Development of an AI-Enabled System for Pain Monitoring Using Skin Conductance Sensoring in Socks.

Journal: International journal of neural systems
Published Date: Sep 9, 2022

Abstract

: Where self-report is unfeasible or observations are difficult, physiological estimates of pain are needed. : Pain-data from 30 healthy adults were gathered to create a database of physiological pain responses. A model was then developed, to analyze pain-data and visualize the AI-estimated level of pain on a mobile app. : The initial low precision and F1-score of the pain classification algorithm were resolved by interpolating a percentage of similar data. : This system presents a novel approach to assess pain in noncommunicative people with the use of a sensor sock, AI predictor and mobile app. Performance analysis and the limitations of the AI algorithm are discussed.

Authors

  • Helen Korving
    Department of Child and Family Studies, Vrije Universiteit Amsterdam, Van der Boechorststraat, 7, Amsterdam, 1081 BT, The Netherlands.
  • Di Zhou
    Dazhou Industrial Technological Institute of Intelligent Manufacturing, Sichuan university of Arts and Science, Dazhou, China.
  • Huan Xiang
    School of Artificial Intelligence and Computer, Jiangnan University, 1800 Lihu Avenue, Wuxi, Jiangsu 214122, P. R. China.
  • Paula Sterkenburg
    Department of Child and Family Studies, Vrije Universiteit Amsterdam, Van der Boechorststraat, 7, Amsterdam, 1081 BT, The Netherlands.
  • Panos Markopoulos
    Department of Industrial Design, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.
  • Emilia Barakova
    Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, The Netherlands.

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