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Head Pose and Biomedical Signals Analysis in Pain Level Recognition

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Information Technology in Biomedicine (ITIB 2022)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1429))

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Abstract

Pain feeling assessment is crucial for a safe and efficient course of physiotherapy. Especially onset of severe pain stands for specific tissue guard and protects it from damage. In this study, an approach for automatic pain level recognition is described. Biomedical signals (EMG, BVP, EDA) and video data of a head pose are analyzed in patients undergoing fascial therapy. The impact of video data and their fusion with biomedical data is tested for the system’s performance. Decision trees and random forest are applied for classification, yielding an accuracy of 0.85. The energy of the EMG signal turned out to be a highly discriminative feature that dominated the weak classifier. Video features impact the classification results in ensembled methods.

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Acknowledgement

This work was supported by the Polish-German grant in the field of DIGITIZATION of ECONOMY: ‘Multimodal Platform for Pain Monitoring in Physiotherapy’ (grant number WPN-3/1/2019).

Author information

Authors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, ul. Roosevelta 40, 41-800, Zabrze, Poland

    Maria Bieńkowska, Aleksandra Badura & Ewa Pietka

  2. Institute of Physiotheraphy and Health Science, Academy of Physical Education in Katowice, ul. Mikołowska 72a, 40-065, Katowice, Poland

    Andrzej Myśliwiec

Authors
  1. Maria Bieńkowska
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  2. Aleksandra Badura
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  3. Andrzej Myśliwiec
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  4. Ewa Pietka
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Corresponding author

Correspondence to Maria Bieńkowska .

Editor information

Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Ewa Pietka

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Pawel Badura

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Jacek Kawa

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Wojciech Wieclawek

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Bieńkowska, M., Badura, A., Myśliwiec, A., Pietka, E. (2022). Head Pose and Biomedical Signals Analysis in Pain Level Recognition. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2022. Advances in Intelligent Systems and Computing, vol 1429. Springer, Cham. https://doi.org/10.1007/978-3-031-09135-3_29

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