A Brief Review on Gender Identification with Electrocardiography Data
; Bastos, E.
; Duarte, R.
; Marinho, F.
; Rudenko, R.
; Gonçalves, N.
; Zdravevski, E.
; Albuquerque, C.
Garcia, N. M.
Applied System Innovation Vol. 5, Nº 4, pp. 81 - 81, August, 2022.
ISSN (print): 2571-5577
Scimago Journal Ranking: 0,63 (in 2022)
Digital Object Identifier: 10.3390/asi5040081
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.