An Examination of the Feasibility of Detecting Cocaine Use Using Smartwatches

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.

Keywords: clinical trials; cocaine; measurement; mobile sensing; photoplethysmography.

Figure 1

Wrist-worn sensor development. (A,B) Illustrate the version of the wrist-worn sensor used in the Phase 1 Pilot study. (C,D) Show the sensor used in the Phase 2 Main study.

Figure 2

Bland-Altman plots comparing differences in ECG data by race and gender. (A,B) Illustrate the Bland-Altman plots comparing the ECG chest sensor and wrist sensor for African American participants and White participants. (C,D) Show the Bland-Altman plots comparing the ECG chest sensor and wrist sensor for female and male participants.