Biometrics System Technology Trends Based on Biosignal

생체신호 기반 바이오인식 시스템 기술 동향

  • Received : 2016.10.28
  • Accepted : 2017.01.20
  • Published : 2017.01.28


Biometric technology is a technology for authenticating a user using the physical or behavioral features of the inherent characteristics of the individual. With the necessity and efficiency of the technology in the fields of finance, security, access control, medical welfare, inspection, and entertainment, the service range has been expanding. Biometrics using biometric information such as fingerprints and faces have been exposed to counterfeit and disguised threats and become a social problem. Recent studies using a bio-signal from the inside of the body other than the bio-information of the external body are being developed. This paper analyzes the recent research and technology of biometric systems using bio-signals, ECG, heart sounds, EEG, and EMG to present the skills needed for the development direction. In the future, utilizing the deep learning to build and analyze database to manage bio-signal based big data for the complex condition of individuals, biometrics technologies suitable for real time environment are expected to be researched.


Biometrics;Bio-signal;ECG;Heart beat;EEG;EMG;Big data;Deep learning


Grant : 웹 서비스 사용자 계정 정보 관리 및 유출/악용 탐지 기술 개발

Supported by : 정보통신기술진흥센터


  1. P. D. Lapsley, M. Kleeman, and P. J. Gioia, "Biometric financial transaction system and method." U.S. Patent and trademark office, No. 8,630,933, Jan. 2014.
  2. C. K. Dimitriadis and D. Polemi, "Biometric-enabled authentication in 3G/WLAN systems." Proceedings 39th annual 2005 international carnahan conference on security technology, PP. 164-167, Oct. 2005.
  3. C. C. Poon, Y. T. Zhang, and S. D. Bao, "A novel biometrics method to secure wireless body area sensor networks for telemedicine and m-health." Communications magazine IEEE, Vol. 44, Issue 4, PP. 73-81, Apr. 2006.
  4. J. D. Woodward, N. M. Orlans, and P. T. Higgins, "Biometrics:[Identity assurance in the information age]." New york: McGraw-Hill/Osborne, 2003.
  5. S. Davies, "Biometrics:A civil liberties and privacy perspective." Information security technical report, Vol. 3, Issue 1, PP. 90-94, 1998.
  6. J. Pathuel, "Biometric control systems and associated methods of use." U.S. Patent application, No. 11/159,814, 2005.
  7. J. Morton and A. Secretary, "US immigration and customs enforcement." US Immigration and customs enforcement, Jul. 2012.
  8. J. M. Gatto, T. B. Decourssou, and P. J. Beney, "Modular entertainment and gaming system configured for processing raw biometric data and multimedia response by a remote server." DC: U.S. Patent and trademark office, No. 6,945,870, Sep. 2005.
  9. J. L. Wayman, "Technical testing and evaluation of biometric identification devices." Biometrics. Springer US, PP. 345-368, 1996.
  10. R. De luis-garcia, C. Alberola-lopez, O. Aghzout, and J. Ruiz-Alzola, "Biometric identification systems." Signal processing, Vol. 83, Issue 12, PP. 2539-2557, Dec. 2003.
  11. A. Kaveh and W. H. Chung, "Temporal and spectral features of single lead ECG for human identification." Biometric Measurements and Systems for Security and Medical Applications (BIOMS), 2013 IEEE Workshop on IEEE, PP. 17-21, Sep. 2013.
  12. J. Wang, M. She, S. Nahavandi, and A. Kouzani, "Human identification from ECG signals via sparse representation of local segments." Signal processing letters IEEE, Vol. 20, Issue 10, PP. 937-940, Jun. 2103.
  13. T. M. Nazmy, H. El-messiry, and B. Al-bokhity, "Adaptive neuro-fuzzy inference system for classification of ECG signals." Informatics and systems (INFOS), 2010 The 7th international conference on IEEE, PP. 1-6, 2010.
  14. S. D. Al-shamma and M. C. Al-noaemi, "Heart sound as a physiological biometric signature." Biomedical Engineering Conference (CIBEC), 2010 5th Cairo International. IEEE, PP. 232-235, Dec. 2010.
  15. K. Phua, T. H. Dat, J. Chen, and L. Shue, "Human identification using heart sound." Second international workshop on multimodal user authentication, Vol. 227, No. 10, May. 2006.
  16. S. K. Yeom, H. I. Suk, and S. W. Lee, "Person authentication from neural activity of face-specific visual self-representation." Pattern recognition, Vol. 46, Issue 4, PP. 1159-1169, Apr. 2013.
