Open Access
Identification of Individuals using Electrocardiogram
TLDR
This work establishes that ECG signal is a signature like fingerprint, retinal signature for any individual Identification, and presents a systematic Template matching for Identification of individuals from ECG data.Abstract:
Protection anxiety is to be increased as the technology for forgery grows. Reliable personal Identification and prevention of forged identities is one of the major tasks. Currently, Biometrics is being used extensively for the purpose of security measures. Biometric recognition provides strong security by identifying an individual based on the feature vector(s) derived from their physiological and/or behavioral characteristics. It has been proved that the human Electrocardiogram (ECG) shows adequately unique patterns for biometric recognition. Individual can be identified once ECG signature is formulated. This paper presents a systematic Template matching for Identification of individuals from ECG data. This work establishes that ECG signal is a signature like fingerprint, retinal signature for any individual Identification. Samples of individuals from the MIT/BIH database were taken. The matching decisions are evaluated on the basis of correlation coefficient between features. Preliminary experimental results indicate that the system is accurate (99%), robust, error rate is smaller than 0.9 and achieves a good result for Identification process.read more
Citations
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Driver Fatigue Detection Systems: A Review
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TL;DR: This paper presents state-of-the-art review of recent advancement in the field of driver fatigue detection and various approaches have been compared for fatigue detection, and areas open for improvements are deduced.
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Evolution, Current Challenges, and Future Possibilities in ECG Biometrics
TL;DR: A deep review and discussion of 93 state-of-the-art publications on their proposed methods, signal datasets, and publicly available ECG collections is conducted to present the fundamentals and the evolution of ECG biometrics, describe the current state of the art, and draw conclusions on prior art approaches and current challenges.
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Individual identification via electrocardiogram analysis
TL;DR: A survey of the techniques used so far in ECG-based human identification is provided, providing a unifying framework to appreciate previous studies and, hopefully, guide future research.
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Towards a Continuous Biometric System Based on ECG Signals Acquired on the Steering Wheel
TL;DR: The enhancement of the unprecedented lesser quality of electrocardiogram signals through the combination of Savitzky-Golay and moving average filters, followed by outlier detection and removal based on normalised cross-correlation and clustering was able to render ensemble heartbeats of significantly higher quality.
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