

Background: Ubiquitous digital technologies such as smartphone sensors promise to fundamentally change biomedical research and treatment monitoring in neurological diseases such as PD, creating a new domain of digital biomarkers.

Objectives: The present study assessed the feasibility, reliability, and validity of smartphone-based digital biomarkers of PD in a clinical trial setting.

Methods: During a 6-month, phase 1b clinical trial with 44 Parkinson participants, and an independent, 45-day study in 35 age-matched healthy controls, participants completed six daily motor active tests (sustained phonation, rest tremor, postural tremor, finger-tapping, balance, and gait), then carried the smartphone during the day (passive monitoring), enabling assessment of, for example, time spent walking and sit-to-stand transitions by gyroscopic and accelerometer data.

Results: Adherence was acceptable: Patients completed active testing on average 3.5 of 7 times/week. Sensor-based features showed moderate-to-excellent test-retest reliability (average intraclass correlation coefficient = 0.84). All active and passive features significantly differentiated PD from controls with P < 0.005. All active test features except sustained phonation were significantly related to corresponding International Parkinson and Movement Disorder Society-Sponsored UPRDS clinical severity ratings. On passive monitoring, time spent walking had a significant (P = 0.005) relationship with average postural instability and gait disturbance scores. Of note, for all smartphone active and passive features except postural tremor, the monitoring procedure detected abnormalities even in those Parkinson participants scored as having no signs in the corresponding International Parkinson and Movement Disorder Society-Sponsored UPRDS items at the site visit.

Conclusions: These findings demonstrate the feasibility of smartphone-based digital biomarkers and indicate that smartphone-sensor technologies provide reliable, valid, clinically meaningful, and highly sensitive phenotypic data in Parkinson's disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Keywords: Parkinson's disease; clinical trial; digital biomarkers; digital health; remote patient monitoring.

Figure 1

Screenshots of the smartphone application and workflow for the daily assessments. The smartphone (Galaxy S3 mini; Samsung, Seoul, South Korea) was provided with a single, preinstalled custom application (Roche PD Mobile Application v1; Roche, Basel, Switzerland). The application requested the completion of six active tests daily and subsequently recorded sensor data during daily living (“passive monitoring”), whereby participants were instructed to carry the smartphone in their trouser pocket, or a small bag around the waist.

Figure 2

Machine‐learning algorithms applied to passive monitoring data revealed multiple aspects of significantly reduced everyday motor behavior in PD participants compared with controls. See Results (Reliability of Testing) for details. ^** P < 0.01; ^*** P < 0.001. C, control group.

Figure 3

Active test feature scores aggregated over 2 weeks of in‐home testing demonstrated case‐control differences, significant relationships with clinical severity ratings, and significantly greater sensitivity compared with MDS‐UPDRS item/subscale scores from site visits. The orange arrow indicates the statistical test for association of increased disease severity as to the selected MDS‐UPDRS item with the digital biomarker feature, taking into account repeated measures per participant. The black square bracket indicates a comparison of the control group (C) with PD participants that are rated “0” for the corresponding MDS‐UPDRS item. ^* P < 0.05; ^** P < 0.01; ^*** P < 0.001. C, control group; MFCC2, mel‐frequency cepstral coefficient 2; n.s, not significant.