  17. K. Brigham and B. V. K. V. Kumar, "Subject identification from electroencephalogram (EEG) signals during imagined speech." Biometrics: theory applications and systems (BTAS), 2010 Fourth IEEE international conference on. IEEE, PP. 1-8, Sep. 2010.
  18. M. Suresh, P. G. Krishnamohan, and M. S. Holi, "GMM modeling of person information from EMG signals." Recent advances in intelligent computational systems (RAICS) IEEE, PP. 712-717, Sep. 2011.
  19. A. Alkan and M. Gunay, "Identification of EMG signals using discriminant analysis and SVM classifier." Expert systems with applications, Vol. 39, Issue 1, PP. 44-47, Jan. 2012.
  20. G. B. Moody, R. G. Mark, and A. L. Goldberger, "PhysioNet: a web-based resource for the study of physiologic signals." IEEE Eng med biol mag, Vol. 20, Issue 3, PP. 70-75, Jun. 2001.
  21. I. W. Selesnich and C. S. Burrus, "Generalized digital butterworth filter design." Signal processing, IEEE Transactions on, Vol. 46, Issue 6, PP. 1688-1694, Jun. 1998.
  22. R. J. Cameron, "Fast generation of chebyshev filter prototypes with asymmetrically-prescribed transmission zeros." ESA Journal, Vol. 6, No. 1, PP. 83-95, 1982.
  23. A. Nehorai, "A minimal parameter adaptive notch filter with constrained poles and zeros." Acoustics, Speech and signal processing, IEEE Transactions on, Vol. 33, Issue 4, PP. 983-996, Aug. 1985.
  24. M. J. Shensa, "The discrete wavelet transform: wedding the a trous and mallat algorithms." Signal processing, IEEE transactions on, Vol. 40, Issue 10, PP. 2464-2482, Oct. 1992.
  25. Y. Y. Tang, J. Liu, L. H. Yang, and H. Ma, "Continuous wavelet transforms." Wavelet theory and its application to pattern recognition, Vol. 74, PP. 53-81, 2000.
  26. Z. Zhao, L. Yang, D. Chen, and Y. Luo, "A human ECG identification system based on ensemble empirical mode decomposition." Sensors, Vol. 13, Issue. 5, PP. 6832-6864, May. 2013.
  27. S. Wold, K. Esbensen, and P. Geladi, "Principal component analysis." Chemometrics and intelligent laboratory systems, Vol. 2, Issue 1-3, PP. 37-52, Aug. 1987.
  28. B. Scholkopft and R. K. Mullert, "Fisher discriminant analysis with kernels." Neural networks for signal processing IX, Vol. 1, Issue 1, PP. 41-48, 1999.
  29. M. A. Hearst, S. T. Dumais, E. Osman, J. Platt, and B. scholkopf, "Support vector machines", Intelligent Systems and their Applications IEEE, Vol. 13, Issue 4, PP. 18-28, Aug. 1998.
  30. M. A. Friedl and C. E. Brodley, "Decision tree classification of land cover from remotely sensed data." Remote sensing of environment, Vol. 61, Issue 3, PP. 339-409, Sep. 1997.
  31. T. Denoeux, "A k-nearest neighbor classification rule based on Dempster-Shafer theory." Systems, man and cybernetics, IEEE transactions on, Vol. 25, Issue 5, PP. 804-813, May. 1995.
  32. A. Liaw and M. Wiener, "Classification and regression by randomForest." R news, Vol. 2, Issue 3, PP. 18-22, Dec. 2002.
  33. C. E. Rasmussen, "The infinite gaussian mixture model." NIPS, Vol. 12, PP. 554-560, 1999.
  34. L. M. Sangalli, P. Secchi, S. Vantini, and V. Vitelli, "K-mean alignment for curve clustering." Computational statistics & data analysis, Vol. 54, Issue 5, PP. 1219-1233, May. 2010.
  35. L. Biel, O. Pettersson, L. Philipson, and P. Wide, "ECG analysis: a new approach in human identification." Instrumentation and measurement transactions on IEEE, Vol. 50, Issue 3, PP. 808-812, Jun. 2001.
  36. G. U. Gang, C. H. Min, and T. S. Kim, "Single channel ECG-based biometric system development." Korea journal of electronics engineers, Vol. 49, No. 1, PP. 1-7, Jan. 2012.
  37. S. J. Lee and M. H. Lee, "ECG developed face recognition algorithm using SVM classifier." Korea journal of electrical engineers, Vol. 60, No. 3, PP. 654-661, Mar. 2011.
  38. H. Gurkan, U. Guz, and B. S. Yarman, "A Novel Human Identification System based on Electrocardiogram Features." Signals, circuits and systems (ISSCS), 2013 International symposium on. IEEE, PP. 1-4, Jul. 2013.
  39. S. Pathoumvanh, S. Airphaiboon, B. Prapochanung, and T. Leauhatong, "ECG analysis for person identification." Biomedical engineering international conference (BMEiCON) on IEEE, PP. 1-4, Oct. 2013.
  40. A. B. Amiruddin, O. O. Khalifa, and F. A. F. Rabih, "Performance evaluation of human identification based on ECG signal." Computing, control, networking, electronics and embedded systems engineering (ICCNEEE), International conference on. IEEE, PP. 479-484, Sep. 2015.
  41. S. L. Lin, C. K. Chen, W. C. Yang, and C. T. Chiang, "Individual identification based on chaotic electrocardiogram signals during muscular exercise." Biometrics, Vol. 3, Issue 4, PP. 257-266, Dec. 2014.
