Computational Intelligence in Biomedical Engineering: 1st Edition (Hardback) book cover

Computational Intelligence in Biomedical Engineering

1st Edition

By Rezaul Begg, Daniel T.H. Lai, Marimuthu Palaniswami

CRC Press

392 pages | 152 B/W Illus.

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Hardback: 9780849340802
pub: 2007-12-04
eBook (VitalSource) : 9780429127199
pub: 2007-12-04
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As in many other fields, biomedical engineers benefit from the use of computational intelligence (CI) tools to solve complex and non-linear problems. The benefits could be even greater if there were scientific literature that specifically focused on the biomedical applications of computational intelligence techniques. The first comprehensive field-specific reference, Computational Intelligence in Biomedical Engineering provides a unique look at how techniques in CI can offer solutions in modelling, relationship pattern recognition, clustering, and other problems particular to the field.

The authors begin with an overview of signal processing and machine learning approaches and continue on to introduce specific applications, which illustrate CI’s importance in medical diagnosis and healthcare. They provide an extensive review of signal processing techniques commonly employed in the analysis of biomedical signals and in the improvement of signal to noise ratio. The text covers recent CI techniques for post processing ECG signals in the diagnosis of cardiovascular disease and as well as various studies with a particular focus on CI’s potential as a tool for gait diagnostics.

In addition to its detailed accounts of the most recent research, Computational Intelligence in Biomedical Engineering provides useful applications and information on the benefits of applying computation intelligence techniques to improve medical diagnostics.

Table of Contents


Biomedical Systems

Bioelectric Signals and Electrode Theory

Signal Processing and Feature Extraction

Computational Intelligence Techniques

Chapter Overview

Book Usage

Biomedical Signal Processing

Signals and Signal Systems

Signal Transforms

Spectral Analysis and Estimation

Analog Filters

Digital Filters

Adaptive Filters

Computational Intelligence Techniques

Computational Intelligence: A Fusion of Paradigms

Artificial Neural Networks

Support Vector Machines

Hidden Markov Models

Fuzzy Sets and Fuzzy Logic

Hybrid Systems

Computational Intelligence in Cardiology and Heart Disease Diagnosis

The Human Heart

The ECG Waveform

The Electrocardiogram

Cardiovascular Diseases

ECG Feature Extraction Methods

Computational Intelligence for Diagnosis of Cardiovascular Diseases

Computational Intelligence in Analysis of Electromyography Signals

The Human Muscle Physiology

Neuromuscular Disorders

The Electromyograph

Electromyograph Signal-Processing Methods

Classification of Neuromuscular Disease

Prostheses and Orthotics

Computational Intelligence in Electroencephalogram Analysis

Computational Intelligence in EEG Analysis

Brain–Computer Interfaces

Computational Intelligence in Gait and Movement Pattern Analysis

Gait Measurement and Analysis Techniques

Gait in Various Populations

CI Techniques in Gait Analysis

Summary and Future Trends

Overview of Progress

Future Challenges and Research Areas

Emerging and Future Technologies in Healthcare


Subject Categories

BISAC Subject Codes/Headings:
MEDICAL / Biotechnology
MEDICAL / Biostatistics
SCIENCE / Life Sciences / Biology / General