Open Access
Issue
E3S Web Conf.
Volume 229, 2021
The 3rd International Conference of Computer Science and Renewable Energies (ICCSRE’2020)
Article Number 01030
Number of page(s) 6
DOI https://doi.org/10.1051/e3sconf/202122901030
Published online 25 January 2021
  1. R. B. Duffey and E. Zio, “Analysing Recovery From Pandemics by Learning Theory: The Case of CoVid19, ” in IEEE Access, Vol. 8, pp. 110789-110795, 2020. [CrossRef] [Google Scholar]
  2. J. Zhang et al., “Navigating the Pandemic Response Life Cycle: Molecular Diagnostics and Immunoassays in the Context of COVID-19 Management, ” in IEEE Reviews in Biomedical Engineering. [Google Scholar]
  3. V. Chamola, V. Hassija, V. Gupta and M. Guizani, “A Comprehensive Review of the COVID-19 Pandemic and the Role of IoT, Drones, AI, Blockchain, and 5G in Managing its Impact, ” in IEEE Access, Vol. 8, pp. 90225-90265. [CrossRef] [Google Scholar]
  4. X. Ding et al., “Wearable Sensing and Telehealth Technology with Potential Applications in the Coronavirus Pandemic, ” in IEEE Reviews in Biomedical Engineering. [Google Scholar]
  5. R. B. Duffey and E. Zio, “Analyzing Recovery From Pandemics by Learning Theory: The Case of CoVid19, ” in IEEE Access, Vol. 8, pp. 110789-110795, 2020. [CrossRef] [Google Scholar]
  6. B. Hu, S. Wei, D. Wei, L. Zhao, G. Zhu and C. Liu, “Multiple Time Scales Analysis for Identifying Congestive Heart Failure Based on Heart Rate Variability, ” in IEEE Access, Vol. 7, pp. 17862-17871, 2019. [CrossRef] [Google Scholar]
  7. D. Biswas, N. Simões-Capela, C. Van Hoof and N. Van Helleputte, “Heart Rate Estimation From Wrist-Worn Photoplethysmography: A Review, ” in IEEE Sensors Journal, Vol. 19, no. 16, pp. 6560-6570, 15 Aug. 15, 2019. [CrossRef] [Google Scholar]
  8. V. L. Petrović, M. M. Janković, A. V. Lupšić, V. R. Mihajlović and J. S. Popović-Božović, “High-Accuracy Real-Time Monitoring of Heart Rate Variability Using 24 GHz Continu-ous-Wave Doppler Radar, ” in IEEE Access, Vol. 7, pp. 74721-74733, 2019. [CrossRef] [Google Scholar]
  9. S. Kontaxis et al., “ECG-Derived Respiratory Rate in Atrial Fibrillation, ” in IEEE Transac-tions on Biomedical Engineering, Vol. 67, no. 3, pp. 905-914, March 2020 [CrossRef] [Google Scholar]
  10. C. Uysal and T. Filik, “RF-Based Noncontact Respiratory Rate Monitoring With Parametric Spectral Estimation, ” in IEEE Sensors Journal, Vol. 19, no. 21, pp. 9841-9849, 1 Nov.1, 2019. [CrossRef] [Google Scholar]
  11. Hertzman, A.B. Observations on the finger volume pulse recorded photoelectrically. Am. J. Physiol. 1937, 119, 334–335. [Google Scholar]
  12. Wang, W.; den Brinker, A.C.; Stuijk, S.; de Haan, G. Algorithmic principles of remote PPG. IEEE Trans. Biomed. Eng. 2017, 64, 1479–1491. [CrossRef] [Google Scholar]
  13. S. Sanyal and K. K. Nundy, “Algorithms for Monitoring Heart Rate and Respiratory Rate From the Video of a User’s Face, ” in IEEE Journal of Translational Engineering in Health and Medicine, Vol. 6, pp. 1-11, 2018, Art no. 2700111. [CrossRef] [Google Scholar]
  14. Khanam, F.T.Z.; Al-Naji, A.; Chahl, J. Remote Monitoring of Vital Signs in Diverse Non-Clinical and Clinical Scenarios Using Computer Vision Systems: A Review. Appl. Sci. 2019, 9, 4474. [CrossRef] [Google Scholar]
