Advanced Biosignal Processing -

Advanced Biosignal Processing

Amine Nait-Ali (Herausgeber)

Buch | Softcover
XVI, 378 Seiten
2010 | 1. Softcover reprint of hardcover 1st ed. 2009
Springer Berlin (Verlag)
978-3-642-10045-1 (ISBN)
181,89 inkl. MwSt
This concise book presents the principles of many advanced biosignal processing techniques. The book has been voluntarily structured according to signal categories. This helps the reader to assimilate the techniques dedicated to a given class of biosignals.

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.

Biosignals: Acquisition and General Properties.- Extraction of ECG Characteristics Using Source Separation Techniques: Exploiting Statistical Independence and Beyond.- ECG Processing for Exercise Test.- Statistical Models Based ECG Classification.- Heart Rate Variability Time-Frequency Analysis for Newborn Seizure Detection.- Adaptive Tracking of EEG Frequency Components.- From EEG Signals to Brain Connectivity: Methods and Applications in Epilepsy.- Neural Network Approaches for EEG Classification.- Analysis of Event-Related Potentials Using Wavelet Networks.- Detection of Evoked Potentials.- Visual Evoked Potential Analysis Using Adaptive Chirplet Transform.- Uterine EMG Analysis: Time-Frequency Based Techniques for Preterm Birth Detection.- Pattern Classification Techniques for EMG Signal Decomposition.- Parametric Modeling of Some Biosignals Using Optimization Metaheuristics.- Nonlinear Analysis of Physiological Time Series.- Biomedical Data Processing Using HHT: A Review.- to Multimodal Compression of Biomedical Data.

Erscheint lt. Verlag 19.10.2010
Zusatzinfo XVI, 378 p. 218 illus., 3 illus. in color.
Verlagsort Berlin
Sprache englisch
Maße 155 x 235 mm
Gewicht 585 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik
Medizinische Fachgebiete Innere Medizin Kardiologie / Angiologie
Medizin / Pharmazie Physiotherapie / Ergotherapie Orthopädie
Naturwissenschaften Physik / Astronomie Thermodynamik
Technik
Schlagworte biomedical engineering • classification • detection • ecg • EEG • Elecromyogram • Electrocardiogram • Elektroenzephalografie • Elektroenzephalogram • EMG • Evoked potential • fuzzy • Heuristics • Metaheuristic • Modeling • Network • Optimization • Radiologieinformationssystem • Science • Signal Processing • Wavelets
ISBN-10 3-642-10045-7 / 3642100457
ISBN-13 978-3-642-10045-1 / 9783642100451
Zustand Neuware
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