A Survey of Heart Anomaly Detection Using Ambulatory Electrocardiogram (ECG)

Sensors
Hong Zu Li, Pierre Boulanger

Abstract

Cardiovascular diseases (CVDs) are the number one cause of death globally. An estimated 17.9 million people die from CVDs each year, representing 31% of all global deaths. Most cardiac patients require early detection and treatment. Therefore, many products to monitor patient's heart conditions have been introduced on the market. Most of these devices can record a patient's bio-metric signals both in resting and in exercising situations. However, reading the massive amount of raw electrocardiogram (ECG) signals from the sensors is very time-consuming. Automatic anomaly detection for the ECG signals could act as an assistant for doctors to diagnose a cardiac condition. This paper reviews the current state-of-the-art of this technology discusses the pros and cons of the devices and algorithms found in the literature and the possible research directions to develop the next generation of ambulatory monitoring systems.

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Citations

Sep 18, 2020·Biomedicine & Pharmacotherapy = Biomédecine & Pharmacothérapie·Ming-Zhu XiaoYuan-Yuan Cheng

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Methods Mentioned

BETA
feature extraction
PCA

Software Mentioned

Astroskin Smart Shirt
QardioMD
AliveCor
Omron HeartScan
Astroskin
ecgpuwave
PhysioNet
SEEHT

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