Verification of humans using the electrocardiogram
Pattern Recognition Letters
Remote health-care monitoring using personal care connect
IBM Systems Journal
EURASIP Journal on Advances in Signal Processing
An Efficient Clustering Scheme to Exploit Hierarchical Data in Network Traffic Analysis
IEEE Transactions on Knowledge and Data Engineering
A novel wavelet packet-based anti-spoofing technique to secure ECG data
International Journal of Biometrics
A New Feature Detection Mechanism and Its Application in Secured ECG Transmission with Noise Masking
Journal of Medical Systems
Novel methods of faster cardiovascular diagnosis in wireless telecardiology
IEEE Journal on Selected Areas in Communications - Special issue on wireless and pervasive communications for healthcare
Pattern Recognition
Echidna: efficient clustering of hierarchical data for network traffic analysis
NETWORKING'06 Proceedings of the 5th international IFIP-TC6 conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems
Implementation of a WAP-based telemedicine system for patient monitoring
IEEE Transactions on Information Technology in Biomedicine
A Mobile Care System With Alert Mechanism
IEEE Transactions on Information Technology in Biomedicine
A novel biometrics method to secure wireless body area sensor networks for telemedicine and m-health
IEEE Communications Magazine
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Adoption of compression technology is often required for wireless cardiovascular monitoring, due to the enormous size of Electrocardiography (ECG) signal and limited bandwidth of Internet. However, compressed ECG must be decompressed before performing human identification using present research on ECG based biometric techniques. This additional step of decompression creates a significant processing delay for identification task. This becomes an obvious burden on a system, if this needs to be done for a trillion of compressed ECG per hour by the hospital. Even though the hospital might be able to come up with an expensive infrastructure to tame the exuberant processing, for small intermediate nodes in a multihop network identification preceded by decompression is confronting. In this paper, we report a technique by which a person can be identified directly from his / her compressed ECG. This technique completely obviates the step of decompression and therefore upholds biometric identification less intimidating for the smaller nodes in a multihop network. The biometric template created by this new technique is lower in size compared to the existing ECG based biometrics as well as other forms of biometrics like face, finger, retina etc. (up to 8302 times lower than face template and 9 times lower than existing ECG based biometric template). Lower size of the template substantially reduces the one-to-many matching time for biometric recognition, resulting in a faster biometric authentication mechanism.