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license: cc
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license: cc
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---
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E4SelfLearning is a collection of the following open-access datasets recording with an [Emaptica E4](https://support.empatica.com/hc/en-us/articles/202581999-E4-wristband-technical-specifications):
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- [ADARP](https://arxiv.org/pdf/2206.14568.pdf)
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- [BID IDEAS Lab](https://www.nature.com/articles/s41746-021-00465-w)
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- [In-Gauge En-Gage](https://www.nature.com/articles/s41597-022-01347-w)
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- [Nurses Stress Detection](https://www.nature.com/articles/s41597-022-01361-y)
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- [PPG-DaLiA](https://archive.ics.uci.edu/dataset/495/ppg+dalia)
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- [SPS](https://www.mdpi.com/1424-8220/22/21/8135)
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- [Toadstool](https://dl.acm.org/doi/10.1145/3339825.3394939)
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- [UE4W](https://zenodo.org/record/6898244)
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- [WEEE](https://www.nature.com/articles/s41597-022-01643-5)
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- [WESAD](https://dl.acm.org/doi/10.1145/3242969.3242985)
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- [WESD](https://ieeexplore.ieee.org/abstract/document/9744065)
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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](https://arxiv.org/abs/2311.04215)''.
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The codebase to pre-process E4SelfLearning and use it for training a self-supervised learning model (E4mer) is available at [APRIL lab](https://github.com/april-tools/e4selflearning).
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