Skip to main content
SpringerLink
Log in

Human respiration rate estimation using ultra-wideband distributed cognitive radar system

  • Published:
International Journal of Automation and Computing Aims and scope Submit manuscript

Abstract

It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare, rescue, and security applications. In this paper, we first present a multi-ray propagation model for UWB signal, which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces. A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment. This model enables replication of time-varying multipath profiles due to the displacement of a human chest. Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate. The analytical framework can serve as a basis in the planning and evaluation of future measurement programs. We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. R. N. Anderson. A Method for Constructing Complete Annual U.S. Life Tables. National Center for Health Statistics, Vital Health Statistics, vol. 2, no. 129, pp. 1–28, 1999.

    Google Scholar 

  2. A. N. Vgontzas, A. Kales. Sleep and its Disorders. Annual Review of Medicine, vol. 50, no. 1, pp. 387–400, 1999.

    Article  Google Scholar 

  3. F. Michahelles, R. Wicki, B. Shiele. Less Contact: Heartrate Detection without Even Touching the User. In Proceedings of the 8th International Symposium on Wearable Computers, IEEE Press, Washington DC, USA, pp. 4–7, 2004.

    Chapter  Google Scholar 

  4. E. M. Staderini. UWB Radars in Medicine. IEEE Aerospace and Electronic Systems Magazine, vol. 17, no. 1, pp. 13–18, 2002.

    Article  Google Scholar 

  5. G. Ossberger, T. Buchegger, E. Schimback, A. Stelzer, R. Weigel. Non-invasive Respiratory Movement Detection and Monitoring of Hidden Humans Using UltraWideband Pulse Radar. In Proceedings of International Workshop on Ultra Wideband Systems Joint with Conference on Ultrawideband Systems and Technologies, IEEE Press, Kyoto, Japan, pp. 395–399, 2004.

    Chapter  Google Scholar 

  6. I. Y. Immoreev, S. Samkov, T.H. Tao. Short-distance Ultra Wideband Radars. IEEE Aerospace and Electronic Systems Magazine, vol. 20, no. 6, pp. 9–14, 2005.

    Article  Google Scholar 

  7. S. Venkatesh, C. R. Anderson, N. V. Rivera, R.M. Buehrer. Implementation and Analysis of Respiration-rate Estimation Using Impulse-based UWB. In Proceedings of IEEE Military Communications Conference, IEEE Press, New Jersey, USA, pp. 3314–3320, 2005.

    Google Scholar 

  8. Y. Chen, E. Gunawan, K. S. Low, Y. Kim, C. B. Soh, A. R. Leyman, L. L. Thi. Non-invasive Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System. In Proceedings of IEEE International Conference of the Engineering in Medicine and Biology Society, IEEE Press, New York, USA, pp. 920–923, 2006.

    Google Scholar 

  9. L. W. Chua. A New UWB Antenna With Excellent Time Domain Characteristics. In Proceedings of European Conference on Wireless Technology, Paris, France, pp. 531–534, 2005.

  10. J. Y. Lee, S. Yoo. Large Error Performance of UWB Ranging in Multipath and Multiuser Environments. IEEE Transactions on Microwave Theory and Techniques, vol. 54, no. 4, pp. 1887–1895, 2006.

    Article  Google Scholar 

  11. S. Gabriel, R.W. Lau, C. Gabriel. The Dielectric Properties of Biological Tissues: III. Parametric Models for the Dielectric Spectrum of Tissues. Physics in Medicine and Biology, vol. 41, no. 11, pp. 2271–2293, 1996.

    Article  Google Scholar 

  12. Y. Chen, V. K. Dubey. Accuracy of Geometric Channelmodeling Methods. IEEE Transactions on Vehicular Technology, vol. 53, no. 1, pp. 82–93, 2004.

    Article  Google Scholar 

  13. F. Amoroso, W. W. Jones. Geometric Model for DSPN Satellite Reception in the Dense Scatterer Mobile Environment. IEEE Transactions on Communications, vol. 41, no. 3, pp. 450–453, 1993.

