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README.md

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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): 
+E4SelfLearning is a collection of the following open-access datasets recording with an [Empatica E4](https://support.empatica.com/hc/en-us/articles/202581999-E4-wristband-technical-specifications): 
 
-- [ADARP](https://arxiv.org/pdf/2206.14568.pdf)
-- [BID IDEAS Lab](https://www.nature.com/articles/s41746-021-00465-w)
-- [In-Gauge En-Gage](https://www.nature.com/articles/s41597-022-01347-w)
-- [Nurses Stress Detection](https://www.nature.com/articles/s41597-022-01361-y)
-- [PPG-DaLiA](https://archive.ics.uci.edu/dataset/495/ppg+dalia)
-- [SPS](https://www.mdpi.com/1424-8220/22/21/8135)
-- [Toadstool](https://dl.acm.org/doi/10.1145/3339825.3394939)
-- [UE4W](https://zenodo.org/record/6898244)
-- [WEEE](https://www.nature.com/articles/s41597-022-01643-5)
-- [WESAD](https://dl.acm.org/doi/10.1145/3242969.3242985)
-- [WESD](https://ieeexplore.ieee.org/abstract/document/9744065)
+- [ADARP](https://zenodo.org/records/6640290) - [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/legalcode)
+- [BID IDEAS Lab](https://physionet.org/content/big-ideas-glycemic-wearable/1.0.0/) - [Open Data Commons Attribution License v1.0](https://physionet.org/content/big-ideas-glycemic-wearable/view-license/1.0.0/)
+- [In-Gauge En-Gage](https://physionet.org/content/in-gauge-and-en-gage/1.0.0/) - [Open Data Commons Attribution License v1.0](https://physionet.org/content/in-gauge-and-en-gage/view-license/1.0.0/)
+- [Nurses Stress Detection](https://www.kaggle.com/datasets/priyankraval/nurse-stress-prediction-wearable-sensors) - [ODC Database Contents License (DbCL) v1.0](https://www.ebi.ac.uk/ols4/ontologies/swo/classes/http%3A%2F%2Fwww.ebi.ac.uk%2Fswo%2Flicense%2FSWO_1000097?iri=http%3A%2F%2Fwww.ebi.ac.uk%2Fswo%2Flicense%2FSWO_1000097)
+- [PPG-DaLiA](https://archive.ics.uci.edu/dataset/495/ppg+dalia) - [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/)
+- [SPS](https://github.com/italha-d/Stress-Predict-Dataset/tree/main) - [MIT License](https://github.com/italha-d/Stress-Predict-Dataset/blob/main/LICENSE)
+- [Toadstool](https://www.kaggle.com/datasets/hugohammer/toadstool) - [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/)
+- [UE4W](https://zenodo.org/record/6898244) - [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/)
+- [WEEE](https://zenodo.org/records/6420886) - [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/)
+- [WESAD](https://archive.ics.uci.edu/dataset/465/wesad+wearable+stress+and+affect+detection) - [licence details](https://www.eti.uni-siegen.de/ubicomp/home/datasets/icmi18/index.html.en?lang=en)
+- [WESD](https://physionet.org/content/wearable-exam-stress/1.0.0/) - [Open Data Commons Attribution License v1.0](https://physionet.org/content/wearable-exam-stress/view-license/1.0.0/)
 
 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](https://arxiv.org/abs/2311.04215)''. 
 
-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).
+The codebase to pre-process E4SelfLearning and use it for training an E4-tailored self-supervised learning [Transformer](https://arxiv.org/abs/1706.03762) model (E4mer) is available at [APRIL lab](https://github.com/april-tools/e4selflearning).