Ultra Wideband radar-based gait analysis for gender classification using artificial intelligence

Saleem, Adil Ali and Siddiqui, Hafeez Ur Rehman and Raza, Muhammad Amjad and Dudley, Sandra and Martínez Espinosa, Julio César and Dzul López, Luis Alonso and de la Torre Díez, Isabel UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ulio.martinez@unini.edu.mx, luis.dzul@uneatlantico.es, UNSPECIFIED (2025) Ultra Wideband radar-based gait analysis for gender classification using artificial intelligence. Array, 27. p. 100477. ISSN 25900056

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Abstract

Gender classification plays a vital role in various applications, particularly in security and healthcare. While several biometric methods such as facial recognition, voice analysis, activity monitoring, and gait recognition are commonly used, their accuracy and reliability often suffer due to challenges like body part occlusion, high computational costs, and recognition errors. This study investigates gender classification using gait data captured by Ultra-Wideband radar, offering a non-intrusive and occlusion-resilient alternative to traditional biometric methods. A dataset comprising 163 participants was collected, and the radar signals underwent preprocessing, including clutter suppression and peak detection, to isolate meaningful gait cycles. Spectral features extracted from these cycles were transformed using a novel integration of Feedforward Artificial Neural Networks and Random Forests , enhancing discriminative power. Among the models evaluated, the Random Forest classifier demonstrated superior performance, achieving 94.68% accuracy and a cross-validation score of 0.93. The study highlights the effectiveness of Ultra-wideband radar and the proposed transformation framework in advancing robust gender classification.

Item Type:	Article
Uncontrolled Keywords:	Gait; Ultra-wide band radar; Gender classification; Spectral features; Feed forward artificial neural network; Ridge classifier; Hist gradient boosting
Subjects:	Subjects > Engineering
Divisions:	Europe University of Atlantic > Research > Scientific Production Fundación Universitaria Internacional de Colombia > Research > Scientific Production Ibero-american International University > Research > Scientific Production Ibero-american International University > Research > Scientific Production Universidad Internacional do Cuanza > Research > Scientific Production University of La Romana > Research > Scientific Production
Depositing User:	Sr Bibliotecario
Date Deposited:	17 Sep 2025 14:45
Last Modified:	17 Sep 2025 14:45
URI:	http://repositorio.funiber.org/id/eprint/17849

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