    Article  Google Scholar 

  14. B. Alavi, K. Pahlavan. Modeling of the Distance Error for Indoor Geolocation. In Proceedings of IEEE Wireless Communications and Networking Conference, IEEE Press, Louisiana, USA, pp. 668–672, 2003.

    Google Scholar 

  15. B. Alavi, K. Pahlavan. Bandwidth Effect on Distance Error Modeling for Indoor Geolocation. In Proceedings of International Symposium on Personal, Indoor and Mobile Radio Communications, IEEE Press, Beijing, PRC, pp. 2198–2202, 2003.

    Google Scholar 

  16. B. Denis, N. Daniele. NLOS Ranging Error Mitigation in a Distributed Positioning Algorithm for Indoor UWB Ad-hoc Networks. In Proceedings of IEEE International Workshop on Wireless Ad-hoc Networks, IEEE Press, Oulu, Finland, pp. 356–360, 2004.

    Chapter  Google Scholar 

  17. L. Yang, G. B. Giannakis. Ultra-wideband Communications: An Idea Whose Time Has Come. IEEE Signal Processing Magazine, vol. 21, no. 6, pp. 26–54, 2004.

    Article  Google Scholar 

  18. S. Haykin. Cognitive Radar: A Way of the Future. IEEE Signal Processing Magazine, vol. 23, no. 1, pp. 30–40, 2006.

    Article  Google Scholar 

  19. W. Suwansantisuk, M. Z. Win, L. A. Shepp. On the Performance of Wide-bandwidth Signal Acquisition in Dense Multipath Channels. IEEE Transactions on Vehicular Technology, vol. 54, no. 5, pp. 1584–1594, 2005.

    Article  Google Scholar 

  20. S. M. Kay. Fundamentals of Statistical Signal Processing: Detection Theory, PTR Prentice Hall, 1998.

  21. S. M. Kay. Fundamentals of Statistical Signal Processing: Estimation Theory, PTR Prentice Hall, 1993.

Download references

Author information

Authors and Affiliations

  1. School of Engineering, University of Greenwich, Kent, ME4 4TB, UK

    Yifan Chen & Predrag Rapajic

  2. School of Computer, Electronic and Information, Guangxi University, Nanning, 530004, PRC

    Yifan Chen

Authors
  1. Yifan Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Predrag Rapajic
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yifan Chen.

Additional information

Yifan Chen received the B. Eng. (Hons I) and Ph.D. degrees in electrical and electronic engineering from Nanyang Technological University, Singapore, in 2002 and 2006, respectively. He is presently with the School of Engineering, University of Greenwich, UK, as a lecturer. He is also with the School of Computer, Electronic and Information, Guangxi University, PRC, as an adjunct associate professor.

His research interests include ultra-wideband radar systems for healthcare applications including microwave imaging of human tissues and non-contact vital-signs monitoring, statistical modeling of mobile radio channels, and wireless communications and geolocation systems.

Predrag Rapajic received his B.Eng. in telecommunications, in 1982 (gold medal) and M.Eng. in telecommunications, in 1988. He received his Ph.D. degree from the University of Sydney, Australia, 1994 for his thesis “Coding and Equalization in Telecommunications Systems”. Since 1995, he has held full time academic posts at the three out of four highest ranked Australian Universities: the University of Sydney, the Australian National University and the University of New South Wales. Until his latest full time industrial post in 1996, after which he began his full time commitment to academia, he provided in excess of 10 years of full time service to various industrial organizations. Since July 2005, he has held chair of Communication Systems at the School of Engineering, University of Greenwich, UK. He is internationally known for his contribution to the area of mobile communications, in particular for his pioneering contribution to the concept of adaptive multi-user detection.

His research interests include mobile communication system, adaptive multi-user detection, equalization, error control coding, and multi-user information theory.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, Y., Rapajic, P. Human respiration rate estimation using ultra-wideband distributed cognitive radar system. Int. J. Autom. Comput. 5, 325–333 (2008). https://doi.org/10.1007/s11633-008-0325-3

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11633-008-0325-3

Keywords

Search

Navigation