Computational Intelligence Bio Eng

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.

Introduction
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

Index