Abstract
As digital technology increasingly informs clinical trials, novel ways to collect study data in the natural field setting have the potential to enhance the richness of research data. Cocaine use in clinical trials is usually collected via self-report and/or urine drug screen results, both of which have limitations. This article examines the feasibility of developing a wrist-worn device that can detect sufficient physiological data (i.e., heart rate and heart rate variability) to detect cocaine use. This study aimed to develop a wrist-worn device that can be used in the natural field setting among people who use cocaine to collect reliable data (determined by data yield, device wearability, and data quality) that is less obtrusive than chest-based devices used in prior research. The study also aimed to further develop a cocaine use detection algorithm used in previous research with an electrocardiogram on a chestband by adapting it to a photoplethysmography sensor on the wrist-worn device which is more prone to motion artifacts. Results indicate that wrist-based heart rate data collection is feasible and can provide higher data yield than chest-based sensors, as wrist-based devices were also more comfortable and affected participants' daily lives less often than chest-based sensors. When properly worn, wrist-based sensors produced similar quality of heart rate and heart rate variability features to chest-based sensors and matched their performance in automated detection of cocaine use events.Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02915341.
Highlights
Digital health technologies are changing the way we conduct research [1]
Concomitant medications prescribed for enrolled Pilot participants included methadone, an Angiotensin Converting Enzyme (ACE) inhibitor, calcium channel blocker, anti-convulsant, proton pump inhibitor, antipsychotic, antidepressant, and a benzodiazepine
Though participants appear to have worn the chest sensor (ECG) longer, the quality of the data collected was superior in the wrist sensors (PPG); 68.7% of data collected from the left wrist sensor and 77.7% from the right wrist sensor were of acceptable quality, while only 34.4% of data were of acceptable quality
Summary
Collecting data via digital devices [a.k.a., mobile health (mHealth)] in the natural field setting in which research participants make health choices presents an opportunity to collect granular data as individuals live their daily lives. These ecologically valid data may enhance the richness of research data, without excessive intrusion by researchers or strict reliance on participant recall. Cocaine use detection in clinical trials is usually measured via self-report and/or urine drug screens. Sensing physiological data via wearable digital health technologies (e.g., heart rate and heart rate variability) may offer a potential avenue to collect objective data that can better inform the detection of use events and be unobtrusive and convenient for both participants and researchers
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