Development of an AI-Enabled System for Pain Monitoring Using Skin Conductance Sensoring in Socks
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Published on: July 22, 2022
Helen Korving1,2, Di Zhou3, Huan Xiang4
1Department of Child and Family Studies, Vrije Universiteit Amsterdam, Van der Boechorststraat, 7, Amsterdam, 1081 BT, The Netherlands.
Abstract:
Background: Where self-report is unfeasible or observations are difficult, physiological estimates of pain are needed. Methods: 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. Results: The initial low precision and F1-score of the pain classification algorithm were resolved by interpolating a percentage of similar data. Discussion: 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.
