Cargando…

Ultra Low-Power Biomedical Signal Processing An Analog Wavelet Filter Approach for Pacemakers /

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 electrom...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Haddad, Sandro Augusto Pavlik (Autor), Serdijn, Wouter A. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Dordrecht : Springer Netherlands : Imprint: Springer, 2009.
Edición:1st ed. 2009.
Colección:Analog Circuits and Signal Processing,
Temas:
Acceso en línea:Texto Completo

MARC

LEADER 00000nam a22000005i 4500
001 978-1-4020-9073-8
003 DE-He213
005 20220118032852.0
007 cr nn 008mamaa
008 100301s2009 ne | s |||| 0|eng d
020 |a 9781402090738  |9 978-1-4020-9073-8 
024 7 |a 10.1007/978-1-4020-9073-8  |2 doi 
050 4 |a R856-857 
072 7 |a MQW  |2 bicssc 
072 7 |a TEC059000  |2 bisacsh 
072 7 |a MQW  |2 thema 
082 0 4 |a 610.28  |2 23 
100 1 |a Haddad, Sandro Augusto Pavlik.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Ultra Low-Power Biomedical Signal Processing  |h [electronic resource] :  |b An Analog Wavelet Filter Approach for Pacemakers /  |c by Sandro Augusto Pavlik Haddad, Wouter A. Serdijn. 
250 |a 1st ed. 2009. 
264 1 |a Dordrecht :  |b Springer Netherlands :  |b Imprint: Springer,  |c 2009. 
300 |a X, 215 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Analog Circuits and Signal Processing,  |x 2197-1854 
505 0 |a 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. 
520 |a 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. 
650 0 |a Biomedical engineering. 
650 0 |a Signal processing. 
650 1 4 |a Biomedical Engineering and Bioengineering. 
650 2 4 |a Signal, Speech and Image Processing . 
700 1 |a Serdijn, Wouter A.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9789048180615 
776 0 8 |i Printed edition:  |z 9781402090806 
776 0 8 |i Printed edition:  |z 9781402090721 
830 0 |a Analog Circuits and Signal Processing,  |x 2197-1854 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-1-4020-9073-8  |z Texto Completo 
912 |a ZDB-2-ENG 
912 |a ZDB-2-SXE 
950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712)