Unobtrusive Monitoring of Parkinson's Disease Based on Digital Biomarkers of Human Behaviour

Research output: Contribution to conferencePaper


© 2017 Copyright held by the owner/author(s). Parkinson's Disease impairs the motor, cognitive and emotional functioning of people. Clinicians do not get an accurate image of the disease because patients visit them every six months and their symptoms can change within hours. Technology has been used to tackle this problem, but most approaches disrupt people's routines or are uncomfortable to use. We aim to monitor Parkinson's in an unobtrusive, longitudinal and naturalistic way based on digital biomarkers inferred from smartphone-collected heterogeneous data. We use Parkinson's clinical scales and self-reporting of symptoms as ground truth to evaluate our methodology. Here, we present three insights we gained after tracking four people 24/7 for four months: a) the monitoring smartphone needs to be people's primary device, b) participants prefer a paper diary for symptom self-reporting, and c) social and phone interaction will be explored as digital biomarkers. We expect this approach to improve patient's quality of life and the efficiency of health services.
Original languageEnglish
Number of pages2
Publication statusPublished - 20 Oct 2017


Dive into the research topics of 'Unobtrusive Monitoring of Parkinson's Disease Based on Digital Biomarkers of Human Behaviour'. Together they form a unique fingerprint.

Cite this