title: Compressed ECG biometric: a fast, secured and efficient method for identification of CVD patient.
abstract: 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.
authors: School of Computer Science and Information Technology, RMIT University, Melbourne, Australia. research@fahimsufi.com
authors: Fahim
authors: F
authors: Sufi
authors: Ibrahim
authors: I
authors: Khalil
authors: Abdun
authors: A
authors: Mahmood
mesh_terms: D000465:Algorithms; D001699:Biometry; D002318:Cardiovascular Diseases / Q000175:diagnosis*; D044962:Data Compression / Q000379:methods*; D004562:Electrocardiography / Q000295:instrumentation*; D006801:Humans; D008991:Monitoring, Physiologic; D010355:Patient Identification Systems / Q000379:methods*; D013997:Time Factors