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: Ultra Low-Power Biomedical Signal Processing
    sub title: An Analog Wavelet Filter Approach for Pacemakers
  name:
    name part: Haddad, Sandro A. P.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Serdijn, Wouter A.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: ne
    date issued: 2009
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 215 p. online resource.
  abstract: Ultra Low-Power Biomedical Signal Processing describes signal processing methodologies and analog integrated circuit techniques for low-power biomedical systems. Physiological signals, such as the electrocardiogram (ECG), the electrocorticogram (ECoG), the electroencephalogram (EEG) and the electromyogram (EMG) are mostly non-stationary. The main difficulty in dealing with biomedical signal processing is that the information of interest is often a combination of features that are well localized temporally (e.g., spikes) and others that are more diffuse (e.g., small oscillations). This requires the use of analysis methods sufficiently versatile to handle events that can be at opposite extremes in terms of their time-frequency localization. Wavelet Transform (WT) has been extensively used in biomedical signal processing, mainly due to the versatility of the wavelet tools. The WT has been shown to be a very efficient tool for local analysis of non-stationary and fast transient signals due to its good estimation of time and frequency (scale) localizations. Being a multi-scale analysis technique, it offers the possibility of selective noise filtering and reliable parameter estimation. Often WT systems employ the discrete wavelet transform, implemented on a digital signal processor. However, in ultra low-power applications such as biomedical implantable devices, it is not suitable to implement the WT by means of digital circuitry due to the relatively high power consumption associated with the required A/D converter. Low-power analog realization of the wavelet transform enables its application in vivo, e.g. in pacemakers, where the wavelet transform provides a means to extremely reliable cardiac signal detection. In Ultra Low-Power Biomedical Signal Processing we present a novel method for implementing signal processing based on WT in an analog way. The methodology presented focuses on the development of ultra low-power analog integrated circuits that implement the requir…
  table of contents: The Evolution of Pacemakers: An Electronics Perspective -- Wavelet versus Fourier Analysis -- Analog Wavelet Filters: The Need for Approximation -- Optimal State Space Descriptions -- Ultra Low-Power Integrator Designs -- Ultra Low-Power Biomedical System Designs -- Conclusions and Future Research.
  note: by Sandro A. P. Haddad, Wouter A. Serdijn.
  subject:
    topic: Engineering
  subject:
    topic: Biomedical engineering
  subject:
    topic: Engineering
  subject:
    topic: Biomedical Engineering
  subject:
    topic: Signal, Image and Speech Processing
  classification: R856-857
  classification: 610.28
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Analog Circuits and Signal Processing
  identifier: 9781402090738
  identifier: http://dx.doi.org/10.1007/978-1-4020-9073-8
  record info:
    record creation date: 100301
    record change date: 20151204140733.0
    record identifier: 978-1-4020-9073-8