Cocaine-Related Disorders Clinical Trial
Official title:
Towards Detecting Cocaine Use Using Smartwatches in the NIDA Clinical Trials Network
The overall objective of this study is to extend previous work in the development of methods to automatically detect the timing of cocaine use from cardiac interbeat interval and physical activity data derived from wearable, unobtrusive mobile sensor technologies. The specific objectives of this protocol are to characterize under which conditions high quality continuous interbeat interval data and physical activity data can be obtained from a specially developed smartwatch device in the natural field setting among a population of cocaine users. In addition to identifying common failure scenarios and understanding wearability/usage patterns when collecting interbeat interval from smartwatches, this study will extend previous work in the detection of cocaine use via interbeat interval and physical activity data that were previously obtained from wearable chestband sensors. Information from this study will contribute toward the adaptation of the investigators' existing computational model for detecting cocaine use via the chest sensors, so it can be applied to the interbeat and physical activity data obtained from less obtrusive smartwatches.
This study will evaluate a smartwatch device for the continuous field assessment of
physiological measures, including cardiac interbeat interval and physical activity. These
measures have been previously employed using wearable chest sensors to develop a model for
the automatic in-the-field detection of the timing of cocaine use; computational models using
physiological data of this type have been used in prior research to detect cocaine use and
moment-by-moment stress using a mobile sensor suite called AutoSense. AutoSense is a
chest-worn device used to collect measures of heart rate via a two-lead electrocardiograph
(ECG) and physical activity via 3-axis accelerometers that can be transmitted wirelessly to
an Android-based smartphone for initial processing and data storage. The adapted AutoSense
protocol will incorporate smartwatches specially designed to continuously detect heart beat
timings using optical photoplethysmogram (PPG) sensors rather than ECG leads.
Prior to the start of this protocol, investigators will optimize collection of cardiac
interbeat interval data on the smartwatches via a preliminary ambulatory study (with
Co-Investigator Ertin at the Ohio State University). The development of the smartwatch device
and the initial smartwatch computational model is currently being supported separately
(outside of this human subjects protocol) by the National Drug Abuse Treatment Clinical
Trials Network (CTN). Investigators and research assistants at the Ohio State University will
wear prototypes of the smartwatch devices and the AutoSense chest sensor during waking hours
for five days to capture cardiac interbeat interval data as well as identify initial fit and
usability problems with the prototype smartwatch devices and inform its subsequent
refinements. This preliminary ambulatory study is a separate protocol being conducted at Ohio
State University with oversight by that institution's Institutional Review Board (IRB), and
thus is not considered part of the 0073-Ot human subjects protocol.
Once the preliminary study has concluded, investigators will conduct a field test during
which the smartwatch and AutoSense chest sensors will be worn by 25 cocaine users for two
weeks (5 participants will participate in pilot testing for two weeks each, after which the
smartwatch device may undergo further refinements for improved wearability and/or data
collection among the remaining participants). Outcomes of this study are to characterize the
feasibility of the smartwatch device to continuously detect interbeat interval and physical
activity data, and to characterize situations where data yield of sufficient quality for the
application of more advanced computational models (e.g., cocaine detection) can take place in
participants' natural field settings. Secondarily, data from the trial will be used to
compare data yields from the two sensor suites being worn (the smartwatch devices and the
AutoSense chest sensors). The data may also be useful for updating the computational models
(e.g., cocaine detection) previously developed with the AutoSense chest sensors for data
collected by the smartwatches. The results from this study may be used to inform future
research of this type to investigate technological improvements and the situations during
which using mobile sensors can unobtrusively characterize precipitants and use patterns
(e.g., contextual) surrounding drug use events.
It is important to note that this study is not designed to assess the acceptability of the
smartwatch among cocaine users, nor is it a study to evaluate the utility of using a
smartwatch for measuring cocaine use outcomes as part of a clinical trial. Rather,
investigators are intentionally recruiting participants who frequently use cocaine and
compensating them to participate in this study designed to characterize the feasibility of
using a smartwatch to collect reliable, continuous interbeat interval and physical activity
data in the natural field setting, and to characterize under what conditions high quality
data can be obtained from smartwatches. If results are promising, future research designs
with larger sample sizes can explore some of these more clinically-relevant scientific
questions.
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