Abstract
The ECG (electrocardiogram) is an emerging technology for biometric human identification. In this paper, the performance of an ECG biometric recognition system is evaluated. Signal processing techniques are utilized to extract the ECG features. In preprocessing stage, digital filters eliminate the noises and hence improve the signal to noise ratio. The process of ventricular complex (QRS Complex) detection depends on Pan and Tompkins approach that achieves an efficient QRS detection, and hence enhancing the feature extraction process. The main classifiers applied to the extracted features are Neural Network (NN), Fuzzy Logic (FL), Nearest Mean Classifier (NMC), Linear Discriminant Analysis (LDA), and Euclidean Distance (ED) are utilized to classify QRS fragments. ECG of an unknown subject is acquired; the classifiers are applied to wavelet coefficient features set between the unknown subject and all enrolled subjects. The Performance of the different approaches is evaluated by utilizing Sensitivity, Specificity, and efficiency, EER (Equal Error Rate) and ROC (Receiver Operating Characteristic) curve. The experiments are conducted on 112 individuals MIT-BIH database and the accuracy is up to 98.99%.
Similar content being viewed by others
References
Alvarado M, Melin P, Lopez M, Mancilla A, Castillo O (2009) A hybrid approach with the wavelet transform, modular neural networks and fuzzy integrals for face and fingerprint recognition, 2009 IEEE Workshop on Hybrid Intelligent Models and Applications, 19–24. Doi:https://doi.org/10.1109/HIMA.2009.4937820
Barra S, Casanova A, Fraschini M, Nappi M (2017) Fusion of physiological measures for multimodal biometric systems. Multimed Tools Appl 76(4):4835–4847. https://doi.org/10.1007/s11042-016-3796-1
Belgacem N, Nait-Ali A, Fournier R, Bereksi-Reguig F (2012) ECG based human authentication using wavelets and random forests. Int J Cryptograp Inform Sec (IJCIS) 2(2):1–11
Biel L, Pettersson O, Philipson L, Wide P (2001) ECG analysis: a new approach in human identification. IEEE Trans Instrum Meas 50(3):808–812
Castro B, Kogan D, Geva AB (2000) ECG feature extraction using optimal mother wavelet. 21st IEEE convention of the electrical and electronic engineers, 346–350
Chan ADC, Hamdy MM, Badre A, Badee V (2008) Wavelet distance measure for person identification using electrocardiograms. IEEE Trans Instrum Meas 57(2):248–253
Chen ZX, Wysocki T, Agrafioti F, Hatzinakos D (2012) Securing handheld devices and fingerprint readers with ECG biometrics. 5th International Conference on Biometrics: Theory, Applications and Systems (BTAS): 150–155
Chen S, Guo J, Huang H, Kung W, Tseng K, Tu SH (2014) Hiding patients confidential Datainthe ECG signal via a transform-domain quantization scheme. J Med Syst, 38–54. doi:https://doi.org/10.1007/s10916-014-0054-9
Falconi JSA (2013 ECG authentication for Mobile devices. Master degree thesis, Faculty of Engineering, University of Ottawa
Gawande PS, Ladhake SA (2015) Artificial neural network based electrocardiogram classification for biometric authentication. Int J Comput Appl 109(2):6–9
Halici U, Ngun G (1996) Fingerprint classification through self-organizing feature maps modified to treat uncertainties. Proc IEEE 84(10):1497–1512
Karpagachelvi S, Arthanari M, Sivakumar M (2010) ECG feature extraction techniques - a survey approach. Int J Comput Sci Inform Sec 8(1):76–80
Lourenço A, Silva H, Fred A (2011) Unveiling the biometric potential of finger-based ECG signals. Comput Intell Neurosci 720971:1–8
Nawal M, Purohit GN (2014) ECG based human authentication: a review. Int J Emerg Eng Res Technol 2(3):178–185
Nemirko AP, Lugovaya TS (2005) Biometric human identification based on electrocardiogram. Proceeding XII-th Russian conference on mathematical methods of pattern recognition. MAKS Press, Moscow, pp 387–390
Pal A, Singh YN (2018) ECG biometric recognition. ECG biometric recognition. In: Ghosh D, Giri D, Mohapatra R, Savas E, Sakurai K, Singh L (eds) Mathematics and computing. ICMC 2018. Communications in Computer and Information Science, vol 834. Springer, Singapore, pp 61–73
Pan J, Tompkins WJ (1985) A real-time QRS detection algorithm. IEEE Trans Biomed Eng BME-32(3):230–236
Sedghamiz H (2014) Matlab Implementation of Pan Tompkins ECG QRS detector. [Online] Available: https://www.researchgate.net/publication/313673153_Matlab_Implementation_of_Pan_Tompkins_ECG_QRS_detector
Singh YN (2014) Individual identification using linear projection of heartbeat features. J Appl Comput Intell Soft Comput 602813:1–14
Singh YN, Gupta P (2008) ECG to individual identification. 2nd IEEE international conference on biometrics:theory, Applications and Systems (BTAS ‘08), 1–8
Singh YN, Gupta P (2009) Biometric method for human identification using electrocardiogram. Proc 3rd IAPR/IEEE Int Conf Biomet ICB 2009, LNCS, Springer-Verlag Berlin 5558(2009):1270–1279
Singh YN, Gupta P (2011) Correlation based classification of heartbeats for individual identification. Journal of Soft Computing 15(3):449–460
Singh YN, Singh SK (2012) Evaluation of electrocardiogram for biometric authentication. J Inf Secur 3(1):39–48
Singh YN, Singh SK (2013) Identifying individuals using Eigenbeat features of electrocardiogram. J Eng 539284:1–8
Singh YN, Singh SK, Gupta P (2012) Fusion of electrocardiogram with unobtrusive biometrics: an efficient individual authentication system. Pattern Recogn Lett 33(14):1932–1941
Sugeno M (1974) Theory of fuzzy integrals and its application. Ph.D thesis, Tokyo institute of technology
Tun HM, Moe WK, Naing ZM (2015) Analysis of computer aided identification system for ECG characteristic points. Int J Biomed Sci Eng 3(4):49–61
Varatharajan R, Manogaran G, Priyan MK (2017) A big data classification approach using LDA with an enhanced SVM method for ECG signals in cloud computing. Journal of multimedia tools and applications, © Springer, 1–21. doi:https://doi.org/10.1007/s11042-017-5318-1
Venkatesh N, Jayaraman S (2010) Human electrocardiogram for biometrics using DTW and FLDA. International conference on pattern recognition. © IEEE Comput Soc: 3838–3841
Wang Y, Agrafioti F, Hatzinakos D, Plataniotis KN (2008) Analysis of human electrocardiogram for biometric recognition. EURASIP J Adv Sign Process 148658:1–11
Zokaee S, Faez K (2012) Human identification based on electrocardiogram and Palmprint. Int J Electric Comput Eng (IJECE) 2(2):261–266
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
El_Rahman, S.A. Biometric human recognition system based on ECG. Multimed Tools Appl 78, 17555–17572 (2019). https://doi.org/10.1007/s11042-019-7152-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-019-7152-0