Enabling breakthroughs in Parkinson's disease with wearable technologies and big data analytics.

Area of Science:

• Neurology
• Biomedical Engineering
• Digital Health

Background:

• Parkinson's disease (PD) is a progressive neurodegenerative disorder.
• Current clinical diagnosis relies on the Unified Parkinson's Disease Rating Scale (UPDRS).
• Objective, continuous monitoring tools are needed to enhance PD research and therapeutic development.

Purpose of the Study:

• To develop a scalable Internet of Things (IoT) platform and mobile application for objective, continuous monitoring of Parkinson's disease (PD) motor symptoms.
• To support large-scale research studies by collecting and analyzing sensory data from individuals with PD.
• To provide researchers with open-source access to collected data for advanced analyses.

Main Methods:

• Development of a mobile application and an IoT platform in collaboration with The Michael J. Fox Foundation and Intel Corporation.
• Integration of wearable sensors for continuous data sampling.
• Implementation of population and per-patient analyses for gait, activity levels, tremor, and other motor functions.

Main Results:

• Successful demonstration of the IoT platform's proof of concept for PD research.
• Collection of continuous, objective sensory data from individuals with PD.
• Identification of key engineering considerations including sensor selection, data management, and algorithm validation.

Conclusions:

• IoT platforms and wearable technologies offer a robust, reliable, and cost-effective approach to PD research.
• Continuous data monitoring can significantly inform therapeutic development and clinical trial outcomes.
• This technology holds promise for advancing patient care strategies in Parkinson's disease.