Cloud-based non-invasive cognitive breath monitoring system for patients in health-care system-Reference-Cited by-同舟云学术

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Cloud-based non-invasive cognitive breath monitoring system for patients in health-care system

Published:2023-10-05 Issue: Volume: Page:
ISSN:2364-415X
Container-title:International Journal of Data Science and Analytics
language:en
Short-container-title:Int J Data Sci Anal

Author:

Soni Mukesh,Shabaz Mohammad,Maaliw Renato R.,Keshta Ismail,Altaee Rasool,Das Sanju

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Theory and Mathematics,Computer Science Applications,Modeling and Simulation,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41060-023-00461-1.pdf

Reference27 articles.

1. Penzel, T., Glos, M., Fietze, I., Herberger, S., Pillar, G.: Distinguish Obstructive and central sleep apnea by portable peripheral arterial tonometry. In: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), , pp. 2780–2783, (2020) https://doi.org/10.1109/EMBC44109.2020.9175700

2. Pitkänen, H., et al.: Gamma power of electroencephalogram arousal is modulated by respiratory event type and severity in obstructive sleep apnea. IEEE Trans. Biomed. Eng. 69(4), 1417–1423 (2022). https://doi.org/10.1109/TBME.2021.3118229

3. Nikkonen, S., et al.: Automatic respiratory event scoring in obstructive sleep apnea using a long short-term memory neural network. IEEE J. Biomed. Health Inform. 25(8), 2917–2927 (2021). https://doi.org/10.1109/JBHI.2021.3064694

4. Ferrer-Lluis, Y., Castillo-Escario, M., Glos, I.F., Penzel, T., Jané, R.: Sleep apnea & chronic obstructive pulmonary disease: overlap syndrome dynamics in patients from an epidemiological study. In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5574–5577 (2021) https://doi.org/10.1109/EMBC46164.2021.9630515.

5. Nakari, E.K., Tajima, Y., Takadama, K.: Non-contact sleep apnea syndrome detection based on what random forests learned. In: 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech), pp. 240–244 (2020) https://doi.org/10.1109/LifeTech48969.2020.1570619209.

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