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Advanced Biosignal Processing

von Springer-Verlag GmbH

Generally speaking, Biosignals refer to signals recorded from the human body. They can be either electrical (e. g. Electrocardiogram (ECG), Electroencephalogram (EEG), Electromyogram (EMG), etc. ) or non-electrical (e. g. breathing, movements, etc. ). The acquisition and processing of such signals play an important role in clinical routines. They are usually considered as major indicators which provide clinicians and physicians with useful information during diagnostic and monitoring processes. In some applications, the purpose is not necessarily medical. It may also be industrial. For instance, a real-time EEG system analysis can be used to control and analyze the vigilance of a car driver. In this case, the purpose of such a system basically consists of preventing crash risks. Furthermore, in certain other appli- tions,asetof biosignals (e. g. ECG,respiratorysignal,EEG,etc. ) can be used toc- trol or analyze human emotions. This is the case of the famous polygraph system, also known as the "lie detector", the ef ciency of which remains open to debate! Thus when one is dealing with biosignals, special attention must be given to their acquisition, their analysis and their processing capabilities which constitute the nal stage preceding the clinical diagnosis. Naturally, the diagnosis is based on the information provided by the processing system.

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Produktbeschreibung

Generally speaking, Biosignals refer to signals recorded from the human body. They can be either electrical (e. g. Electrocardiogram (ECG), Electroencephalogram (EEG), Electromyogram (EMG), etc. ) or non-electrical (e. g. breathing, movements, etc. ). The acquisition and processing of such signals play an important role in clinical routines. They are usually considered as major indicators which provide clinicians and physicians with useful information during diagnostic and monitoring processes. In some applications, the purpose is not necessarily medical. It may also be industrial. For instance, a real-time EEG system analysis can be used to control and analyze the vigilance of a car driver. In this case, the purpose of such a system basically consists of preventing crash risks. Furthermore, in certain other appli- tions,asetof biosignals (e. g. ECG,respiratorysignal,EEG,etc. ) can be used toc- trol or analyze human emotions. This is the case of the famous polygraph system, also known as the "lie detector", the ef ciency of which remains open to debate! Thus when one is dealing with biosignals, special attention must be given to their acquisition, their analysis and their processing capabilities which constitute the nal stage preceding the clinical diagnosis. Naturally, the diagnosis is based on the information provided by the processing system. 

Inhaltsverzeichnis

Preface: Amine Na‹t-Ali Chapter 1: Biosignals: acquisition and general properties
Amine Na‹t-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, Herv‚ Rix and Gr‚gory Blain Chapter 4: Statistical models based ECG classification
Rodrigo VarejÆo AndreÆo1, J‚r“me 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, C‚dric Duchˆne, 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 Na‹t-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 Duchˆne 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. Na‹t-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 Na‹t-Ali, Emre Zeybek and Xavier Drouot 

Mehr vom Verlag:

Springer-Verlag GmbH

Produktdetails

Medium: Buch
Format: Gebunden
Seiten: XVI, 374
Sprache: Englisch
Erschienen: April 2009
Maße: 242 x 167 mm
Gewicht: 843 g
ISBN-10: 3540895051
ISBN-13: 9783540895053
Verlagsbestell-Nr.: 12111176

Bestell-Nr.: 4753042 
Bestell-Nr. Verlag: 12111176

LIBRI: 7994230
LIBRI-EK*: 122.33 € (23.00%)
LIBRI-VK: 169,99 €
Libri-STOCK: 3
* EK = ohne MwSt.

UVP: 2 
Warengruppe: 16890 

KNO: 22412337
KNO-EK*: 67.41 € (25.00%)
KNO-VK: 171,19 €
KNV-STOCK: 0

KNOABBVERMERK: 2009. xvi, 378 S. 235 mm
KNOMITARBEITER: Herausgeber: Nait-Ali, Amine
Einband: Gebunden
Sprache: Englisch
Beilage(n): HC runder Rücken kaschiert

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