Wearable Long-Term Graph Learning for Non-invasive Mental Health Evaluation
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-0109-4_15
Reference12 articles.
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3. Sano, A., et al.: Prediction of happy-sad mood from daily behaviors and previous sleep history. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 6796–6799 (2015).
4. Mahmud, M.S., Wang, H., Hua, F.: SensoRing: an integrated wearable system for continuous measurement of physiological biomarkers. In: 2018 IEEE International Conference on Communications (ICC), pp. 1–7 (2018)
5. Ghandeharioun, A., Fedor, S., Sangermano, L., Ionescu, D., Picard, R.: Objective assessment of depressive symptoms with machine learning and wearable sensors data. In: 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), pp. 325–332 (2017)
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