Towards Detecting Cocaine Use Using Smartwatches in the NIDA Clinical Trials Network

This project will investigate methods to detect cocaine use from heart rate data captured by smartwatches.  This approach may nicely complement self-report methods that suffer from temporal inaccuracy in reporting cocaine use in the field setting.  Detection of cocaine use through smartwatches will build upon, and extend, recently developed methods to identify cocaine use from interbeat interval heart rate data obtained from electrocardiogram (ECG) sensors and physical activity from accelerometer data.  A smartwatch device will be developed that can reliably detect interbeat interval and can last the entire day on a single charge of battery with continuous sensor data collection.  A user study will be conducted to determine feasibility of using smartwatches to collect reliable interbeat interval and physical activity data in the natural field setting.  This study will provide the data necessary to determine under what conditions high quality data can be obtained from smartwatches, identify common failure scenarios, and understand wearability/usage patterns.  A computational model will be adapted for detecting cocaine use from interbeat interval, so it can be applied to the interbeat and physical activity data obtained from smartwatches.  The degree of specificity of the model relative to other stimulant use will also be assessed.

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Principal Investigator(s)

Lisa A. Marsch, Ph.D.

Professor, Department of Psychiatry; Director, Center for Technology and Behavioral Health; Director, Dartmouth Psychiatric Research Center
Geisel School of Medicine at Dartmouth College
Department of Biomedical Data Science

46 Centerra Parkway, Suite 315
Lebanon, NH 03766
United States