Graphene-based Wearable Sensor for Biometric Authentication and Real-Time Health Monitoring with Secure AI at the Edge
Keywords:
Biometric Data, Warm Expanded Graphite, Polyvinylidene Fluoride, Graphene Nanoplatelets, Anomaly Detection, Fourier and Wavelet Analysis, Support Vector Machine.Abstract
Wearable sensors enable continuous monitoring of vital signs and biometric data, providing real-time feedback for personalized health management and early detection of health issues. They support remote patient monitoring, improving healthcare access and reducing the need for frequent hospital visits, especially for individuals with chronic conditions. The work focuses on developing a graphene-based wearable sensor system for biometric authentication and real-time health monitoring. The innovative fabrication process involves integrating warm expanded graphite (WEG) and polyvinylidene fluoride (PVDF) to create a conductive and flexible material suitable for wearable sensors. Graphene nanoplatelets (GNPs) are embedded within a PVDF matrix to enhance conductivity. The resulting PVDF/GNP electrodes offer high flexibility and signal quality, critical for accurate data acquisition and user comfort. Advanced signal processing techniques, including Fourier and wavelet analysis, extract physiological features for biometric identification and health assessment. Anomaly detection algorithms like One-Class SVM (Support Vector Machine) ensure system security by identifying deviations from normal behavior. This project offers a sophisticated solution for personalized biometric authentication and comprehensive health monitoring, driven by the precise analysis of physiological waveform data captured across diverse electrode configurations. Successful fabrication of graphene-based wearable sensors using WEG and PVDF, resulting in flexible, conductive materials suitable for integration into wearable devices.Top of Form
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