Key result
ECG-based biometric authentication achieves up to ~99% accuracy using Dynamic Time Warping.
Why the study?
Automatic attendance systems using heart biometrics focus on the internal uniqueness and flexibility of the heart, with ECG authentication being a primary modality.
May support ECG biometrics for secure identification; leaves open prospective validation in diverse clinical populations before adoption.
All the biometric systems are based on some important features of these modalities which are mainly known for their uniqueness in one way or the other. However, the automatic attendance system using heart biometrics is focused as it is internally unique and focused on internal flexibility of the heart. Heart biometrics include different authentication modalities such as ECG, SCG, PCG and so on. It is primarily focused on authentication using ECG signals which uses algorithms or techniques such as SVM (support vector machine) for authentication purposes and dynamic time warping for signal matching. Algorithms used have shown high accuracy results and the challenges faced were considerable and effectively managed to improve for further advancements.
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Rastogi et al. (2023) conducted a review in Biometric Authentication. ECG-based biometric authentication vs. Traditional biometrics (face, fingerprint) was evaluated on Authentication accuracy. ECG-based biometric authentication provides a highly secure and unique alternative to traditional modalities, achieving accuracy up to 99.4% using Dynamic Time Warping.
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