Key result
An ECG biometric verification system using non-fiducial features achieved a verification rate of 94.44% and an F-score of 96.66%.
Why the study?
Biometric systems use behavioral or physiological traits for human identification, and the ECG provides a physiological biometric that is impossible to mimic or steal.
An ECG biometric system using non-fiducial features achieved 96.66% accuracy for personal identity verification.
ECG verification via DWT non-fiducial features reaches 96.66% F-score; leaves open clinical use pending larger prospective validation.
Biometrics was used as an automated and fast acceptable technology for human identification and it may be behavioral or physiological traits. Any biometric system based on identification or verification modes for human identity. The electrocardiogram (ECG) is considered as one of the physiological biometrics which impossible to mimic or stole. ECG feature extraction methods were performed using fiducial or non-fiducial approaches. This research presents an authentication ECG biometric system using non-fiducial features obtained by Discrete Wavelet Decomposition and the Euclidean Distance technique was used to implement the identity verification. From the obtained results, the proposed system accuracy is 96.66% also, using the verification system is preferred for a large number of individuals as it takes less time to get the decision.
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Marwa A. Elshahed (2020) studied Biometric identification (n=90). ECG biometric verification using non-fiducial features (Discrete Wavelet Decomposition and Euclidean Distance) was evaluated on F-score for biometric verification. An ECG biometric verification system using non-fiducial features achieved a verification rate of 94.44% and an F-score of 96.66%.
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