rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Advanced Biosignal Processing
  name:
    name part: Naït-Ali, Amine.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2009
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 378 p. 218 illus., 3 illus. in color. online resource.
  abstract: Through 17 chapters, this book presents the principle of many advanced biosignal processing techniques. After an important chapter introducing the main biosignal properties as well as the most recent acquisition techniques, it highlights five specific parts which build the body of this book. Each part concerns one of the most intensively used biosignals in the clinical routine, namely the Electrocardiogram (ECG), the Elektroenzephalogram (EEG), the Electromyogram (EMG) and the Evoked Potential (EP). In addition, each part gathers a certain number of chapters related to analysis, detection, classification, source separation and feature extraction. These aspects are explored by means of various advanced signal processing approaches, namely wavelets, Empirical Modal Decomposition, Neural networks, Markov models, Metaheuristics as well as hybrid approaches including wavelet networks, and neuro-fuzzy networks. The last part, concerns the Multimodal Biosignal processing, in which we present two different chapters related to the biomedical compression and the data fusion. Instead organising the chapters by approaches, the present book has been voluntarily structured according to signal categories (ECG, EEG, EMG, EP). This helps the reader, interested in a specific field, to assimilate easily the techniques dedicated to a given class of biosignals. Furthermore, most of signals used for illustration purpose in this book can be downloaded from the Medical Database for the Evaluation of Image and Signal Processing Algorithm. These materials assist considerably the user in evaluating the performances of their developed algorithms. This book is suited for final year graduate students, engineers and researchers in biomedical engineering and practicing engineers in biomedical science and medical physics.
  table of contents: 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.
  note: edited by Amine Naït-Ali.
  subject:
    topic: Engineering
  subject:
    topic: Cardiology
  subject:
    topic: Computer graphics
  subject:
    topic: Biomathematics
  subject:
    topic: Statistical physics
  subject:
    topic: Dynamical systems
  subject:
    topic: Computational intelligence
  subject:
    topic: Biomedical engineering
  subject:
    topic: Engineering
  subject:
    topic: Biomedical Engineering
  subject:
    topic: Cardiology
  subject:
    topic: Computational Intelligence
  subject:
    topic: Statistical Physics, Dynamical Systems and Complexity
  subject:
    topic: Computer Imaging, Vision, Pattern Recognition and Graphics
  subject:
    topic: Physiological, Cellular and Medical Topics
  classification: R856-857
  classification: 610.28
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783540895060
  identifier: http://dx.doi.org/10.1007/978-3-540-89506-0
  record info:
    record creation date: 100301
    record change date: 20151107111253.0
    record identifier: 978-3-540-89506-0