Mobile-based Monitoring of Parkinson's Disease

Abstract

Parkinson's disease (PD) is the second most common neurodegenerative disorder, impacting an estimated seven to ten million people worldwide. It is commonly accepted that improving medication adherence alleviates symptoms and maintains motor capabilities. Not following the medication regimen (e.g., skipping or over-medicating) may worsen side-effects, which mislead clinicians and patients. We developed and evaluated a mobile application, STOP, for screening the PD symptoms and medication intake. It contains a game for tracking the PD symptoms, and a medication journal for recording medical intake and adherence. We conducted a 1-month long real-world deployment with 13 PD patients from two countries. We found that the application medication adherence tracking provides non-bias information, and users are receptive to share such data with their care and medical personnel.

Future Opportunities for IoT to Support People with Parkinson's

“…This in itself is a worthwhile consideration for future work exploring IoT solutions to support self-care. With acknowledged challenges around the burden that self-tracking can have on an individual [79,34], particularly in the sense that physical symptoms and unfamiliarity with technology can cause stress and fatigue, voice input could offer a light-touch way to collect daily report data [25].…”

Measuring Parkinson's disease motor symptoms with smartphone-based drawing tasks

“…This study was a proof of concept for conducting drawing tasks with a smartphone for measuring PD symptoms. The drawing tasks will be a part of a larger set of tools for longitudinal PD symptom assessment; we already have tools for medication logging, measuring the motor symptoms (mainly tremor) with a ball-balancing game, and reporting the daily self-evaluated symptom level [4,5]. With this combination of tools, we aim to assess the effectiveness of medication.…”

“…We will extract more parameters from the drawing data, such as the speed change within one drawing. We will combine the drawing data to the data collected by our existing tools [5]. The drawing results will be compared to the ballbalancing game performance metrics, and these combined with the medication logging we can estimate the medication effectiveness and lasting effect.…”