Forensic Science is a branch of science that deals with the discovery, examination, and analysis of strong elements or evidence involved in the criminal justice system. It involves the use of scientific methods to investigate crimes. The Gender Classification System is closely linked to forensic studies, specifically investigating individuals through their handwriting, known as Behavioral Biometrics. Biometric systems rely on behavioral and physiological traits such as brain-prints, fingerprints, handwritten text, speech, facial attributes, gait information, palm vein patterns, hand geometry, electrocardiograms (ECGs), and more. Gender classification is an intriguing and important aspect within the field of pattern recognition and machine learning. It involves a binary problem of classifying individuals as either male or female. Analyzing the differences in femininity and masculinity behaviors can contribute to the evaluation of biometric-based identification systems. Gender classification has numerous forensic applications, including crime identification, demographic research, forgery detection, security, and surveillance. The main objective of this article is to present the latest survey findings on the gender classification system based on handwritten text, specifically the behavioral biometric modality. It includes an overview of the state-of-the-art work, the general framework, approaches, biometric modalities, and critical analysis. The article concludes with a critical analysis, discussion of open issues, concluding remarks, and future perspectives.

法医学是科学的一个分支，涉及刑事司法系统中涉及的强有力的要素或证据的发现、检查和分析。它涉及使用科学方法调查犯罪。性别分类系统与法医研究密切相关，特别是通过笔迹来调查个人，称为行为生物识别。生物识别系统依赖于行为和生理特征，例如脑纹、指纹、手写文本、语音、面部属性、步态信息、手掌静脉模式、手部几何形状、心电图 (ECG) 等。性别分类是模式识别和机器学习领域中一个有趣且重要的方面。它涉及将个体分类为男性或女性的二元问题。分析女性和男性行为的差异有助于评估基于生物识别的识别系统。性别分类有许多法医应用，包括犯罪识别、人口统计研究、伪造品检测、安全和监视。本文的主要目的是介绍基于手写文本的性别分类系统的最新调查结果，特别是行为生物识别模式。它包括对最先进工作的概述、总体框架、方法、生物识别模式和批判性分析。本文最后进行了批判性分析、对未解决问题的讨论、结论性意见和未来展望。