Development of a remote therapeutic monitoring platform: applications for movement disorders

Figures

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  Fig. 1. Compliance results for daily and monthly surveys along with passive data collection (Healthkit: Apple Watch). Median compliance rates (orange) for the subjects were 100% for PDQ-39 (mean = 85.5%), 67.9% for PGIS (mean = 63.3%) and 71.8% for passive data (mean = 61.9%).

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  Fig. 2. Daily check-in scores (PGIS) tracked from baseline to 3 months post implant. On average, patients improved on the PGIS over the course of 3 months. At baseline, mean PGIS score was 4.4 ± 0.65, at 1-month it was 3.6 ± 0.09 and at 3-months it was 3.2 ± 0.08. Statistical significance (p < 0.05*) of PGIS post-implant compared to the baseline period was determined according to the paired Wilcoxon test with a one-sided alternative hypothesis on median values; multiple comparisons correction was applied.

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  Fig. 3. Conceptual framework of the Integrated platform for the RM app leveraging the cybersecurity infrastructure from commercially available Neurosphere platform with compatibility to consumer-grade wearables and validated algorithms to determine presence and severity of symptoms. The goal of the platform is to improve patient experience and optimize neuromodulation therapy. This figure illustrates the overarching vision of the Remote Therapeutic Monitoring Platform, where the backend can accept multimodal data as objective input from wearables (skin adhesives, smart ring, or smart watch) and patient-reported outcomes surveys, diaries, etc.). This data (raw traces) can be analyzed for specific insights using validated algorithms that are available through the backend. In this example, we are showing how insights about severity and presence of cardinal symptoms for PD can be extracted using this framework.

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  Fig. 4. Easy-to-navigate user interface of the RM application. The interface includes (1) Daily check-in using validated surveys (Patient Global Impression of Severity (PGIS)), (2) Timed surveys including validated quality of life metrics (Parkinson’s Disease Questionnaire 39 (PDQ-39)) and (Patient Global Impression of Change (PGIC), (3) Continuous objective sensor data collected through ubiquitous wearables (Apple Watch).

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  Fig. 5. Web Portal to monitor patient compliance for survey completion and wearable use. The profile tab allows the user to enter study duration and upcoming programming dates; survey data and device data tabs provide real-time data about patient compliance.