  42. S. H. Im, G. R. Min, J. S. Lee, D. P, Jang, and I. Y. Kim, "Personal identification using a single lead electrocardiogram." Korea journal of biomedical engineering research, Vol. 35, No. 3, PP. 42-49, Jun. 2014.
  43. E. Rabhi and Z. Lachiri, "Biometric Personal Identification System using the ECG Signal." Computing in cardiology conference (CinC) on IEEE, PP. 507-510, Sep. 2013.
  44. A. Fratini, M. Sansone, P. Bifulco, M. Romano, A. Pepino, M. Cesarelli, and G. D'Addio, "Individual identification using electrocardiogram morphology." Medical measurements and applications proceedings (MeMeA), International symposium on. IEEE, PP. 107-110, May. 2013.
  45. S. Hari, F. Agrafioti, and D. Hatzinakos, "Design of a Hamming-distance classifier for ECG biometrics." Acoustics, speech and signal processing (ICASSP), International conference on. IEEE, PP. 3009-3012, May. 2013.
  46. M. N. Dar, M. U. Akram, A. Shaukat, and M. A. Khan, "ECG based biometric identification for population with normal and cardiac anomalies using hybrid HRV and DWT features." IT convergence and security (ICITCS), 5th International conference on. IEEE, PP. 1-5, Aug. 2015.
  47. S. J. Jang, S. J. Yoon, J. W. Lee, G. J. Kim, and C. S. Jang, "Biometrics using discrete wavelet transform based ECG." Korea electronics and telecommunications society journal proceedings, Vol. 7, No. 1, PP. 514-517, Mar. 2013.
  48. F. Beritelli and A. Spadaccini, "Human identity verification based on mel frequency analysis of digital heart sounds." Digital signal processing, 2009 16th international conference on. IEEE, PP. 1-5, Jul. 2009.
  49. H. D. Tran, Y. R. Leng, and H. Li, "Feature integration for heart sound biometrics." Acoustics speech and signal processing (ICASSP), international conference on. IEEE, PP. 1714-1717, Mar. 2010.
  50. K. Das, S. Zhang, B. Giesbrecht, and M. P. Eckstein, "Using rapid visually evoked EEG activity for person identification." Engineering in medicine and biology society, Annual international conference of the IEEE, PP. 2490-2493, Sep. 2009.
  51. D. La Rocaa, P.Campisi, and G. Scarano, "On the repeatability of EEG features in a biometric recognition framework using a resting state protocol." BIOSIGNALS, PP. 419-428, 2013.
  52. N. Kunju, N. Kumar, D. Pankaj, A. Dhawan, and A. Kumar, "EMG signal analysis for identifying walking patterns of normal healthy individuals." Indian journal of biomechanics, Vol. 118, Mar. 2009.
  53. C. H. Lee, S. I. Gang, S. H. Bea, J. W. Gwon, and D. H. Lee, "Study on the wrist direction recognition module using electromyography." Korea journal of welfare rehabilitation engineering, Vol. 7, No. 1, PP. 51-58, Jun. 2013.
  54. L. Francioso, C. De Pascali, I. Farella, C. Martucci, P. Creti, P. Siciliano, and A. Perrone, "Flexible thermoelectric generator for ambient assisted living wearable biometric sensors." Journal of Power Sources, Vol. 196, Issue 6, PP. 3239-3243, Mar. 2011.
  55. J. Ngiam, A. Khosla, M. Kim, J. Nam, H. Lee, and A. Y. Ng, "Multimodal deep learning." Proceedings of the 28th international conference on machine learning (ICML-11), PP. 689-696, 2011.
  56. L. Deng, G. Hinton, and B. Kingsbury, "New types of deep neural network learning for speech recognition and related applications: An overview." Acoustics, speech and signal processing (ICASSP), International conference on. IEEE, PP. 8599-8603, 2013.
  57. A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems, PP. 1097-1105, 2012.
  58. Y. C. Hwang, H. J. Moon, and J. W. Lee, "Face Recognition System Technologies for Authentication System - A Survey", Journal of convergence society for small and medium business, Vol. 5, No. 3, PP. 9-13, 2015.
  59. J. I. Lee, "Convergent Case Study of Research and Education: Internet of Things Based Wireless Device Forming Research." Journal of the korea convergence society, Vol. 6, No. 4, PP. 1-7, 2015.
  60. S. H. Lee and D. W. Lee, "On Issue and Outlook of wearable Computer based on Technology in Convergence", Journal of the korea convergence society, Vol. 6, No. 3, PP. 73-78, 2015.
  61. Y. J. Lee and Y. S. Choi, "Design and Implementation of Wearable Device using Lithium Polymer consist of Peltier", Journal of convergence society for small and medium business, Vol. 5, No. 2, PP. 15-20. 2015.

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