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Autor(en): 
  • Sandro Augusto Pavlik Haddad
  • Wouter A Serdijn
  • Ultra Low-Power Biomedical Signal Processing: An Analog Wavelet Filter Approach for Pacemakers 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

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    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  April 2009  
    Genre:  Naturwissensch., Medizin, Technik 
    ISBN:  9781402090721 
    EAN-Code: 
    9781402090721 
    Verlag:  Springer Nature Singapore 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Analog Circuits and Signal Processing  
    Dimensionen:  H 243 mm / B 164 mm / D 22 mm 
    Gewicht:  484 gr 
    Seiten:  215 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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 required signal processing, taking into account the limitations imposed by an implantable device.

      
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