A. Arivarasi, D. Thiripurasundari, A. Selvakumar, B. Kumaar, T. Aghil, S. Rahul, R. Kannan
{"title":"An advanced cost-efficient IoT method for stroke rehabilitation using smart gloves","authors":"A. Arivarasi, D. Thiripurasundari, A. Selvakumar, B. Kumaar, T. Aghil, S. Rahul, R. Kannan","doi":"10.1063/10.0020290","DOIUrl":null,"url":null,"abstract":"Stroke represents a severe, widespread, and widely acknowledged health crisis on both national and international levels. It is one of the most prevalent life-threatening conditions. Despite impressive advances in treating stroke, in addition to a need for effective patient care services, many sufferers still rely solely on physical interventions. The present paper describes and explains the use of a newly designed gadget for stroke survivors who cannot move their fingers. This is a sophisticated mobile device that enables stroke patients to regain their muscle memory and thus their ability to perform repetitive actions by continuing to tighten and stretch their muscles without the intervention of a physiotherapist. Gamification methodology is used to encourage patients to become involved in the process of rehabilitation. The device also has sensors that take information and transmit it to an app through an ESP32 connection. This enables physicians to view glove usage information remotely and keep track of an individual patient’s health. Communication between app and glove is facilitated by a broker in the Amazon Web Service IoT. With the robotic glove presented here, the recovery rate is found to be 90.23% over four weeks’ duration, which represents a significant improvement compared with existing hospital-based rehabilitation techniques.","PeriodicalId":35428,"journal":{"name":"Nami Jishu yu Jingmi Gongcheng/Nanotechnology and Precision Engineering","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nami Jishu yu Jingmi Gongcheng/Nanotechnology and Precision Engineering","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.1063/10.0020290","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Stroke represents a severe, widespread, and widely acknowledged health crisis on both national and international levels. It is one of the most prevalent life-threatening conditions. Despite impressive advances in treating stroke, in addition to a need for effective patient care services, many sufferers still rely solely on physical interventions. The present paper describes and explains the use of a newly designed gadget for stroke survivors who cannot move their fingers. This is a sophisticated mobile device that enables stroke patients to regain their muscle memory and thus their ability to perform repetitive actions by continuing to tighten and stretch their muscles without the intervention of a physiotherapist. Gamification methodology is used to encourage patients to become involved in the process of rehabilitation. The device also has sensors that take information and transmit it to an app through an ESP32 connection. This enables physicians to view glove usage information remotely and keep track of an individual patient’s health. Communication between app and glove is facilitated by a broker in the Amazon Web Service IoT. With the robotic glove presented here, the recovery rate is found to be 90.23% over four weeks’ duration, which represents a significant improvement compared with existing hospital-based rehabilitation techniques.