title: Domain Adaptation Methods for Improving Lab-to-field Generalization of Cocaine Detection using Wearable ECG.
abstract: Mobile health research on illicit drug use detection typically involves a two-stage study design where data to learn detectors is first collected in lab-based trials, followed by a deployment to subjects in a free-living environment to assess detector performance. While recent work has demonstrated the feasibility of wearable sensors for illicit drug use detection in the lab setting, several key problems can limit lab-to-field generalization performance. For example, lab-based data collection often has low ecological validity, the ground-truth event labels collected in the lab may not be available at the same level of temporal granularity in the field, and there can be significant variability between subjects. In this paper, we present domain adaptation methods for assessing and mitigating potential sources of performance loss in lab-to-field generalization and apply them to the problem of cocaine use detection from wearable electrocardiogram sensor data.
authors.affiliation: College of Information and Computer Sciences, University of Massachusetts Amherst.
authors.forename: Annamalai
authors.initials: A
authors.lastname: Natarajan
authors.affiliation: Department of Psychiatry, Yale School of Medicine, New Haven.
authors.forename: Gustavo
authors.initials: G
authors.lastname: Angarita
authors.affiliation: Department of Psychiatry, Yale School of Medicine, New Haven.
authors.forename: Edward
authors.initials: E
authors.lastname: Gaiser
authors.affiliation: Department of Psychiatry, Yale School of Medicine, New Haven.
authors.forename: Robert
authors.initials: R
authors.lastname: Malison
authors.affiliation: College of Information and Computer Sciences, University of Massachusetts Amherst.
authors.forename: Deepak
authors.initials: D
authors.lastname: Ganesan
authors.affiliation: College of Information and Computer Sciences, University of Massachusetts Amherst.
authors.forename: Benjamin M
authors.initials: BM
authors.lastname: Marlin
keywords: Covariate shift; classification; cocaine detection; domain adaptation; prior probability shift; wearable sensors