On signal variability of ECG-based biometric system under practical considerations

This article presents a study of an ECG-based biometric system with hybrid extraction of 10 features in the face of three challenges: variability intra- and inter-subject, ECG acquisition length and population length, arising from practical scenarios. To analyze its results, an ECG database with 1400 records of 10 s each one for 140 healthy subjects with scenarios of ECG variability was generated. The authentication performance with 5 matching metrics was studied, obtaining for 140 subjects an EER = 4.88%, 6.15% and 8.51% with records of 10 s, 5 s and 3 s respectively by means of Mahalanobis distance. Also, the identification performance was analyzed through 3 classifiers, obtaining for the same number of records an IR = 94.63%, 88.07% and 76.75% with records of 10 s, 5 s and 3 s respectively by means of k-NN (k = 1) with Mahalanobis distance.

[1]  Balazs Feil,et al.  Cluster Analysis for Data Mining and System Identification , 2007 .

[2]  Carlo Sansone,et al.  ECG databases for biometric systems: A systematic review , 2017, Expert Syst. Appl..

[3]  B. Hjorth.  EEG analysis based on time domain properties. , 1970, Electroencephalography and clinical neurophysiology.

[4]  Abdel-Badeeh M. Salem,et al.  Intelligent hybrid approaches for human ECG signals identification , 2018, Signal, Image and Video Processing.

[5]  Dimitrios Hatzinakos,et al.  Secure Telemedicine: Biometrics for Remote and Continuous Patient Verification , 2012, J. Comput. Networks Commun..

[6]  Zhang Rui,et al.  A Survey on Biometric Authentication: Toward Secure and Privacy-Preserving Identification , 2019, IEEE Access.

[7]  Juan Manuel Ramirez-Cortes,et al.  Embedded System for Bimodal Biometrics with Fiducial Feature Extraction on ECG and PPG Signals , 2020, 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[8]  Ana L. N. Fred,et al.  Check Your Biosignals Here: A new dataset for off-the-person ECG biometrics , 2014, Comput. Methods Programs Biomed..

[9]  Sugondo Hadiyoso,et al.  One-Lead Electrocardiogram for Biometric Authentication using Time Series Analysis and Support Vector Machine , 2019 .

[10]  Dimitrios Hatzinakos,et al.  ECG Based Recognition Using Second Order Statistics , 2008, 6th Annual Communication Networks and Services Research Conference (cnsr 2008).

[11]  Sahar A. ElRahman.  Biometric human recognition system based on ECG , 2019, Multimedia Tools and Applications.

[12]  Phalguni Gupta,et al.  Biometrics Method for Human Identification Using Electrocardiogram , 2009, ICB.

[13]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[14]  Ola Pettersson,et al.  ECG analysis: a new approach in human identification , 2001, IEEE Trans. Instrum. Meas..

[15]  Slawomir T. Wierzchon,et al.  Modern Algorithms of Cluster Analysis , 2018 .

[16]  Jaime S. Cardoso,et al.  Evolution, Current Challenges, and Future Possibilities in ECG Biometrics , 2018, IEEE Access.

[17]  B. Schijvenaars.  Intra-individual Variability of the Electrocardiogram: Assessment and exploitation in computerized ECG analysis , 2000 .

[18]  I. Jekova,et al.  Biometric verification by cross-correlation analysis of 12-lead ECG patterns: Ranking of the most reliable peripheral and chest leads. , 2017, Journal of electrocardiology.

[19]  S. Chiba,et al.  Dynamic programming algorithm optimization for spoken word recognition , 1978 .

[20]  Brenda K. Wiederhold,et al.  ECG to identify individuals , 2005, Pattern Recognit..

[21]  Mahesh M. Bundele,et al.  Design and implementation of human identification through physical activity aware 12 lead ECG , 2016, 2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE).

[22]  Dimitrios Hatzinakos,et al.  On Evaluating ECG Biometric Systems: Session-Dependence and Body Posture , 2014, IEEE Transactions on Information Forensics and Security.

[23]  Pablo Laguna,et al.  Bioelectrical Signal Processing in Cardiac and Neurological Applications , 2005 .

[24]  Ana L. N. Fred,et al.  Evaluating Template Uniqueness in ECG Biometrics , 2014, ICINCO.

[25]  Nadine Eberhardt,et al.  Bioelectrical Signal Processing In Cardiac And Neurological Applications , 2016 .

[26]  Arun Ross,et al.  An introduction to biometrics , 2008, ICPR 2008.