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Implementation of the Time Series and the Convolutional Vision Transformers for Biological Signal Processing - Blood Pressure Estimation from Photoplethysmogram

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ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data (ICT Innovations 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1991))

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Abstract

Blood pressure estimation is crucial for early detection and prevention of many cardiovascular diseases. This paper explores the potential of the relatively new transformer architecture for accomplishing this task in the domain of biological signal processing. Several preceding studies of blood pressure estimation solely for PPG signals have had success with CNN and LSTM neural networks. In this study two types of transformer variants are considered: the time series and the convolutional vision transformers. The results obtained from our research indicate that this type of approach may be unsuitable for the task. However, further research is needed to make a definitive claim, since only simple transformer type are considered.

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Acknowledgment

This paper has been written thanks to the support of the "Smart Patch for Life Support Systems" - NATO project G5825 SP4LIFE and by the National project IBS4LIFE of Faculty of Computer Science and Engineering, at Ss. Cyril and Methodius University in Skopje.

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Authors and Affiliations

  1. University Ss. Cyril and Methodius, Faculty of Computer Science and Engineering, Rugjer Boskovikj 16, 1000, Skopje, North Macedonia

    Ivan Kuzmanov, Nevena Ackovska & Ana Madevska Bogdanova

  2. Institute of Measurement Science, Slovak Academy of Sciences and Faculty of Informatics and Information Technologies, STU, Bratislava, Slovakia

    Fedor Lehocki

Authors
  1. Ivan Kuzmanov
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  2. Nevena Ackovska
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  3. Fedor Lehocki
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  4. Ana Madevska Bogdanova
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Corresponding author

Correspondence to Ana Madevska Bogdanova .

Editor information

Editors and Affiliations

  1. Ss. Cyril and Methodius University in Skopje, Skopje, North Macedonia

    Marija Mihova

  2. Ss. Cyril and Methodius University in Skopje, Skopje, North Macedonia

    Mile Jovanov

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Kuzmanov, I., Ackovska, N., Lehocki, F., Bogdanova, A.M. (2024). Implementation of the Time Series and the Convolutional Vision Transformers for Biological Signal Processing - Blood Pressure Estimation from Photoplethysmogram. In: Mihova, M., Jovanov, M. (eds) ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data. ICT Innovations 2023. Communications in Computer and Information Science, vol 1991. Springer, Cham. https://doi.org/10.1007/978-3-031-54321-0_4

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  • DOI: https://doi.org/10.1007/978-3-031-54321-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-54320-3

  • Online ISBN: 978-3-031-54321-0

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