Real-Time PPG-Based Biometric Identification: Advancing Security with 2D Gram Matrices and Deep Learning Models

• Published in: Sensors (Basel, Switzerland) Vol. 25; no. 1; p. 40
• Main Authors: Cherry, Ali, Nasser, Aya, Salameh, Wassim, Abou Ali, Mohamad, Hajj-Hassan, Mohamad
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.01.2025; MDPI
• Subjects: Accuracy; Adult; Algorithms; Artificial intelligence; Biometric identification; Biometric Identification - methods; biometric security; Biometrics; Biometry - methods; Deep Learning; Female; Gram matrix conversion; Humans; liveness detection; Machine learning; Male; Neural networks; photoplethysmography (PPG) signals; Photoplethysmography - methods; Physiology; Signal Processing, Computer-Assisted; two-dimensional format; deep learning; real-time predictions; Gram matrix conversion; biometric security; liveness detection; classification; photoplethysmography (PPG) signals; two-dimensional format

The integration of liveness detection into biometric systems is crucial for countering spoofing attacks and enhancing security. This study investigates the efficacy of photoplethysmography (PPG) signals, which offer distinct advantages over traditional biometric techniques. PPG signals are non-invas...