  15. Dalal, H.; Basu, A.; Abegaonkar, M.P. Remote sensing of vital sign of human body with radio frequency. CSI Trans. ICT 2017, 5, 161–166. [CrossRef] [Google Scholar]
  16. Ghafouri-Shiraz, H. Ultra-wide patch antenna array design at 60 GHz band for remote vital sign monitoring with Doppler radar principle. J. Infrared Millim. Terahertz Waves 2017, 38, 548–566. [CrossRef] [Google Scholar]
  17. Yang, M.; Liu, Q.; Turner, T.; Wu, Y. Vital sign estimation from passive thermal video. In Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, AK, USA, 23–28 June 2008; pp. 1–8. [Google Scholar]
  18. Bennett, S.; El Harake, T.N.; Goubran, R.; Knoefel, F. Adaptive Eulerian Video Processing of Thermal Video: An Experimental Analysis. IEEE Trans. Instrum. Meas. 2017, 66, 2516–2524. [CrossRef] [Google Scholar]
  19. Nakajima, K.; Osa, A.; Miike, H. A method for measuring respiration and physical activity in bed by optical flow analysis. In Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. ‘Magnificent Milestones and Emerging Opportunities in Medical Engineering’ (Cat. No. 97CH36136), Chicago, IL, USA, 30 October–2November 1997; pp. 2054–2057. 50. [Google Scholar]
  20. Frigola, M.; Amat, J.; Pagès, J. Vision based respiratory monitoring system. In Proceedings of the 10th Mediterranean Conference on Control and Automation (MED 2002), Lisbon, Portugal, 9–12 July 2002; pp. 9–13. [Google Scholar]
  21. Al-Naji, A.; Chahl, J. Remote respiratory monitoring system based on developing motion magnification technique. Biomed. Signal Process. Control 2016, 29, 1–10. [CrossRef] [Google Scholar]
  22. Latif Rachid, Saddik Amine, “Embedded Implementation of Biomedical Applications in Het-erogeneous Systems”, Biomedical Spectroscopy and Imaging, Vol. 8, no. 3-4, pp. 73-80, 2019. [CrossRef] [Google Scholar]
  23. R. Latif, A. Saddik, A. Elouardi, “Evaluation of Agricultural Precision Algorithms on UAV Images, ” 2019 International Conference of Computer Science and Renewable Energies (ICCSRE), Agadir, Morocco, 2019, pp. 1-4, doi: 10.1109/ICCSRE.2019.8807604 [Google Scholar]
  24. Guanghao Sun, Yosuke Nakayama, Sumiyakhand Dagdanpurev, Shigeto Abe, Hidekazu Nishimura, Tetsuo Kirimoto, Takemi Matsui, “Remote sensing of multiple vital signs using a CMOS camera-equipped infrared thermography system and its clinical application in rapidly screening patients with suspected infectious diseases”, International Journal of Infectious Diseases, Vol. 55, 2017, pp. 113-117. [CrossRef] [Google Scholar]
  25. Mayank Kumar, Ashok Veeraraghavan, and Ashutosh Sabharwal, “DistancePPG: Robust non-contact vital signs monitoring using a camera, ” Biomed. Opt. Express 6, 1565-1588 (2015). [CrossRef] [PubMed] [Google Scholar]
  26. R. Latif, F. Z. Guerrouj, A. Saddik and O. El B’Charri, “ECG signal compression based on ASCII coding using CUDA architecture, ” 2019 4th World Conference on Complex Systems (WCCS), Ouarzazate, Morocco, 2019, pp. 1-6, doi: 10.1109/ICoCS.2019.8930744. [Google Scholar]

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