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A Survey of Heart Anomaly Detection Using Ambulatory Electrocardiogram (ECG).
Li, Hong Zu; Boulanger, Pierre.
Afiliação
  • Li HZ; Computing Science Department, University of Alberta, Edmonton, AB T6G 2R3, Canada.
  • Boulanger P; Computing Science Department, University of Alberta, Edmonton, AB T6G 2R3, Canada.
Sensors (Basel) ; 20(5)2020 Mar 06.
Article em En | MEDLINE | ID: mdl-32155930
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inquéritos e Questionários / Eletrocardiografia Ambulatorial / Cardiopatias Congênitas Tipo de estudo: Diagnostic_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inquéritos e Questionários / Eletrocardiografia Ambulatorial / Cardiopatias Congênitas Tipo de estudo: Diagnostic_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article