Open Access
| Issue |
E3S Web Conf.
Volume 491, 2024
International Conference on Environmental Development Using Computer Science (ICECS’24)
|
|
|---|---|---|
| Article Number | 02019 | |
| Number of page(s) | 8 | |
| Section | Smart Systems for Environmental Development | |
| DOI | https://doi.org/10.1051/e3sconf/202449102019 | |
| Published online | 21 February 2024 | |
- A. Bolhari, A. Rezaeian, J. Bolhari, S. Bairamzadeh, International Journal of Information and Electronics Engineering, 2, 5, (2012) [Google Scholar]
- B. Padmaja, V.V.R. Prasad, K.V.N. Sunitha, International Journal of Machine Learning and Computing, 8, 1, (2018) [Google Scholar]
- C. M. Duran-Acevedo, J. K. Carrillo-Gomez, C. A. Albarracin-Rojas, Multidisciplinary Digital Publishing Institute, (2021) [Google Scholar]
- F.S. Lopez, N. Condori-Fernández, A. Catalá, Information Management and Big Data. SIMBig 2018. Communications in Computer and Information Science, Springer, Cham, 898, 273, (2019) [Google Scholar]
- H. Gjoreski, S. Kozina, M. Gams, M. Luštrek, Á. García, J.H. Hong, J. Ramos, A.K. Dey, M. Bocca, N. Patwari, IEEE Pervasive Computing, 14, 70 (2015) [Google Scholar]
- J.-H. Kim et al., Journal on Health, 6, 2014 [Google Scholar]
- L. Vanitha, G. R. Suresh, Hierarchical SVM to detect mental stress in human beings using heart rate variability, in Proceedings of the 2nd International Conference on Devices, Circuits and Systems (ICDCS), 1 (2014) [Google Scholar]
- M. Gjoreski et al., Continuous stress detection using a wrist device–In laboratory and real life, in Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, 1185 (2016) [Google Scholar]
- SP. Kostopoulos, A. I. Kyritsis, M. Deriaz, D. Konstantas, Stress detection using smart phone data, in Proceedings of the eHealth 3600 International Summit on eHealth, Budapest, Hungary, 14-16 June, 340 (2016) [Google Scholar]
- S. M. Sincero, Physiological Stress Response (2023) from Explorable.com: https://explorable.com/physiological-stress-response [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.