research-article

Domain adaptation methods for improving lab-to-field generalization of cocaine detection using wearable ECG

Authors:

Annamalai Natarajan,

Gustavo Angarita,

Robert Malison,

Deepak Ganesan,

Benjamin M. MarlinAuthors Info & Claims

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Pages 875 - 885

https://doi.org/10.1145/2971648.2971666

Published: 12 September 2016 Publication History

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.

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Cited By

Kambale WSalem MBenarbia TAl Machot FKyamakya K(2024)Comprehensive Sensitivity Analysis Framework for Transfer Learning Performance Assessment for Time Series Forecasting: Basic Concepts and Selected Case StudiesSymmetry10.3390/sym1602024116:2(241)Online publication date: 16-Feb-2024
https://doi.org/10.3390/sym16020241
Lyu SChen YDuan DJia RXu W(2024)EarDA: Towards Accurate and Data-Efficient Earable Activity Sensing2024 IEEE Coupling of Sensing & Computing in AIoT Systems (CSCAIoT)10.1109/CSCAIoT62585.2024.00005(1-7)Online publication date: 13-May-2024
https://doi.org/10.1109/CSCAIoT62585.2024.00005
Alajaji AGerych WBuquicchio LChandrasekaran KMansoor HAgu ERundensteiner E(2023)Domain Adaptation Methods for Lab-to-Field Human Context RecognitionSensors10.3390/s2306308123:6(3081)Online publication date: 13-Mar-2023
https://doi.org/10.3390/s23063081
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Index Terms

Domain adaptation methods for improving lab-to-field generalization of cocaine detection using wearable ECG
1. Computing methodologies
  1. Machine learning

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Published In

cover image ACM Conferences

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 2016

1288 pages

ISBN:9781450344616

DOI:10.1145/2971648

General Chairs:
Paul Lukowicz
DFKI and University of Kaiserslautern
,
Antonio Krüger
DFKI and Saarland University
,
Program Chairs:
Andreas Bulling
Max Planck Institute for Informatics
,
Youn-Kyung Lim
KAIST
,
Shwetak N. Patel
University of Washington

Copyright © 2016 ACM.

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Published: 12 September 2016

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UbiComp '16: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 12 - 16, 2016

Germany, Heidelberg

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UbiComp '16 Paper Acceptance Rate 101 of 389 submissions, 26%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

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https://doi.org/10.3390/sym16020241
Lyu SChen YDuan DJia RXu W(2024)EarDA: Towards Accurate and Data-Efficient Earable Activity Sensing2024 IEEE Coupling of Sensing & Computing in AIoT Systems (CSCAIoT)10.1109/CSCAIoT62585.2024.00005(1-7)Online publication date: 13-May-2024
https://doi.org/10.1109/CSCAIoT62585.2024.00005
Alajaji AGerych WBuquicchio LChandrasekaran KMansoor HAgu ERundensteiner E(2023)Domain Adaptation Methods for Lab-to-Field Human Context RecognitionSensors10.3390/s2306308123:6(3081)Online publication date: 13-Mar-2023
https://doi.org/10.3390/s23063081
Byeon YKwak K(2023)Semi-Supervised Domain Adaptation for Individual Identification from Electrocardiogram SignalsApplied Sciences10.3390/app13241325913:24(13259)Online publication date: 14-Dec-2023
https://doi.org/10.3390/app132413259
Rafi TKo Y(2023)SF-ECG: Source-Free Intersubject Domain Adaptation for Electrocardiography-Based Arrhythmia ClassificationApplied Sciences10.3390/app1314855113:14(8551)Online publication date: 24-Jul-2023
https://doi.org/10.3390/app13148551
Duan DYang HLan GLi TJia XXu W(2023)EMGSense: A Low-Effort Self-Supervised Domain Adaptation Framework for EMG Sensing2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)10.1109/PERCOM56429.2023.10099164(160-170)Online publication date: 13-Mar-2023
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Angarita GPittman BNararajan AMayerson TParate AMarlin BGueorguieva RPotenza MGanesan DMalison R(2023)Discriminating cocaine use from other sympathomimetics using wearable electrocardiographic (ECG) sensorsDrug and Alcohol Dependence10.1016/j.drugalcdep.2023.110898250(110898)Online publication date: Sep-2023
https://doi.org/10.1016/j.drugalcdep.2023.110898
Nikolaidis KKristiansen SPlagemann TGoebel VLiestøl KKankanhalli MTraaen GØverland BAkre HAakerøy LSteinshamn S(2022)My Health Sensor, My Classifier – Adapting a Trained Classifier to Unlabeled End-User DataACM Transactions on Computing for Healthcare10.1145/35597673:4(1-24)Online publication date: 3-Nov-2022
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Oesterle TKarpyak VCoombes BAthreya ABreitinger SCorrea da Costa S(Dana) Gerberi D(2022)Systematic review: Wearable remote monitoring to detect nonalcohol/nonnicotine‐related substance use disorder symptomsThe American Journal on Addictions10.1111/ajad.1334131:6(535-545)Online publication date: 5-Sep-2022
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Alajaji AGerych WChandrasekaran KBuquicchio LMansoor HAgu ERundensteiner E(2022)Triplet-based Domain Adaptation (Triple-DARE) for Lab-to-field Human Context Recognition2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops53856.2022.9767432(155-161)Online publication date: 21-Mar-2022
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