Large-Scale Wearable Sensor Deployment in Parkinson's Patients: The Parkinson@Home Study Protocol

Ana Lígia Silva de Lima, Tim Hahn, Nienke M de Vries, Eli Cohen, Lauren Bataille, Max A Little, Heribert Baldus, Bastiaan R Bloem, Marjan J Faber, Ana Lígia Silva de Lima, Tim Hahn, Nienke M de Vries, Eli Cohen, Lauren Bataille, Max A Little, Heribert Baldus, Bastiaan R Bloem, Marjan J Faber

Abstract

Background: Long-term management of Parkinson's disease does not reach its full potential because we lack knowledge about individual variations in clinical presentation and disease progression. Continuous and longitudinal assessments in real-life (ie, within the patients' own home environment) might fill this knowledge gap.

Objective: The primary aim of the Parkinson@Home study is to evaluate the feasibility and compliance of using multiple wearable sensors to collect clinically relevant data. Our second aim is to address the usability of these data for answering clinical research questions. Finally, we aim to build a database for future validation of novel algorithms applied to sensor-derived data from Parkinson's patients during daily functioning.

Methods: The Parkinson@Home study is a two-phase observational study involving 1000 Parkinson's patients and 250 physiotherapists. Disease status is assessed using a short version of the Parkinson's Progression Markers Initiative protocol, performed by certified physiotherapists. Additionally, participants will wear a set of sensors (smartwatch, smartphone, and fall detector), and use these together with a customized smartphone app (Fox Insight), 24/7 for 3 months. The sensors embedded within the smartwatch and fall detector may be used to estimate physical activity, tremor, sleep quality, and falls. Medication intake and fall incidents will be measured via patients' self-reports in the smartphone app. Phase one will address the feasibility of the study protocol. In phase two, mathematicians will distill relevant summary statistics from the raw sensor signals, which will be compared against the clinical outcomes.

Results: Recruitment of 300 participants for phase one was concluded in March, 2016, and the follow-up period will end in June, 2016. Phase two will include the remaining participants, and will commence in September, 2016.

Conclusions: The Parkinson@Home study is expected to generate new insights into the feasibility of integrating self-collected information from wearable sensors into both daily routines and clinical practices for Parkinson's patients. This study represents an important step towards building a reliable system that translates and integrates real-life information into clinical decisions, with the long-term aim of delivering personalized disease management support.

Clinicaltrial: ClinicalTrials.gov NCT02474329; https://ichgcp.net/clinical-trials-registry/NCT02474329 (Archived at http://www.webcitation.org/6joEc5P1v).

Keywords: Parkinson’s disease; ambulatory monitoring; computer-assisted; signal processing; wearable sensors.

Conflict of interest statement

Conflicts of Interest: Ana Lígia Silva de Lima is supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES Foundation; grant number 0428-140). Bastiaan R Bloem received grant support from the Michael J Fox Foundation and the Stichting Parkinson Foundation. Eli Cohen is supported by Intel Corporation. Lauren Bataille is supported by the Michael J. Fox Foundation. Max Little is managing director of NumericAnalysis Ltd. and received research funding support from the Michael J Fox Foundation. Heribert Baldus is supported by Philips Research. Tim Hahn, Nienke M de Vries, and Marjan J Faber declare no competing interests.

Figures

Figure 1
Figure 1
Fox Insight Mobile App activity graph.
Figure 2
Figure 2
Fox Insight Mobile App sleep analysis graph.
Figure 3
Figure 3
Fox Insight Mobile app main screen.

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