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: Biomedical Signal Processing
    sub title: Advances in Theory, Algorithms and Applications
  name:
    name part: Naik, Ganesh.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: si
    date issued: 2020
    edition: 1st ed. 2020.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (X, 432 pages 237 illustrations, 125 illustrations in color.)
  abstract: This book reports on the latest advances in the study of biomedical signal processing, and discusses in detail a number of open problems concerning clinical, biomedical and neural signals. It methodically collects and presents in a unified form the research findings previously scattered throughout various scientific journals and conference proceedings. In addition, the chapters are self-contained and can be read independently. Accordingly, the book will be of interest to university researchers, R&D engineers and graduate students who wish to learn the core principles of biomedical signal analysis, algorithms, and applications, while also offering a valuable reference work for biomedical engineers and clinicians who wish to learn more about the theory and recent applications of neural engineering and biomedical signal processing. .
  table of contents: Surface Electromyography (EMG) Signal Processing, Classification, and Practical Considerations -- Estimation of ankle joint torque and angle based on S-EMG signal for assistive rehabilitation robots -- Force Myography and its Application to Human Locomotion -- Comparison of Independence of Triceps Brachii and Biceps Brachii between Paretic and Non-Paretic side during different MVCs-A case study -- An EEG brain-computer interface to classify motor imagery signals.
  note: edited by Ganesh Naik.
  subject:
    topic: Biomedical engineering
  subject:
    topic: Signal processing
  subject:
    topic: Image processing
  subject:
    topic: Speech processing systems
  subject:
    topic: Pattern recognition
  subject:
    topic: Computational intelligence
  subject:
    topic: Computer mathematics
  subject:
    topic: Artificial intelligence
  subject:
    topic: Biomedical Engineering and Bioengineering
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Pattern Recognition
  subject:
    topic: Computational Intelligence
  subject:
    topic: Computational Mathematics and Numerical Analysis
  subject:
    topic: Artificial Intelligence
  classification: R856-857
  classification: HC79.E5
  classification: GE220
  classification: 610.28
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: Series in BioEngineering
  identifier: 9789811390975
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 191112
    record change date: 20230330185438.0
    record identifier: in00004384925