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EasiCPRS: design and implementation of a portable Chinese pulse-wave retrieval system

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Published:01 November 2011Publication History

ABSTRACT

Traditional Chinese Pulse Diagnosis is a convenient and noninvasive method for disease diagnosis and healthcare. We have designed and implemented a Chinese wrist-pulse retrieval system based on the principle of Traditional Chinese Pulse Diagnosis (TCPD), called EasiCPRS. It is designed to be small in size, low in cost, with flexibility in deployment, and simplicity in operation. The contributions of this work are: 1. The wrist-pulse at "cun, guan and chi"points over the radial artery are obtained by applying a moderate and adjustable taking pressure during wrist-pulse retrieval. 2. A wrist-pulse signal conditioning circuit and a robust external taking pressure control algorithm are designed to overcome low signal-to-noise ratio (SNR). 3. A lightweight algorithm for wrist-pulse feature extraction is achieved on a resource-constrained platform to economize energy and bandwidth.

We developed EasiCPRS prototype, trained and verified the performance of the system by collecting and analyzing thousands of wrist-pulse samples from volunteers in a number of different health conditions such as hypertension, pregnancy and so on which were diagnosed by doctors in hospital. The experimental results showed potential usefulness of the system in disease diagnosis and healthcare.

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  1. S. Abhinav, M. Kumar, M. Anand, et al. Yantra: A Robust System Design to Capture the Signals from the Radial Artery for Non-Invasive Diagnosis. In Proceedings of the IEEE ICBBE, pages 1387--1390, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  2. G. Bodenstein and H. Praetorius. Feature Extraction from the Electroencephalogram by Adaptive Segmentation. Proceedings of the IEEE, 65:642--652, May 1977.Google ScholarGoogle ScholarCross RefCross Ref
  3. M. M. Broffman. Instrument-Assisted Pulse Evaluation in the Acupuncture Practice. American Journal of Acupuncture, 14(3):255--259, 1986.Google ScholarGoogle Scholar
  4. B. Thakker and A. L. Vyas. Outlier Pulse Detection and Feature Extraction for Wrist Pulse Analysis. In Proceedings of the IEEE ICBST, pages 173--176, 2009.Google ScholarGoogle Scholar
  5. O. Chipara, C. Lu, T. C. Bailey, and G.-C. Roman. Reliable Clinical Monitoring using Wireless Sensor Networks: Experiences in a Step-down Hospital Unit. In Proceedings of the ACM SenSys, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Y. Chu and A. Ganz. A Mobile Teletrauma System Using 3G Networks. IEEE Transactions on Information Technology in Biomedicine, 8(4):456--462, Dec. 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Y. Feng. Chinese Journal of Biomedical Engineering. 1983.Google ScholarGoogle Scholar
  8. B. Flaws. The Secret of Chinese Pulse Diagnosis. Blue Poppy Press, 1995.Google ScholarGoogle Scholar
  9. S. Fu and S. Lai. A System for Pulse Measurement and Analysis of Chinese Medicine. In Proceedings of the IEEE Engineering in Images of the 21st Century, 1989.Google ScholarGoogle ScholarCross RefCross Ref
  10. T. R. F. Fulford-Jones, G.-Y. Wei, and M. Welsh. A Portable, Low-Power, Wireless Two-Lead EKG System. In Proceedings of the IEEE EMBS, 2004.Google ScholarGoogle Scholar
  11. T. Gao, T. Massey, L. Selavo, et al. The Advanced Health and Disaster Aid Network: A Light-weight Wireless Medical System for Triage. IEEE Transactions on Biomedical Circuits and Systems, Aug. 2007.Google ScholarGoogle ScholarCross RefCross Ref
  12. T. Gao, C. Pesto, L. Selavo, et al. Wireless Medical Sensor Networks in Emergency Response: Implementation and Pilot Results. In Proceedings of the IEEE International Conference on Technologies for Homeland Security, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  13. J. B. Gong, S. L. Lu, R. Wang, and L. Cui. PDhms: Pulse Diagnosis via Wearable Healthcare Sensor Network. In Proceedings of the IEEE ICC, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  14. S. He et al. Objectifying of Pulse-taking. Journal of Japanese Eastern Medicine Society, 27(4):7, 1977.Google ScholarGoogle Scholar
  15. S. Hong, Z. Shu, W. Yan, and R. Chaoshi. Advaned Development of Multi-Information Acquisition System on Pulse Tracing of Traditional Chinese Medicine. Journal of Chinese Medicine, 2007.Google ScholarGoogle Scholar
  16. J. Jing, Y. H. Hu, X. Li, and Z. Huang. Feature Extraction of Pulse Signal based on Hilbert-Huang Transformation and Singular Value Decomposition. In Proceedings of the IEEE ICBBE, pages 1007--1010, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  17. J. P. Killeen, T. C. Chan, C. Buono, W. G. Griswold, and L. A. Lenert. A Wireless First Responder Handheld Device for Rapid Triage, Patient Assessment and Documentation During Mass Casualty Incidents. Journal of the American Medical Informatics Association, 2006.Google ScholarGoogle Scholar
  18. J. Ko, R. Musaloiu-Elefteri, J. H. Lim, et al. MEDiSN: Medical Emergency Detection in Sensor Networks. In Proceedings of the ACM SenSys, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. S. Li. Pulse Diagnosis. Paradigm Publications, translated by huynh hk edition, 1985.Google ScholarGoogle Scholar
