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IoT-Based Continuous Bedside Monitoring Systems

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Advances in Big Data and Cloud Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 750))

Abstract

Oxygen saturation is an important parameter for people with breathing and heart problems to monitor their oxygen levels. The method proposed here uses pulse oximeter sensor to measure SpO2 (oxygen saturation). In this, two LEDs (Red and IR) with different wavelengths are used to obtain the signal from finger. Noninvasive system permits pain-free continuous monitoring of patient with minimum risk of infection. The oxygen saturation (SpO2) in blood is obtained and it is transmitted wirelessly through Bluetooth and further, these data can be given to the doctor through cloud. Noninvasively obtained SpO2 is compared with the standard device values. This measurement can provide early warning to potential problems that your body may potentially be facing.

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Acknowledgements

The authors are grateful to Karunya Institute of Technology and Sciences for providing needful facilities to do the experiment.

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Authors and Affiliations

  1. Electronics and Instrumentation Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India

    G. R. Ashisha, X. Anitha Mary, K. Rajasekaran & R. Jegan

Authors
  1. G. R. Ashisha
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  2. X. Anitha Mary
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  3. K. Rajasekaran
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  4. R. Jegan
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Corresponding author

Correspondence to G. R. Ashisha .

Editor information

Editors and Affiliations

  1. Department of Computer Sciences Technology, Karunya Institute of Technology & Sciences, Coimbatore, Tamil Nadu, India

    J. Dinesh Peter

  2. Department of Civil and Environmental Engineering, University of Missouri, Columbia, MO, USA

    Amir H. Alavi

  3. School of Computing, Engineering and Mathematics, University of Western Sydney, Sydney, NSW, Australia

    Bahman Javadi

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Ashisha, G.R., Anitha Mary, X., Rajasekaran, K., Jegan, R. (2019). IoT-Based Continuous Bedside Monitoring Systems. In: Peter, J., Alavi, A., Javadi, B. (eds) Advances in Big Data and Cloud Computing. Advances in Intelligent Systems and Computing, vol 750. Springer, Singapore. https://doi.org/10.1007/978-981-13-1882-5_34

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