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Computational pulse signal analysis

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Computational pulse signal analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational pulse signal analysisby David Zhang, Wangmeng Zuo, Peng Wang.
作者:	Zhang, David.
其他作者:	Zuo, Wangmeng.
出版者:	Singapore :Springer Singapore :2018.
面頁冊數:	xiv, 328 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Pulse.
電子資源:	https://doi.org/10.1007/978-981-10-4044-3
ISBN:	9789811040443$q(electronic bk.)

Computational pulse signal analysis
Zhang, David.

Computational pulse signal analysis[electronic resource] /by David Zhang, Wangmeng Zuo, Peng Wang. - Singapore :Springer Singapore :2018. - xiv, 328 p. :ill., digital ;24 cm.

1. 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.

This 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.

ISBN: 9789811040443$q(electronic bk.)

Standard No.: 10.1007/978-981-10-4044-3doiSubjects--Topical Terms:

195272
Pulse.

LC Class. No.: RC74

Dewey Class. No.: 616.0754

Computational pulse signal analysis
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505 0 $a 1. 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.
520 $a This 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.
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