An Energy Efficient Wearable Smart IoT System to Predict Cardiac Arrest. (12th February 2019)

• Record Type: Journal Article
• Authors: Majumder, AKM Jahangir Alam; ElSaadany, Yosuf Amr; Young, Roger; Ucci, Donald R.
• Other Names: Rebaudengo Maurizio Guest Editor.
• Is Part Of: Advances in human-computer interaction. Volume 2019(2019)
• Publication Date: 2019-02-12
• Subjects: Human-computer interaction -- Periodicals; Human-computer interaction; Periodicals; Electronic journals; 004.019
• DOI: 10.1155/2019/1507465
• Languages: English
• ISSNs: 1687-5893

Abstract

Abstract : 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.