TY - GEN
T1 - ADARP
T2 - 2022 IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, BSN 2022
AU - Sah, Ramesh Kumar
AU - McDonell, Michael
AU - Pendry, Patricia
AU - Parent, Sara
AU - Ghasemzadeh, Hassan
AU - Cleveland, Michael J.
N1 - Funding Information:
1 School of Electrical Engineering and Computer Science, 2 Elson S. Floyd College of Medicine, 3 Department of Human Development, 4 College of Health Solutions, ∗ Washington State University, Pullman, USA, and # Arizona State University, Tempe, USA. This project was funded by the Alcohol and Drug Research Program of Washington State University through grant funding to Michael J Cleveland. This investigation was supported in part by funds provided for medical and biological research by the State of Washington Initiative Measure #171.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Stress detection and classification from wearable sensor data is an emerging area of research with significant implications for individuals' physical and mental health. In this work, we introduce a new dataset, ADARP, which contains physiological data and self-report outcomes collected in real-world ambulatory settings involving individuals diagnosed with alcohol use disorders. We describe the user study, present details of the dataset, establish the significant correlation between physiological data and self-reported outcomes, demonstrate stress classification, and make our dataset public to facilitate research.
AB - Stress detection and classification from wearable sensor data is an emerging area of research with significant implications for individuals' physical and mental health. In this work, we introduce a new dataset, ADARP, which contains physiological data and self-report outcomes collected in real-world ambulatory settings involving individuals diagnosed with alcohol use disorders. We describe the user study, present details of the dataset, establish the significant correlation between physiological data and self-reported outcomes, demonstrate stress classification, and make our dataset public to facilitate research.
KW - alcohol use disorder
KW - machine learning
KW - mobile health
KW - stress
KW - wearable sensors
UR - http://www.scopus.com/inward/record.url?scp=85152772017&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85152772017&partnerID=8YFLogxK
U2 - 10.1109/BSN56160.2022.9928495
DO - 10.1109/BSN56160.2022.9928495
M3 - Conference contribution
AN - SCOPUS:85152772017
T3 - BHI-BSN 2022 - IEEE-EMBS International Conference on Biomedical and Health Informatics and IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks - Proceedings
BT - BHI-BSN 2022 - IEEE-EMBS International Conference on Biomedical and Health Informatics and IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 September 2022 through 30 September 2022
ER -