Ultra Low-Power Biomedical Signal Processing

An Analog Wavelet Filter Approach for Pacemakers

By: Sandro Augusto Pavlik Haddad, Wouter A. Serdijn

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Hardcover | 30 April 2009

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215 Pages

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23.5 x 15.5 x 1.42

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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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Introduction
Biomedical signal processing
Biomedical applications of the wavelet transform
Analog versus digital circuitry - a power consumption challenge for biomedical front-ends
Objective and scope of this thesis
Outline
The Evolution of Pacemakers: An Electronics Perspective
The Heart
Cardiac Signals
The history and development of cardiac pacing
New Features in Modern Pacemakers
Summary and Conclusions
Wavelet versus Fourier analysis
Introduction
Fourier transform
Windowing function
Wavelet transform
Signal Processing with Wavelet Transform
Low-power analog wavelet filter design
Conclusions
Analog Wavelet filters: the need for approximation
Introduction
Complex First Order filters
Pad- e Approximation in the Laplace domain
L2 Approximation
Other approaches for Wavelet bases approximation
Discussion
Conclusions
Optimal State Space Descriptions
State space description
Dynamic Range
Sparsity
Sensitivity
Conclusion
Ultra Low-power Integrator Designs
Gm-C filters
Translinear (Log-domain) filters
Class-A log-domain filter design examples
Low-power Class-AB Sinh Integrators
Discussion
Conclusions
Ultra Low-power Biomedical System Designs
Dynamic Translinear Cardiac Sense Amplifier for Pacemakers
QRS-complex wavelet detection using CFOS
Wavelet filter designs
Morlet Wavelet Filter
Conclusions
Conclusions and Future Research
Future Research
High-Performance Analog Delays
Bessel-Thomson approximation
Pad- e approximation
Comparison of Bessel-Thomson and Pad- e approximation delay filters
Gaussian Time-domain impulse-response method
Model reduction - the Balanced Truncation method
Switched-Capacitor Wavelet Filters
Ultra-Wideband Circuit Designs
D.1
D.2
D.3
Summary
Table of Contents provided by Publisher. All Rights Reserved.

Ultra Low-Power Biomedical Signal Processing

An Analog Wavelet Filter Approach for Pacemakers

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Hardcover

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