Advanced Biosignal Processing / Edition 1

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As emphasized by the book's title, "Advanced Biosignal Processing", which could also, implicitly be read as: "Advanced Digital Signal Processing Techniques applied on Biosignals"; the purpose is to provide, in some way, an in-depth consideration of the particular orientations regarding the way one can process various specific classes of biosignals; in particular bipotentials, using various signal processing tools.

After an important chapter introducing major bipotential properties and acquisition system principles, the text is structured around four specific sections. Each section concerns one of the most intensively used biosignals in the clinical routine, namely the Electrocardiogram (ECG), the Electrocardiogram (EEG), Evoked Potentials (EPs) and the Electromyogram (EMG). In this context, advanced tools will be considered such as: Estimation, Adaptive techniques, Time-Frequency analysis, Wavelets, Statistical models, Empirical Mode Decomposition, Neural Networks, modeling, Optimization as well as some hybrid approaches including Wavelet Networks and Compression schemes.

The four final chapters address various specific techniques, mainly suited to processing a large panel of biosignals, including non-electrical signals. The epilogue of this book deals with a joint processing approach of biosignals and medical images for the purpose of multimodal compression.

Instead of organizing the chapters into successive approaches, this book has been deliberately structured according to signal categories. We believe that this configuration will help the reader, interested in a specific field to deal directly with the signals in question. In addition, some of the illustratedsignals are available for download from the "Medical Database for the Evaluation of Image and Signal Processing Algorithms" (MeDEISA), accessible at

Finally, we would like to point out that this book is intended for final year undergraduate students, postgraduate students, engineers and researchers in biomedical engineering and applied digital signal processing.

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Product Details

  • ISBN-13: 9783540895053
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 3/1/2009
  • Edition description: 2009
  • Edition number: 1
  • Pages: 378
  • Product dimensions: 9.40 (w) x 6.40 (h) x 1.10 (d)

Table of Contents

Preface: Amine Naït-Ali

Chapter 1: Biosignals: acquisition and general properties
Amine Naït-Ali and Patrick Karasinski

Chapter 2: Extraction of ECG characteristics using source separation techniques
Vicente Zarzozo

Chapter 3: ECG processing for exercise test
Olivier Meste, Hervé Rix and Grégory Blain

Chapter 4: Statistical models based ECG classification
Rodrigo Varejão Andreão1, Jérôme Boudy, Bernadette Dorizzi, Jean-Marc Boucher and Salim Graja

Chapter 5: Newborn Seizure Detection Using both the ECG and EEG via the Heart Rate Variability Time-Frequency Analysis
Mostefa Mesbah, Boualem Boashash and Malarvili Balakrishnan

Chapter 6: Adaptive tracking of EEG frequency components
Laurent Uldry, Cédric Duchêne, Yann Prudat, Micah M. Murray, Jean-Marc Vesin

Chapter 7: From EEG signals to brain connectivity: methods and applications in epilepsy
Lotfi Senhadji, K. Ansari-Asl and F. Wendling

Chapter 8: Neural Network approaches for EEG classification
Amitava Chatterje, Amine Naït-Ali and Patrick Siarry

Chapter 9: Analysis of event-related potentials using wavelet networks
Hartmut Heinrich and Hartmut Dickhaus

Chapter 10: Detection of evoked potentials
Peter Husar

Chapter 11: Visual Evoked Potential Analysis Using Adaptive Chirplet Transform
Jie Cui1 and Willy Wong

Chapter 12: EMG analysis: time-frequency based techniques
Mohamad Khalil, Marwa Chendeb, Mohamad Diab, Catherine Marque and Jacques Duchêne

Chapter 13: Pattern Classification Techniques for EMG Decomposition
Sarbast Rasheed and Dan Stashuk

Chapter 14: Parametrical modeling of some biosignals using optimization metaheuristics
Amir Nakib, Amine. Naït-Ali, Virginie Van Wassenhove and Patrick Siarry

Chapter 15: Nonlinear analysis of physiological time series
Anisoara Ionescu and Kamiar Aminian

Chapter 16: Biomedical data processing using HHT: a review
Ming-Chya Wu and Norden Huang

Chapter 17: Multimodal compression of biomedical data
Amine Naït-Ali, Emre Zeybek and Xavier Drouot

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