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Published in:
Introduction: Computational Pulse Diagnosis Read chapter Read first chapter

2018 | OriginalPaper | Chapter

15. Comparison of Three Different Types of Wrist Pulse Signals

Authors : David Zhang, Wangmeng Zuo, Peng Wang

Published in: Computational Pulse Signal Analysis

Publisher: Springer Singapore

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Abstract

By far, a number of sensors have been employed for pulse signal acquisition, which can be grouped into three major categories, i.e., pressure, photoelectric, and ultrasonic sensors. To guide the sensor selection for computational pulse diagnosis, in this chapter, we analyze the physical meanings and sensitivities of signals acquired by these three types of sensors. The dependency and complementarity of the different sensors are discussed from both the perspective of cardiovascular fluid dynamics and comparative experiments by evaluating disease classification performance. Experimental results indicate that each sensor is more appropriate for the diagnosis of some specific disease that the changes of physiological factors can be effectively reflected by the sensor, e.g., ultrasonic sensor for diabetes and pressure sensor for arteriosclerosis, and improved diagnosis performance can be obtained by combining three types of signals.

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previous chapter Combination of Heterogeneous Features for Wrist Pulse Blood Flow Signal Diagnosis via Multiple Kernel Learning
next chapter Comparison Between Pulse and ECG
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Metadata
Title
Comparison of Three Different Types of Wrist Pulse Signals
Authors
David Zhang
Wangmeng Zuo
Peng Wang
Copyright Year
2018
Publisher
Springer Singapore
Book
Computational Pulse Signal Analysis

Print ISBN: 978-981-10-4043-6

Electronic ISBN: 978-981-10-4044-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-4044-3_15

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