首页> 外文期刊>Journal of ambient intelligence and humanized computing >Real-time smart monitoring system for atrial fibrillation pathology
【24h】

Real-time smart monitoring system for atrial fibrillation pathology

机译:真正智能监控系统进行心房颤动病理学

获取原文
获取原文并翻译 | 示例

摘要

Atrial Fibrillation (AF) is a common cardiac pathology and, due to its unpredictability, it sometimes remains not detected. Aim of this work is to present a new version of the already published eHealth system, that includes a new real-time Android application for AF detection and monitoring. The proposed eHealth system is composed of a commercial wearable sensor device (Bioharness 3.0 by Zephyr) for cardiac monitoring and a specially developed Android smartphone application. This application is able to real-time processing the raw data sensed from the wearable sensor, providing stress detection, calories consumption estimation, sinus arrhythmia detection, sinus rhythm classification, and apnea detection. As novelty, the new smartphone application also implemented a SVM-based algorithm designed to detect AF episodes by handling electrocardiogram and the heart-rate sequence of the subjects. The performance of the new SVM-based algorithm implemented in eHealth was tested on AF recordings and evaluated in term of sensitivity and specificity. The results show a sensitivity of 78% and a specificity of 66%, making this version of eHealth system suitable for real-time monitoring of AF events.
机译:心房颤动(AF)是一种常见的心脏病学,并且由于其不可预测性,它有时仍未检测到。这项工作的目的是展示新版本的已发布的电子医疗系统,其中包括用于AF检测和监控的新实时Android应用程序。拟议的电子健康系统由商业可穿戴传感器设备(BioHarness 3.0由Zephyr)组成,用于心脏监控,专门开发的Android智能手机应用。该应用能够实时处理从可穿戴传感器感测的原始数据,提供应力检测,卡路里消耗估计,窦性能检测,窦性心律分类和呼吸暂停检测。作为新颖性,新的智能手机应用还实现了一种基于SVM的算法,该算法设计用于通过处理心电图和受试者的心率序列来检测AF剧集。在EHEALTE中实现的新SVM的算法的性能在AF录像上进行了测试,并在敏感度和特异性方面进行评估。结果显示敏感性为78%,特异性为66%,这是适合对AF事件的实时监控的eHealth系统的eHealth系统。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号