A Brief Review on Gender Identification with Electrocardiography Data
Journal
Applied System Innovation
Date Issued
2022-08-16
Author(s)
Bastos, Eduarda Sofia
Duarte, Rui Pedro
Marinho, Francisco Alexandre
Rudenko, Roman
Vitaliyivna Denysyuk, Hanna
Gonçalves, Norberto Jorge
Albuquerque, Carlos
M Garcia, Nuno
Pires, Ivan Miguel
Abstract
Cardiac diseases have increased over the years; thus, it is essential to predict their possible
signs. Accurate prediction efficiently treats the patient’s medical history before the attack occurs.
Sensors available in commonly used devices may strive for the proper and early identification of
various cardiac diseases. The primary purpose of this review is to analyze studies related to gender
discretization based on data from different sensors including electrocardiography and echocardiography. The analyzed studies were published between 2010 and 2022 in various scientific databases,
including PubMed Central, Springer, ACM, IEEE Xplore, MDPI, and Elsevier, based on the analysis
of different cardiovascular diseases. It was possible to verify that most of the analyzed studies
measured similar parameters as traditional methods including the QRS complex and other waves
that characterize the various individuals.
signs. Accurate prediction efficiently treats the patient’s medical history before the attack occurs.
Sensors available in commonly used devices may strive for the proper and early identification of
various cardiac diseases. The primary purpose of this review is to analyze studies related to gender
discretization based on data from different sensors including electrocardiography and echocardiography. The analyzed studies were published between 2010 and 2022 in various scientific databases,
including PubMed Central, Springer, ACM, IEEE Xplore, MDPI, and Elsevier, based on the analysis
of different cardiovascular diseases. It was possible to verify that most of the analyzed studies
measured similar parameters as traditional methods including the QRS complex and other waves
that characterize the various individuals.
Subjects
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