Multi-task Neural Networks for Pain Intensity Estimation using Electrocardiogram and Demographic Factors

Stefanos Gkikas, Chariklia Chatzaki, Manolis Tsiknakis
7/28/2024
cs.AIcs.CV

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Abstract

Pain is a complex phenomenon which is manifested and expressed by patients in various forms. The immediate and objective recognition of it is a great of importance in order to attain a reliable and unbiased healthcare system. In this work, we elaborate electrocardiography signals revealing the existence of variations in pain perception among different demographic groups. We exploit this insight by introducing a novel multi-task neural network for automatic pain estimation utilizing the age and the gender information of each individual, and show its advantages compared to other approaches.

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Cite this paper

@article{gkikas2024multitask,
  title  = {Multi-task Neural Networks for Pain Intensity Estimation using Electrocardiogram and Demographic Factors},
  author = {Stefanos Gkikas and Chariklia Chatzaki and Manolis Tsiknakis},
  year   = {2024},
  eprint = {2407.19475},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.19475v1}
}

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