文章基本信息

标题：An Energy Efficient Wearable Smart IoT System to Predict Cardiac Arrest
本地全文：下载
作者：AKM Jahangir Alam Majumder ; AKM Jahangir Alam Majumder ; Yosuf Amr ElSaadany 等
期刊名称：Advances in Human-Computer Interaction
印刷版ISSN：1687-5893
电子版ISSN：1687-5907
出版年度：2019
卷号：2019
DOI：10.1155/2019/1507465
出版社：Hindawi Publishing Corporation
摘要：Recently, many people have become more concerned about having a sudden cardiac arrest. With the increase in popularity of smart wearable devices, an opportunity to provide an Internet of Things (IoT) solution has become more available. Unfortunately, out of hospital survival rates are low for people suffering from sudden cardiac arrests. The objective of this research is to present a multisensory system using a smart IoT system that can collect Body Area Sensor (BAS) data to provide early warning of an impending cardiac arrest. The goal is to design and develop an integrated smart IoT system with a low power communication module to discreetly collect heart rates and body temperatures using a smartphone without it impeding on everyday life. This research introduces the use of signal processing and machine-learning techniques for sensor data analytics to identify predict and/or sudden cardiac arrests with a high accuracy.