Practical Biomedical Signal Analysis Using MATLAB

Book Preface

This book is intended to provide guidance for all those working in the field of biomedical signal analysis and application, in particular graduate students, researchers at the early stages of their careers, industrial researchers, and people interested in the development of the methods of signal processing. The book is different from other monographs, which are usually collections of papers written by several authors. We tried to present a coherent view on different methods of signal processing in the context of their application. Not only do we wish to present the current techniques of biomedical signal processing, we also wish to provide a guidance for which methods are appropriate for the given task and given kind of data.

One of the motivations for writing this book was our longstanding experience in reviewing manuscripts submitted to journals and to conference proceedings, which showed how often methods of signal processing are misused. Quite often, methods, which are sophisticated but at the same time non-robust and prone to systematic errors, are applied to tasks where simpler methods would work better. In this book we aim to show the advantages and disadvantages of differentmethods in the context of their applications.

In the first part of the book we describe the methods of signal analysis, including the most advanced and newest methods, in an easy and accessible way. We omitted proofs of the theorems, sending the reader to the more specialized mathematical literature when necessary. In order to make the book a practical tool we refer to MATLAB R routines when available and to software freely available on the Internet.

In the second part of the bookwe describe the application of the methods presented in the first part of the book to the different biomedical signals: electroencephalogram (EEG), electrocorticogram (ECoG), event-related potential (ERP), electrocardiogram (ECG), heart rate variability signal (HRV), electromyograms (EMG), electroenterograms (EEnG), and electrogastrograms (EGG). The magnetic fields connected with the activity of brain (MEG) and heart (MCG) are considered as well. Methods for acoustic signals—phonocardiograms (PCG) and otoacoustic emissions (OAE) analysis—are also described. Different approaches to solving particular problems are presented with indication to which methods seem to be most appropriate for the given application. Possible pitfalls, which may be encountered in cases of application of the concrete method, are pointed out.