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001 9910299295403321
005 20200705061528.0
010   $a981-10-4044-3
024 7 $a10.1007/978-981-10-4044-3
035   $a(CKB)4100000006671781
035   $a(MiAaPQ)EBC5516998
035   $a(DE-He213)978-981-10-4044-3
035   $a(PPN)230536328
035   $a(EXLCZ)994100000006671781
100   $a20180914d2018      u|             0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aComputational Pulse Signal Analysis$b[electronic resource] /$fby David Zhang, Wangmeng Zuo, Peng Wang
205   $a1st ed. 2018.
210  1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2018.
215   $a1 online resource (328 pages)
311   $a981-10-4043-5 
327   $a1. Introduction: Computational Pulse Diagnosis -- 2. Compound Pressure Signal Acquisition -- 3. Pulse Signal Acquisition Using Multi-Sensors -- 4. Baseline Wander Correction in Pulse Waveforms Using Wavelet-Based Cascaded Adaptive Filter -- 5. Detection of Saturation And Artifact -- 6. Optimized Preprocessing Framework for Wrist Pulse Analysis -- 7. Arrhythmic Pulses Detection -- 8. Spatial and Spectrum Feature Extraction -- 9. Generalized Feature Extraction for Wrist Pulse Analysis: from 1-D Time Series to 2-D Matrix -- 10. Characterization of Inter-Cycle Variations for Wrist Pulse Diagnosis -- 11. Edit Distance for Pulse Diagnosis -- 12. Modified Gaussian Models and Fuzzy C-Means -- 13. Modified Auto-Regressive Models -- 14. Combination of Heterogeneous Features for Wrist Pulse Blood Flow Signal Diagnosis via Multiple Kernel Learning -- 15. Comparison of Three Different Types of Wrist Pulse Signals -- 16. Comparison Between Pulse And Ecg -- 17. Disscusion and Future Work.
330   $aThis book describes the latest advances in pulse signal analysis and their applications in classification and diagnosis. First, it provides a comprehensive introduction to useful techniques for pulse signal acquisition based on different kinds of pulse sensors together with the optimized acquisition scheme. It then presents a number of preprocessing and feature extraction methods, as well as case studies of the classification methods used. Lastly it discusses some promising directions for the future study and clinical applications of pulse signal analysis. The book is a valuable resource for researchers, professionals and postgraduate students working in the field of pulse diagnosis, signal processing, pattern recognition and biometrics. It is also useful for those involved in interdisciplinary research.
606   $aPattern recognition
606   $aSignal processing
606   $aImage processing
606   $aSpeech processing systems
606   $aHealth informatics
606   $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
606   $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051
606   $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/H28009
615  0$aPattern recognition.
615  0$aSignal processing.
615  0$aImage processing.
615  0$aSpeech processing systems.
615  0$aHealth informatics.
615 14$aPattern Recognition.
615 24$aSignal, Image and Speech Processing.
615 24$aHealth Informatics.
676   $a610.9515
700   $aZhang$b David$4aut$4http://id.loc.gov/vocabulary/relators/aut$0763056
702   $aZuo$b Wangmeng$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aWang$b Peng$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910299295403321
996   $aComputational Pulse Signal Analysis$92281692
997   $aUNINA