Key result
A proposed biometric sample extraction technique for ECG signals with abnormal cardiac conditions achieved high person identification accuracy of 96.7% for MITDB, 96.4% for SVDB, and 99.3% for DiSciRi.
Why the study?
Does the proposed ECG biometric extraction technique improve person identification accuracy in subjects with abnormal cardiac conditions compared to existing methods?
Does the proposed ECG biometric extraction technique improve person identification accuracy in subjects with abnormal cardiac conditions compared to existing methods?
A novel ECG biometric extraction technique achieves high person identification accuracy (96.4%-99.3%) even in the presence of abnormal cardiac conditions.
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May aid ECG biometrics in abnormal rhythms; leaves open comparative validation before clinical use.
Sidek et al. (2014) studied Abnormal cardiac conditions (n=164). Biometric sample extraction technique for ECG samples vs. Existing methods was evaluated on Person identification accuracy. A proposed biometric sample extraction technique for ECG signals with abnormal cardiac conditions achieved high person identification accuracy of 96.7% for MITDB, 96.4% for SVDB, and 99.3% for DiSciRi.
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