Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised learning
Paper
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2311.04215
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Published
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E4SelfLearning is a collection of the following open-access datasets recording with an Empatica E4:
- ADARP - Creative Commons Attribution 4.0 International
- BID IDEAS Lab - Open Data Commons Attribution License v1.0
- In-Gauge En-Gage - Open Data Commons Attribution License v1.0
- Nurses Stress Detection - ODC Database Contents License (DbCL) v1.0
- PPG-DaLiA - Creative Commons Attribution 4.0 International
- SPS - MIT License
- Toadstool - Creative Commons Attribution 4.0 International
- UE4W - Creative Commons Attribution 4.0 International
- WEEE - Creative Commons Attribution 4.0 International
- WESAD - licence details
- WESD - Open Data Commons Attribution License v1.0
E4SelfLearning was used in the following article: ''Wearable data from students, teachers or subjects with alcohol use disorder help detect acute mood episodes via self-supervised learning''.
The codebase to pre-process E4SelfLearning and use it for training an E4-tailored self-supervised learning Transformer model (E4mer) is available at APRIL lab.
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