# A Brief Review on Gender Identification with Electrocardiography Data
## 4 Discussion and Conclusions  
This study verified that only a few studies available in the literature using electrocardiography sensors allow for the discretization of gender. However, these studies allowed us to identify which sensors can be used for gender identification with reliable accuracy. There are no previous literature reviews regarding gender identification, but gender can handle the creation of personalized solutions for cardiovascular patients by gender. This article performed a systematic review of the sensors and automated approaches to identifying the gender of the patients based on different parameters calculated by the sensors' signals and the diseases present in the population. Only thirteen studies were considered relevant per the inclusion criteria, which means this area may be an attractive field for future research. In line with this, this topic may be essential for facilitating the identification of diseases and their evolution. From the thirteen studies identified in this review, the main findings are as follows:  
* _(RQ1) Which methods can be used with ECG sensors for gender identification?_ The main methods used were multiple linear regression, the logistic regression model, classification and regression tree analysis, the linear regression model, spectrograms, scalograms, Rentrop classification, and attractor reconstruction;
* _(RQ2) Which features can be extracted from the ECG sensors for gender identification?_ The features extracted from the ECG sensors that can be used for gender identification were mainly the RR interval, the degree of ST-segment elevation, the ST-segment depression, the maximum QRS interval, the P-duration, the P-amplitude, the P-area, the P-terminal negative force, the PR-interval, the QT/QTc, and the slope of the QT-RR;* _(RQ3) What are the benefits of using ECG sensors for gender identification?_ The benefits of using ECG sensors are the possibility of analyzing the differences in the ECG waves of different genders and using this to study and treat heart diseases. The different treatments can be adapted by the different characteristics related to gender, and different treatments can be standardized by gender to promote the automation of the prescription of different medicines. There was a lack of studies related to gender identification. However, the sensors may increase the reliability of the measurements of the electrocardiogram's performance, and this empowers various diagnostics in health. This review allows for the verification that there are different characteristics of ECG signals that can allow for gender identification, opening the possibility for the creation of personalized medical solutions. In future work, we intend to use a labeled database [30] to implement different artificial intelligence methods for gender identification. This study will only be a preliminary study that needs to be validated with other labeled databases to create a reliable method for using ECG data for gender identification. Nevertheless, it can empower different types of patients and improve medical treatments. Conceptualization, methodology, software, validation, formal analysis, investigation, writing--original draft preparation, writing--review, and editing: E.S.B., R.P.D., F.A.M., R.R., H.V.D., N.J.G., E.Z., C.A., N.M.G. and I.M.P. All authors have read and agreed to the published version of the manuscript. This work was funded by FCT/MEC through national funds and cofunded by a FEDER--PT2020 partnership agreement under the project: UIDB/50008/2020. This work was also funded by the national funds through the FCT--Foundation for Science and Technology, I.P., within the scope of the project: UIDB/00742/2020. [PERSON] is funded by the Portuguese Foundation for Science and Technology under the scholarship number 2021.06685.BD. Not applicable.