FIST Lecturer Shares Research on ECG-Based Human Verification

Dr. Siti Nurfarah Ain Mohd Azam, Senior Lecturer from the Faculty of Information Science and Technology (FIST) was invited to share her research on ECG-based human verification during an online webinar organised under the IEEE Malaysia Consultants Network Affinity Group on 26 September 2026.

Titled “Robust ECG-Based Human Verification: Different Physiological Conditions, Signal Compression, and Time Variability”, the webinar explored the use of electrocardiogram (ECG) signals as a biometric technology for human verification.

During the session, Dr. Siti Nurfarah Ain introduced the fundamentals of ECG signals and explained how the unique characteristics of an individual’s heartbeat can be used for identity verification. She also shared her research on a robust ECG-based verification framework that combines signal processing, data compression and machine learning techniques.

The research examined the performance of ECG-based verification under different physiological conditions, with compressed signals, and across recordings taken on different days. These factors are important in developing verification systems that can maintain reliable performance despite variations in physical condition, data size and recording time.

The webinar provided participants with insights into both the potential and challenges of ECG-based biometrics, particularly in developing practical authentication systems for future digital security applications.