Identity Authentication via ECG and PPG Signals: An Innovative Method Incorporating Singular Spectrum Analysis and Feature Integration
- Resource Type
- Conference
- Authors
- Liu, Xiaomin; Wu, Haichao; Ou, Wei
- Source
- 2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2024 IEEE 7th. 7:505-511 Mar, 2024
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Robotics and Control Systems
Signal Processing and Analysis
Noise
Authentication
Process control
Electrocardiography
Photoplethysmography
Robustness
Time-domain analysis
ECG
PPG
Signal Processing
Singular Spectrum Analysis
Feature Fusion
- Language
- ISSN
- 2689-6621
Electrocardiograms (ECG) directly measure cardiac electrical activity, while Photoplethysmography (PPG) indirectly reflects cardiac function; jointly, they reveal vital information about heart health. This paper pioneers the challenges of fusing ECG and PPG signals for identity authentication. We introduce an innovative approach that combines features from both ECG and PPG signals using Singular Spectrum Analysis (SSA) and a feature fusion model. Compared to existing methodologies, our approach demonstrates enhanced accuracy and robustness in identity verification. The results indicate a significant improvement in authentication precision using this integrated method. Simulated studies validate the effectiveness of our approach, underscoring its potential applications in the realm of identity authentication.