Helen Korving, Di Zhou, Huan Xiang, Paula Sterkenburg, Panos Markopoulos, Emilia Barakova
{"title":"Development of an AI-Enabled System for Pain Monitoring Using Skin Conductance Sensoring in Socks.","authors":"Helen Korving, Di Zhou, Huan Xiang, Paula Sterkenburg, Panos Markopoulos, Emilia Barakova","doi":"10.1142/S0129065722500472","DOIUrl":null,"url":null,"abstract":"<p><p><i>Background</i>: Where self-report is unfeasible or observations are difficult, physiological estimates of pain are needed. <i>Methods</i>: 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. <i>Results</i>: The initial low precision and F1-score of the pain classification algorithm were resolved by interpolating a percentage of similar data. <i>Discussion</i>: 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.</p>","PeriodicalId":50305,"journal":{"name":"International Journal of Neural Systems","volume":"32 10","pages":"2250047"},"PeriodicalIF":6.6000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Neural Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1142/S0129065722500472","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/9/9 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 3
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.
期刊介绍：
The International Journal of Neural Systems is a monthly, rigorously peer-reviewed transdisciplinary journal focusing on information processing in both natural and artificial neural systems. Special interests include machine learning, computational neuroscience and neurology. The journal prioritizes innovative, high-impact articles spanning multiple fields, including neurosciences and computer science and engineering. It adopts an open-minded approach to this multidisciplinary field, serving as a platform for novel ideas and enhanced understanding of collective and cooperative phenomena in computationally capable systems.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
