{"title":"Smart Life Saver Jacket: A New Jacket to Support CPR Operation","authors":"Thayita Chantarutai, Piyachat Klinthai, Pimpakarn A-masiri, Chutisant Kerdvibulvech","doi":"10.1007/s41133-024-00080-w","DOIUrl":null,"url":null,"abstract":"<div><p>Cardiac arrest is common death these days. Most patients do not notice the symptoms before it happens. Death or severe consequence and be prevented if help and proper assistance can be reached within time. Since a cardiac arrest is prone to get higher continuously, some buildings have installed AED (automated external defibrillator) defibrillators. Therefore, patients can reach for help immediately. But the fact is that some of the helpers can reach a patient within time but they are not sure how to operate heart stimulation by AED or CPR (cardiopulmonary resuscitation) properly nor do they make a decision to push the patient’s chest. In Thailand, CPR training is just an option; it is not a compulsory lesson. Nevertheless, CPR trainees can obtain only the theoretical lesson; then, they do not know exactly how hard to push the patient’s chest. This leads to misoperation when they face the real incident. Another factor is when an incident occurs, helpers do not know how to contact emergency and do not know what important information they need to provide to medical support. In this paper, we develop a smart life saver jacket to support the helper in how perform accurate CPR by using machine learning technology to detect the patient’s pulse and support the helper to make decisions combined with an interface idea to indicate helper how to perform accurate CPR, while it is the application that will connect to the nearest hospital.</p></div>","PeriodicalId":100147,"journal":{"name":"Augmented Human Research","volume":"10 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Augmented Human Research","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s41133-024-00080-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Cardiac arrest is common death these days. Most patients do not notice the symptoms before it happens. Death or severe consequence and be prevented if help and proper assistance can be reached within time. Since a cardiac arrest is prone to get higher continuously, some buildings have installed AED (automated external defibrillator) defibrillators. Therefore, patients can reach for help immediately. But the fact is that some of the helpers can reach a patient within time but they are not sure how to operate heart stimulation by AED or CPR (cardiopulmonary resuscitation) properly nor do they make a decision to push the patient’s chest. In Thailand, CPR training is just an option; it is not a compulsory lesson. Nevertheless, CPR trainees can obtain only the theoretical lesson; then, they do not know exactly how hard to push the patient’s chest. This leads to misoperation when they face the real incident. Another factor is when an incident occurs, helpers do not know how to contact emergency and do not know what important information they need to provide to medical support. In this paper, we develop a smart life saver jacket to support the helper in how perform accurate CPR by using machine learning technology to detect the patient’s pulse and support the helper to make decisions combined with an interface idea to indicate helper how to perform accurate CPR, while it is the application that will connect to the nearest hospital.