Total views : 394

Improvement in ECG based Biometric Systems using Wavelet Packet Decomposition (WPD) Algorithm

Affiliations

  • Department of Robotics and Artificial Intelligence, School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), H-12 Main Campus, Islamabad, Pakistan

Abstract


In this paper, a non-fiducial approach using Wavelet Packet Decomposition (WPD) algorithm for repeated examination of solitary cable ECG used for individual identification is planned and tested. Multiple samples of ECG wave are extracted considering R-peak as a reference and WPD algorithm is applied for feature extraction. This feature file is fed as an input to a machine learning classifier i.e. random forest in order to classify the individuals. In this work, records from publicly available MIT/BIH arrhythmia dataset have been utilized to evaluate the proposed system. Best result relies on third level of wavelet decomposition using Daubechies wavelet to analyze the signal. Furthermore ranker search method is used in conjunction with relief attribute evaluator for feature selection and random forest classifier is applied by generating 100 trees. It is shown that the method is effective for quantifying the classification of arrhythmia ECG signals with accuracy of 92.62%.

Keywords

Biometrics, ECG, MIT-BIH Arrhythmia Database, Random Forest, Wavelet Packet Decomposition.

Full Text:

 |  (PDF views: 311)

References


  • Bansal A, Agarwal R, Sharma RK. FAR and FRR based analysis of iris recognition system. 2012 IEEE International Conference on Signal Processing, Computing and Control (ISPCC); 2012 Mar. p. 1–6.
  • Syed Z, Helmick J, Banerjee S, Cukic B. Effect of user posture and device size on the performance of touch-based authentication systems. 2015 IEEE 16th International Symposium on High Assurance Systems Engineering (HASE); 2015 Jan. p. 10–7.
  • Silva H, Lourenco A, Lourenco R, Leite P, Coutinho D, Fred A. Study and evaluation of a single differential sensor design based on electro-textile electrodes for ECG biometrics applications. IEEE Sensors; 2011. p. 1764–7.
  • Phillips PJ, Martin A, Wilson CL, Przybocki M. An introduction evaluating biometric systems. Computer. 2000; 33(2):56–63.
  • Ross AA, Nandakumar K, Jain AK. Handbook of multibiometrics (International Series on Biometrics). Secaucus; 2006.
  • Biel L, Pettersson O, Philipson L, Wide P. ECG analysis: A new approach in human identification. IEEE Transactions on Instrumentation and Measurement. 2001; 50(3):808–12.
  • Zeng F, Tseng KK, Huang HN, Tu SY, Pan JS. A new statisticalbased algorithm for ECG identification. 2012 IEEE Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP); 2012 Jul. p. 301–4.
  • Sahoo SK, Choubisa T, Prasanna SM. Multimodal biometric person authentication: A review. IETE Technical Review. 2012; 29(1):54–75.
  • Coutinho DP, Silva H, Gamboa H, Fred A, Figueiredo M. Novel fiducial and non-fiducial approaches to Electrocardiogrambased biometric systems. IET biometrics. 2013; 2(2):64–75.
  • Chiu CC, Chuang CM, Hsu CY. Discrete Wavelet Transform applied on personal identity verification with ECG signal. International Journal of Wavelets, Multiresolution and Information Processing. 2009; 7(03):341–55.
  • Haque AKMF, Ali MH, Kiber MA, Hasan MT. Detection of small variations of ECG features using Wavelet. ARPN Journal of Engineering and Applied Sciences. 2009; 4(6):27–30.
  • Addison P, Watson JN, Clegg GR, Holzer M, Sterz F, Robertson CE. Evaluating arrhythmias in ECG signals using wavelet transforms. IEEE Engineering in Medicine and Biology Magazine. 2000; 19(5):104–9.
  • Chan AD, Hamdy MM, Badre A, Badee V. Wavelet distance measure for person identification using Electrocardiograms. IEEE Transactions on Instrumentation and Measurement. 2008; 57(2):248–53.
  • Chan AD, Hamdy MM, Badre A, Badee V. Person identification using Electrocardiograms. 2006 IEEE Canadian Conference on Electrical and Computer Engineering, CCECE’06; 2006 May. p. 1–4.
  • Ye C, Coimbra MT, Kumar BVKV. Investigation of human identification using two-lead Electrocardiogram (ECG) signals. 2010 Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS); 2010 Sep. p. 1–8.
  • Zhang Z, Wei D. A new ECG identification method using Bayes’ Theorem. 2006 IEEE Region 10 Conference, TENCON; 206 Nov. p. 1–4.
  • Agrafioti F, Hatzinakos D. ECG based recognition using second order statistics. 2008 IEEE 6th Annual Communication Networks and Services Research Conference, CNSR; 2008 May. p. 82–7.
  • Shen TW, Tompkins WJ, Hu YH. One-lead ECG for identity verification. Proceedings of the Second Joint Engineering in Medicine and Biology, 2002 IEEE 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference. 2002; 1:62–3.
  • Palaniappan R, Krishnan SM. Identifying individuals using ECG beats. Proceedings of the International Conference on Signal Processing and Communications (SPCOM’04); 2004 Dec. p. 569–72.
  • Gahi Y, Lamrani M, Zoglat A, Guennoun M, Kapralos B, El-Khatib K. Biometric identification system based on Electrocardiogram data. IEEE New Technologies, Mobility and Security, NTMS’08; 2008 Nov. p. 1–5.
  • Sriram JC, Shin M, Choudhury T, Kotz D. Activity-aware ECG-based patient authentication for remote health monitoring. Proceedings of the 2009 International Conference on Multimodal Interfaces, ACM; 2009 Nov; p. 297–304.
  • Abdelraheem M, Selim H, Abdelhamid TK. Human identification using the main loop of the vector cardiogram. Am J Signal Process. 2012; 2:23–9.
  • Tantawi M, Revett K, Tolba MF, Salem A. A novel feature set for deployment in ECG based biometrics. 2012 IEEE Seventh International Conference on Computer Engineering and Systems (ICCES); 2012 Nov. p. 186–91.
  • Ogunbona PO, Milliss M, De Bore F, Fernandes M. Classification of gas metal arc welds using wavelets. Engineering Mathematics and Applications Conference; Adelaide, Australia. 1998. p. 383–6.
  • Moody GB, Mark RG. The impact of the MIT-BIH arrhythmia database. IEEE Engineering in Medicine and Biology Magazine. 2001; 20(3):45–50.

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.