  20. Y.-H. Lin, I.-C. Jan, P. C.-I. Ko, et al. A Wireless PDA-Based Physiological Monitoring System for Patient Transport. In IEEE Transaction on Information technology in Biomedicine, volume 8, Dec. 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. S. L. Lu, R. Wang, L. Cui, et al. Wireless Networked Chinese Telemedicine System: Method and Apparatus for Remote Pulse Information Retrieval and Diagnosis. In Proceedings of the IEEE PerCom Workshop, pages 698--703, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. W. Lu, Y. Wang, and W. Wang. Pulse Analysis of Patients with Severe Liver Problems: Computational Methods for Traditional Chinese. IEEE Engineering in Medicine and Biology Magazine, 18(1):73--75, January/February 1999.Google ScholarGoogle ScholarCross RefCross Ref
  23. S. Lukman, Y. He, and S. Hui. Computational Methods for Traditional Chinese Medicine: A Survey. Computer Methods and Programs in Biomedicine, pages 283--294, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. F. Michard et al. Relation Between Respiratory Changes in Arterial Pulse Pressure and Fluid Responsiveness in Septic Patients with Acute Circulatory Failure. American Journal of Respire Circuit Care Medicine, 162:134--138, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  25. S. Narayan and V. Bhargava. Temporal and Spatial Phase Analyses of the Electrocar-diogram Stratify Intra-Atrial and Intra-Ventricular Organization. IEEE Transactions on Biomedical Engineering, 51(10):1749--1764, Oct. 2004.Google ScholarGoogle ScholarCross RefCross Ref
  26. A. Phinyomark, C. Limsakul, and P. Phukpattaranont. A Novel Feature Extraction for Robust EMG Pattern Recognition. Journal of Computing, 1(1):71--80, Dec. 2009.Google ScholarGoogle Scholar
  27. P. Rubel, J. Fayn, G. Nollo, et al. Toward Personal eHealth in Cardiology, Results from the EPI-medics Melemedicine Project. Journal of Electrocardioly, 38(4):100--106, Oct. 2005.Google ScholarGoogle ScholarCross RefCross Ref
  28. M. Sareen, Abhinav, P. Prakash, and S. Anand. Wavelet Decomposition and Feature Extraction from Pulse Signals of the Radial Artery. In Proceedings of the IEEE ICACTE, pages 551--555, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. E. I. Shih, A. H. Shoeb, and J. V. Guttag. Sensor Selection for Energy-Efficient Ambulatory Medical Monitoring. In Proceedings of the MobiSys, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. C.-C. Tyan, S.-H. Liu, J.-Y. Chen, J.-J. Chen, and W.-M. Liang. A Novel Noninvasive Measurement Technique for Analyzing the Pressure Pulse Waveform of the Radial Artery. IEEE Transaction on Biomedical Engineering, 55(1), Jan. 2008.Google ScholarGoogle ScholarCross RefCross Ref
  31. A. Wood, G. Virone, T. Doan, et al. Alarmnet: Wireless Snsor Networks for Assisted-living and Residential Monitoring. Technical report, CS-2006-11, Dec. 2006.Google ScholarGoogle Scholar
  32. C. M. Xia, Y. Li, J. J. Yan, et al. Wrist Pulse Waveform Feature Extraction and Dimension Reduction with Feature Variability Analysis. In Proceedings of the IEEE ICBBE, pages 2048--2051, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  33. C. M. Xia, R. Liu, Y. Li, et al. Wrist Pulse Feature Variability Analysis via Spectral Decomposition. In Proceedings of the IEEE ICBBE, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  34. L. Xu, M. Q.-H. Meng, X. Qi, and K. Wang. Morphology Variability Analysis of Wrist Pulse Waveform for Assessment of Arteriosclerosis Status. Journal of Medical, 34(3):331--339.Google ScholarGoogle Scholar
  35. L. Xu, D. Zhang, K. Wang, N. Lia, and X. Wang. Baseline Wander Correction in Pulse Waveforms using Wavelet-based Cascaded Adaptive Filter. Computers in Biology and Medicine, 37:716--731, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. L. S. Xu et al. Objectifying Researches on Traditional Chinese Pulse Diagnosis. Informatica Medica Slovenica, 2:56--63, Aug. 2003.Google ScholarGoogle Scholar
  37. H. X. Yan, Y. Q. Wang, R. Guo, et al. Feature Extraction and Recognition for Pulse Waveform in Traditional Chinese Medicine based on Hemodynamics. In Proceedings of the IEEE ICCA, pages 972--976, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  38. W. Yang, L. Zhang, and D. Zhang. Wrist-Pulse Signal Diagnosis Using ICPulse. In Proceedings of the IEEE ICBBE, 2009.Google ScholarGoogle Scholar
  39. V. D. J. Yoo. Elektronishe Puisographie-eine Hene Diegno-Stishe Moghichkeit auf Chrobobiorhythmischer. Grundlage Akupunktur Theorie und Paris, 3:90, 1980.Google ScholarGoogle Scholar
  40. Y.-Z. Yoon, M.-H. Lee, and M. K.-S. Soh. Pulse Type Classification by Varying Contact Pressure. IEEE Engineering in Medicine and Biology, pages 106--110, 2000.Google ScholarGoogle Scholar
  41. D.-Y. Zhang, W.-M. Zuo, D. Zhang, et al. Wrist Blood Flow Signal-based Computerized Pulse Diagnosis using Spatial and Spectrum Features. Biomedical Science and Engineering, 3:361--366, 2010.Google ScholarGoogle ScholarCross RefCross Ref

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      • Published in

        cover image ACM Conferences
        SenSys '11: Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
        November 2011
        452 pages
        ISBN:9781450307185
        DOI:10.1145/2070942

        Copyright © 2011 ACM

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        Publication History

        • Published: 1 November 2011

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