B. Ramprasad, Hongkai Chen, A. Veith, K. Truong, E. D. Lara
{"title":"Pain-o-vision, effortless pain management","authors":"B. Ramprasad, Hongkai Chen, A. Veith, K. Truong, E. D. Lara","doi":"10.1145/3458864.3466907","DOIUrl":null,"url":null,"abstract":"Chronic pain is often an ongoing challenge for patients to track and collect data. Pain-O-Vision is a smartwatch enabled pain management system that uses computer vision to capture the details of painful events from the user. A natural reaction to pain is to clench ones fist. The embedded camera is used to capture different types of fist clenching, to represent different levels of pain. An initial prototype was built on an Android smartwatch that uses a cloud-based classification service to detect the fist clench gestures. Our results show that it is possible to map a fist clench to different levels of pain which allows the patient to record the intensity of a painful event without carrying a specialized pain management device.","PeriodicalId":153361,"journal":{"name":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3458864.3466907","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Chronic pain is often an ongoing challenge for patients to track and collect data. Pain-O-Vision is a smartwatch enabled pain management system that uses computer vision to capture the details of painful events from the user. A natural reaction to pain is to clench ones fist. The embedded camera is used to capture different types of fist clenching, to represent different levels of pain. An initial prototype was built on an Android smartwatch that uses a cloud-based classification service to detect the fist clench gestures. Our results show that it is possible to map a fist clench to different levels of pain which allows the patient to record the intensity of a painful event without carrying a specialized pain management device.
慢性疼痛往往是一个持续的挑战,患者跟踪和收集数据。pain - o - vision是一款支持智能手表的疼痛管理系统,它使用计算机视觉从用户那里捕捉疼痛事件的细节。对疼痛的自然反应是握紧拳头。嵌入式摄像头用于捕捉不同类型的握拳动作,以表示不同程度的疼痛。最初的原型是建立在Android智能手表上的,它使用基于云的分类服务来检测握拳的手势。我们的研究结果表明,握拳可以映射到不同程度的疼痛,这使得患者可以在不携带专门的疼痛管理设备的情况下记录疼痛事件的强度。