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.
Supplemental Material
- 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 ScholarCross Ref
- G. Bodenstein and H. Praetorius. Feature Extraction from the Electroencephalogram by Adaptive Segmentation. Proceedings of the IEEE, 65:642--652, May 1977.Google ScholarCross Ref
- M. M. Broffman. Instrument-Assisted Pulse Evaluation in the Acupuncture Practice. American Journal of Acupuncture, 14(3):255--259, 1986.Google Scholar
- 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 Scholar
- 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 ScholarDigital Library
- 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 ScholarDigital Library
- Y. Feng. Chinese Journal of Biomedical Engineering. 1983.Google Scholar
- B. Flaws. The Secret of Chinese Pulse Diagnosis. Blue Poppy Press, 1995.Google Scholar
- 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 ScholarCross Ref
- 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 Scholar
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- S. He et al. Objectifying of Pulse-taking. Journal of Japanese Eastern Medicine Society, 27(4):7, 1977.Google Scholar
- 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 Scholar
- 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 ScholarCross Ref
- 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 Scholar
- 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 ScholarDigital Library
- S. Li. Pulse Diagnosis. Paradigm Publications, translated by huynh hk edition, 1985.Google Scholar
- 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 ScholarDigital Library
- 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 ScholarDigital Library
- 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 ScholarCross Ref
- 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 ScholarDigital Library
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 Scholar
- 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 ScholarCross Ref
- 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 ScholarDigital Library
- 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 ScholarDigital Library
- 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 ScholarCross Ref
- 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 Scholar
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 Scholar
- 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 ScholarDigital Library
- L. S. Xu et al. Objectifying Researches on Traditional Chinese Pulse Diagnosis. Informatica Medica Slovenica, 2:56--63, Aug. 2003.Google Scholar
- 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 ScholarCross Ref
- W. Yang, L. Zhang, and D. Zhang. Wrist-Pulse Signal Diagnosis Using ICPulse. In Proceedings of the IEEE ICBBE, 2009.Google Scholar
- V. D. J. Yoo. Elektronishe Puisographie-eine Hene Diegno-Stishe Moghichkeit auf Chrobobiorhythmischer. Grundlage Akupunktur Theorie und Paris, 3:90, 1980.Google Scholar
- 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 Scholar
- 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 ScholarCross Ref
Index Terms
- EasiCPRS: design and implementation of a portable Chinese pulse-wave retrieval system
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