Review on Higher-Order Neural Units to Monitor Cardiac Arrhythmia Patterns

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F17%3A00315048" target="_blank" >RIV/68407700:21220/17:00315048 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.3233/978-1-61499-773-3-219" target="_blank" >http://dx.doi.org/10.3233/978-1-61499-773-3-219</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/978-1-61499-773-3-219" target="_blank" >10.3233/978-1-61499-773-3-219</a>

Result language

angličtina

Original language name

Review on Higher-Order Neural Units to Monitor Cardiac Arrhythmia Patterns

Original language description

An electrocardiogram (ECG) is a non-invasive technique that checks for problems with the electrical activity of a patient’s heart. ECG is economical and extremely versatile. Some of its characteristics make it a very useful tool to detect cardiac pathologies. The ECG records a series of characteristic waves called PQRST; however, the QRS complex analysis enables the detection of a type of arrhythmia in an ECG. Technological developments enable the storage of a large amount of data, from which knowledge extraction is impossible without a powerful data processing tool; in particular, an adequate signal processing tool, whose output provides reliable parameters as a basis to make a precise clinical diagnosis. Thus, ECG signal processing creates an opportunity to analyze and recognize possible arrhythmia patterns. This paper reviews the use of artificial neural networks (ANNs) to detect and recognize cardiac arrhythmia patterns. Recurrent neural networks (RNNs) and higher-order neural units are inspected. In addition, the potentials of using higher-order neural units such as the quadratic dynamic neural unit (D-QNU) and dynamic cubic neural unit (D-CNU) for cardiac arrhythmia detection are analyzed.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 8th International Conference on Applications of Digital Information and Web Technologies

ISBN

978-1-61499-772-6

ISSN

—

e-ISSN

—

Number of pages

13

Pages from-to

219-231

Publisher name

IOS Press BV

Place of publication

Amsterdam

Event location

Juarez City

Event date

Mar 29, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000440621900020