Pain signaling with physiological data for persons with communication difficulties: A pilot study of the Pain App

Helen Korving; Peter Peters; Emilia Barakova; Loe Feijs; Paula Sterkenburg

doi:10.1109/CogInfoCom50765.2020.9237900

Pain signaling with physiological data for persons with communication difficulties: A pilot study of the Pain App

Helen Korving, Peter Peters, Emilia Barakova, Loe Feijs, Paula Sterkenburg

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Pain is a common occurrence in life. For some groups of people expressing, communicating, and seeking pain relief is not possible, due to age, illness, disability, or unconsciousness. To support caregivers, pain detection through physiological measures can be a solution. Currently, an algorithm for an application indicating arousal according to electrodermal changes has been developed and tested. Pain is unique to every person, so new research and algorithm development are necessary to assess which measurable signals coincide with pain. A mobile application utilising such algorithms would allow caregivers to better attend to the patients' needs in daily practice. This study aims to develop an application that can signal pain for caregivers of persons with communication difficulties and examine whether utilizing this software solution, pain can be reliably detected in an experimental setting. Visual analysis of plotted results from a pilot study indicates that within the same person pain shows significant deviation from relaxation and neutral experiences. Further research is needed to examine the reliability of pain detection.

Original language	English
Title of host publication	2020 11th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)
Subtitle of host publication	Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	61-66
Number of pages	6
ISBN (Electronic)	9781728182131
DOIs	https://doi.org/10.1109/CogInfoCom50765.2020.9237900
Publication status	Published - 2 Nov 2020
Event	11th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2020 - Virtual, Mariehamn, Finland Duration: 23 Sept 2020 → 25 Sept 2020

Conference

Conference	11th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2020
Country/Territory	Finland
City	Virtual, Mariehamn
Period	23/09/20 → 25/09/20

Keywords

Application software
Cognitive infocommunication
Mobile app
Pain
Physiological data
Skin conductance

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Korving, H., Peters, P., Barakova, E., Feijs, L., & Sterkenburg, P. (2020). Pain signaling with physiological data for persons with communication difficulties: A pilot study of the Pain App. In 2020 11th IEEE International Conference on Cognitive Infocommunications (CogInfoCom): Proceedings (pp. 61-66). [9237900] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CogInfoCom50765.2020.9237900

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abstract = "Pain is a common occurrence in life. For some groups of people expressing, communicating, and seeking pain relief is not possible, due to age, illness, disability, or unconsciousness. To support caregivers, pain detection through physiological measures can be a solution. Currently, an algorithm for an application indicating arousal according to electrodermal changes has been developed and tested. Pain is unique to every person, so new research and algorithm development are necessary to assess which measurable signals coincide with pain. A mobile application utilising such algorithms would allow caregivers to better attend to the patients' needs in daily practice. This study aims to develop an application that can signal pain for caregivers of persons with communication difficulties and examine whether utilizing this software solution, pain can be reliably detected in an experimental setting. Visual analysis of plotted results from a pilot study indicates that within the same person pain shows significant deviation from relaxation and neutral experiences. Further research is needed to examine the reliability of pain detection.",

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Korving, H, Peters, P, Barakova, E, Feijs, L & Sterkenburg, P 2020, Pain signaling with physiological data for persons with communication difficulties: A pilot study of the Pain App. in 2020 11th IEEE International Conference on Cognitive Infocommunications (CogInfoCom): Proceedings., 9237900, Institute of Electrical and Electronics Engineers Inc., pp. 61-66, 11th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2020, Virtual, Mariehamn, Finland, 23/09/20. https://doi.org/10.1109/CogInfoCom50765.2020.9237900

Pain signaling with physiological data for persons with communication difficulties : A pilot study of the Pain App. / Korving, Helen; Peters, Peter; Barakova, Emilia et al.

2020 11th IEEE International Conference on Cognitive Infocommunications (CogInfoCom): Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. p. 61-66 9237900.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Korving H, Peters P, Barakova E, Feijs L, Sterkenburg P. Pain signaling with physiological data for persons with communication difficulties: A pilot study of the Pain App. In 2020 11th IEEE International Conference on Cognitive Infocommunications (CogInfoCom): Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. p. 61-66. 9237900 doi: 10.1109/CogInfoCom50765.2020.9237900

Pain signaling with physiological data for persons with communication difficulties: A pilot study of the Pain App

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