PAIN RECOGNITION WITH PHYSIOLOGICAL SIGNALS USING MULTILEVEL CONTEXT INFORMATION

Authors

  • Dr.SIVANAGI REDDY KALLI, NELLUTLA RAVIPRAKHYA, DASARI RUPANJALI, GOMASA VASUNDARA

Keywords:

Pain recognition, physiological signals, multilevel context information, machine learning, emotional states, electrodermal activity (EDA), heart rate, real-time monitoring, individualized pain detection, non invasive monitoring, healthcare, context-aware systems.

Abstract

Pain recognition using physiologicalsignals is a challenging yet essentialtask in the medical field, withapplications ranging from clinical painassessment to real-time monitoring ofpatients in critical care. The recognitionof pain through physiological signals,

References

• Gauthier, M., et al. (2015). Heart rate variability and pain assessment: A clinical study. Journal of Pain Research.

• Gogarten, W., et al. (2014). The role of electrodermal activity in pain recognition. Journal of Neuroscience Methods.

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Published

2024-04-10

How to Cite

Dr.SIVANAGI REDDY KALLI, NELLUTLA RAVIPRAKHYA, DASARI RUPANJALI, GOMASA VASUNDARA. (2024). PAIN RECOGNITION WITH PHYSIOLOGICAL SIGNALS USING MULTILEVEL CONTEXT INFORMATION. Journal of Computational Analysis and Applications (JoCAAA), 33(4), 764–771. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2493

Issue

Vol. 33 No. 4 (2024): Selected Papers on Computational Techniques Across Multidisciplinary Fields: Innovations and Applications

Section

Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.