健康受试者心电图用药情况调查

V. Vijean, Abdul Ghapar Ahmad, Syakirah Afiza Mohammed, Razi Ahmad, Wan Amiza Amneera Wan Ahmad, R. Santiagoo, L. C. Chin
{"title":"健康受试者心电图用药情况调查","authors":"V. Vijean, Abdul Ghapar Ahmad, Syakirah Afiza Mohammed, Razi Ahmad, Wan Amiza Amneera Wan Ahmad, R. Santiagoo, L. C. Chin","doi":"10.1109/AIST55798.2022.10064840","DOIUrl":null,"url":null,"abstract":"Heart diseases are now the leading cause of death worldwide, it is estimated that around 7 million patients who are living in developed countries, lost their lives due to diseases related to their cardiovascular system. In Malaysia, cardiovascular diseases represents one fifth of total deaths in the country in the past three decades. Currently patients need some sort of drugs that help them to stabilize and restore the regular patterns of their heart beat because if the patients cannot manage to restore the normal heart beat pattern, the undesired heart condition could lead life threatening situations. Advancement of biotechnology has enabled the creation of new medicated drugs to provide better treatment options. However, when this treatment option fails and there is a need to provide emergency intervention to the patients in hospitals, the medical experts often need to know about the patients’ intake of any medications prior to hospital admittance for providing suitable treatments. Sometimes, this would be a difficult task as the patient might be admitted in semi-conscious or unconscious state. Therefore, this study focusses on identification of different medicated drugs usage through analysis of ECG data of the users. The data for the experiment was obtained from physionet library, which provides ECG data of subjects administered with a combination of Dofetilide, Mexiletine, lidocaine, Moxifloxacin and Diltiazem medicated drugs. The use of morphological and non-linear features derived from the ECG signals were able to provide prediction accuracy of 77.26% using SVM classifier.","PeriodicalId":360351,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigation on Medicated Drugs in ECG of Healthy Subjects\",\"authors\":\"V. Vijean, Abdul Ghapar Ahmad, Syakirah Afiza Mohammed, Razi Ahmad, Wan Amiza Amneera Wan Ahmad, R. Santiagoo, L. C. Chin\",\"doi\":\"10.1109/AIST55798.2022.10064840\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Heart diseases are now the leading cause of death worldwide, it is estimated that around 7 million patients who are living in developed countries, lost their lives due to diseases related to their cardiovascular system. In Malaysia, cardiovascular diseases represents one fifth of total deaths in the country in the past three decades. Currently patients need some sort of drugs that help them to stabilize and restore the regular patterns of their heart beat because if the patients cannot manage to restore the normal heart beat pattern, the undesired heart condition could lead life threatening situations. Advancement of biotechnology has enabled the creation of new medicated drugs to provide better treatment options. However, when this treatment option fails and there is a need to provide emergency intervention to the patients in hospitals, the medical experts often need to know about the patients’ intake of any medications prior to hospital admittance for providing suitable treatments. Sometimes, this would be a difficult task as the patient might be admitted in semi-conscious or unconscious state. Therefore, this study focusses on identification of different medicated drugs usage through analysis of ECG data of the users. The data for the experiment was obtained from physionet library, which provides ECG data of subjects administered with a combination of Dofetilide, Mexiletine, lidocaine, Moxifloxacin and Diltiazem medicated drugs. The use of morphological and non-linear features derived from the ECG signals were able to provide prediction accuracy of 77.26% using SVM classifier.\",\"PeriodicalId\":360351,\"journal\":{\"name\":\"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIST55798.2022.10064840\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIST55798.2022.10064840","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

心脏病现在是世界范围内死亡的主要原因,据估计,生活在发达国家的约700万患者因心血管系统相关疾病而丧生。在马来西亚,心血管疾病在过去三十年中占该国总死亡人数的五分之一。目前,患者需要某种药物来帮助他们稳定和恢复正常的心跳模式,因为如果患者不能设法恢复正常的心跳模式,不希望出现的心脏病可能会导致危及生命的情况。生物技术的进步使人们能够创造新的药物,提供更好的治疗选择。然而,当这种治疗方案失败,需要向医院的患者提供紧急干预时,医学专家通常需要在入院前了解患者的任何药物摄入情况,以便提供适当的治疗。有时,这将是一项艰巨的任务,因为患者可能处于半意识或无意识状态。因此,本研究的重点是通过分析使用者的心电数据来识别不同的用药情况。实验数据来自physionet数据库,该数据库提供了联合使用多非利特、美西汀、利多卡因、莫西沙星和地尔硫卓药物的受试者的心电图数据。利用心电信号的形态特征和非线性特征,SVM分类器的预测准确率达到77.26%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation on Medicated Drugs in ECG of Healthy Subjects
Heart diseases are now the leading cause of death worldwide, it is estimated that around 7 million patients who are living in developed countries, lost their lives due to diseases related to their cardiovascular system. In Malaysia, cardiovascular diseases represents one fifth of total deaths in the country in the past three decades. Currently patients need some sort of drugs that help them to stabilize and restore the regular patterns of their heart beat because if the patients cannot manage to restore the normal heart beat pattern, the undesired heart condition could lead life threatening situations. Advancement of biotechnology has enabled the creation of new medicated drugs to provide better treatment options. However, when this treatment option fails and there is a need to provide emergency intervention to the patients in hospitals, the medical experts often need to know about the patients’ intake of any medications prior to hospital admittance for providing suitable treatments. Sometimes, this would be a difficult task as the patient might be admitted in semi-conscious or unconscious state. Therefore, this study focusses on identification of different medicated drugs usage through analysis of ECG data of the users. The data for the experiment was obtained from physionet library, which provides ECG data of subjects administered with a combination of Dofetilide, Mexiletine, lidocaine, Moxifloxacin and Diltiazem medicated drugs. The use of morphological and non-linear features derived from the ECG signals were able to provide prediction accuracy of 77.26% using SVM classifier.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信