Hypothesis generating model-based wearable clinical trial
Author and article information
Abstract
Wearable physiological sensors have the projected capability to detect unknown and unreported health conditions. Development requires rounds of discovery-oriented human subject research and confirmatory clinical trials. However, each study is a significant investment and difficult to justify in isolation. This impasse requires bootstrapping spiral device development through hypothesis-generating, model-based clinical trials. An unconventional clinical trial design addresses environmental health and infectious disease, through the day-to-day observation of diverse people who occupy a shared environment. The design utilizes a flexible suite of developmental diagnostic devices to detect the physiological impact of exposures. Through advanced data analysis, the devices provide information about deviations from normal parameters for each human subject. The correlation of these anomalies across the entire cohort generates hypotheses about exposures that impact health. These hypotheses can be investigated further in targeted studies and lead to simultaneous refinement of the devices.
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2016. Hypothesis generating model-based wearable clinical trial. PeerJ Preprints 4:e2079v1 https://doi.org/10.7287/peerj.preprints.2079v1Author comment
This is a preprint submission to PeerJ Preprints.
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Competing Interests
The author is affiliated to US Naval Research Laboratory, Washington DC.
Author Contributions
Benjamin C Kirkup wrote the paper, reviewed drafts of the paper.
Data Deposition
The following information was supplied regarding data availability:
The research in this article did not generate any raw data.
Funding
The author was funded under the NRL CORE program during preparation of the manuscript. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
