Towards Generalized ML Model in Automated Physiological Arousal Computing: A Transfer Learning-Based Domain Generalization Approach

Author:

Fang Ruijie1,Zhang Ruoyu1,Hosseini Elahe1,Parenteau Anna M.2,Hang Sally2,Rafatirad Setareh1,Hostinar Camelia E.2,Orooji Mahdi1,Homayoun Houman1

Affiliation:

1. University of California,ECE Department,Davis,CA,USA

2. University of California,Department of Psychology,Davis,CA,USA

Publisher

IEEE

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Emotion and Stress Recognition Utilizing Galvanic Skin Response and Wearable Technology: A Real-time Approach for Mental Health Care;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

2. Introducing an Open-Source Python Toolkit for Machine Learning Research in Physiological Signal based Affective Computing;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

3. Privee: A Wearable for Real-Time Bladder Monitoring System;Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing;2023-10-08

4. Automatic Pain Detection Through Facial Expression;Advances in Systems Analysis, Software Engineering, and High Performance Computing;2023-09-07

5. Continuous Stress Monitoring for Healthcare Workers: Evaluating Generalizability Across Real-World Datasets;Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics;2023-09-03

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