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Conference object . 2015
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Remote Digital Biomarker Monitoring Bringing A Smartphonebased Diagnostic Test For Parkinson'S Disease Progression Into An Interventional Trial

Authors: Christian Gossens;

Remote Digital Biomarker Monitoring Bringing A Smartphonebased Diagnostic Test For Parkinson'S Disease Progression Into An Interventional Trial

Abstract

In clinical research objective, automated and high frequency measures of disease progression are hard to come by. Traditional physicianled tests are only done periodically, missing the fluctuations of disease activity that strongly affect patient's quality of life. They also lack the objectivity that is so important when developing medicines. By providing patients with mobile sensors they carry day in and day out to conduct tests and capture the data, we are addressing this need. We designed a custom Android App asking patients to complete six “Active Tests” on a daily basis, wherever they are. After completing the Active Tests, patients will then pop their phone in their pockets and carry it around with them throughout the day. This is what we call “Passive Monitoring”. We have established an end to end approach and technology platform with great potential. Our experience will give other clinical studies the confidence that we can bring the required software and workflows to the clinic. Compliance and ethics hurdles have been cleared and investigators trained. We are already gaining experience with patient uptake and are developing the necessary data analysis techniques. Interpretation of mobile sensor data might soon replace traditional assessments.

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Keywords

Parkinson's Disease, Digital biomarker, remote patient monitoring, smartphone, app

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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