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Super-Resolution Convolutional Network for Image Quality Enhancement in Remote Photoplethysmography Based Heart Rate Estimation

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Computational Science – ICCS 2022 (ICCS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13352))

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Abstract

Heart rate (HR) is one of the important vital parameters of the human body and understanding this vital sign provides key insights into human wellness. Imaging photoplethysmography (iPPG) allows HR detection from video recordings and its unbeatable compliance over the state of art methods has made much attention among researchers. Since it is a camera-based technique, measurement accuracy depends on the quality of input images. In this paper, we present a pipeline for efficient measurement of HR that includes a learning-based super-resolution preprocessing step. This preprocessing image enhancement step has shown promising results on low-resolution input images and works better on iPPG algorithms. The experimental results verified the reliability of this method.

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Authors and Affiliations

  1. Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, India

    K. Smera Premkumar & D. Jude Hemanth

  2. School of Computer Science and Engineering, University of Westminster, London, UK

    A. Angelopoulou & T. Chaussalet

  3. School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield, UK

    E. Kapetanios

Authors
  1. K. Smera Premkumar
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  2. A. Angelopoulou
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  3. E. Kapetanios
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  4. T. Chaussalet
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  5. D. Jude Hemanth
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Corresponding author

Correspondence to D. Jude Hemanth .

Editor information

Editors and Affiliations

  1. Brunel University London, London, UK

    Derek Groen

  2. University of Amsterdam, Amsterdam, The Netherlands

    Clélia de Mulatier

  3. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  4. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  5. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  6. University of Amsterdam, Amsterdam, The Netherlands

    Peter M. A. Sloot

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Premkumar, K.S., Angelopoulou, A., Kapetanios, E., Chaussalet, T., Hemanth, D.J. (2022). Super-Resolution Convolutional Network for Image Quality Enhancement in Remote Photoplethysmography Based Heart Rate Estimation. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13352. Springer, Cham. https://doi.org/10.1007/978-3-031-08757-8_15

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  • DOI: https://doi.org/10.1007/978-3-031-08757-8_15

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  • Online ISBN: 978-3-031-08757-8

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