Signal Processing of Random Physiological Signals
Published on 31. December 2007
Book
Paperback/Softback
X, 222 pages
978-3-031-00482-7 (ISBN)
Description
This lecture book is intended to be an accessible and comprehensive introduction to random signal processing with an emphasis on the real-world applications of biosignals. Although the material has been written and developed primarily for advanced undergraduate biomedical engineering students it will also be of interest to engineers and interested biomedical professionals of any discipline seeking an introduction to the field. Within education, most biomedical engineering programs are aimed to provide the knowledge required of a graduate student while undergraduate programs are geared toward designing circuits and of evaluating only the cardiac signals. Very few programs teach the processes with which to evaluate brainwave, sleep, respiratory sounds, heart valve sounds, electromyograms, electro-oculograms, or random signals acquired from the body. The primary goal of this lecture book is to help the reader understand the time and frequency domain processes which may be used and to evaluate random physiological signals. A secondary goal is to learn the evaluation of actual mammalian data without spending most the time writing software programs. This publication utilizes "DADiSP", a digital signal processing software, from the DSP Development Corporation.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
X, 222 p.
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 13 mm
Weight
449 gr
ISBN-13
978-3-031-00482-7 (9783031004827)
DOI
10.1007/978-3-031-01610-3
Schweitzer Classification
Other editions
Additional editions
Charles S. Lessard
Signal Processing of Random Physiological Signals
E-Book
05/2022
Springer
€42.79
Available for download
Person
Charles Lessard, Ph.D., Lt. Colonel, U.S. Air Force (Retired), IEEE Life Fellow, Associate Professor, Biomedical Engineering Department, Texas A&M University. Dr. Lessard received his doctorate in Electrical Engineering from Marquette University in 1972, his master's degree in Electrical Engineering from the Air Force Institute of Technology in 1967 and his bachelor's also in Electrical Engineering from Texas A&M University in 1958. As a U.S. Air Force Pilot, he flew F-86L All Weather Interceptors and B-52 Strategic Bombers. He was a Lead Engineer and scientist with the School of Aerospace Medicine and the AF Medical Research Laboratories before serving as the overseas Program Manager and Spain's Field Office director in the installation and testing of Spain's Air Defense system. He joined the Texas A&M Engineering faculty in 1981 as an Assistant Professor after retiring from the Air Force in July 1981. Dr. Lessard has served as an Adjunct Professor with the Air Force Institute of Technology, Electrical Engineering, Assistant Professor, Night Division, San Antonio College, Assistant Professor, Night Division, St. Philips College and Adjunct Professor, Physical Therapy, Texas Women's University. Dr. Lessard specializes in physiological signal processing, design of virtual medical instrumentation, control systems, noninvasive physiological measurements, vital signs, nystagmus, sleep and performance decrement, spatial disorientation, acceleration (G)-induced loss of consciousness (G-LOC), and neural network analysis.
Content
Biomedical Engineering Signal Analysis.- System Classification.- Classification of Signals.- Basis Functions and Signal Representation.- Data Acquisition Process.- Sampling Theory and Analog-to-Digital Conversion.- Stationarity and Ergodic Random Processes.- Nonparametric Statistic and the Runs Test for Stationarity.- Correlation Functions.- Convolution.- Digital Filters.- Fourier Series: Trigonometric.- Fast Fourier Transform.- Truncation of the Infinite Fourier Transform.- Spectral Analysis.- Window Functions and Spectral Leakage.- Transfer Function Via Spectral Analysis.- Coherence Function from Spectral Analysis.- Error in Random Data Estimate Analysis (Information Is Paraphrased from Bendat & Piersol).