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Analog-and-algorithm-assisted ultra-...

Pamula, Venkata Rajesh.

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Analog-and-algorithm-assisted ultra-low power biosignal acquisition systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analog-and-algorithm-assisted ultra-low power biosignal acquisition systems/ by Venkata Rajesh Pamula, Chris Van Hoof, Marian Verhelst.
Author:	Pamula, Venkata Rajesh.
other author:	Van Hoof, Chris.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xxiii, 114 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter1: Challenges and Opportunities in Wearable Biomedical Interfaces -- Chapter2: Adaptive Sampling for Ultra-low Power Electrocardiogram (ECG) Readouts -- Chapter3: Introduction to Compressive Sampling (CS) -- Chapter4: Compressed Domain Feature Extraction -- Chapter5: A Low Power Compressive Sampling (CS) Photoplethysmogram (PPG) Read-out With Embedded Feature Extraction -- Chapter6: Conclusions and Future Work.
Contained By:	Springer eBooks
Subject:	Signal processing - Digital techniques -
Online resource:	https://doi.org/10.1007/978-3-030-05870-8
ISBN:	9783030058708

Analog-and-algorithm-assisted ultra-low power biosignal acquisition systems
Pamula, Venkata Rajesh.

Analog-and-algorithm-assisted ultra-low power biosignal acquisition systems[electronic resource] /by Venkata Rajesh Pamula, Chris Van Hoof, Marian Verhelst. - Cham :Springer International Publishing :2019. - xxiii, 114 p. :ill., digital ;24 cm. - Analog circuits and signal processing,1872-082X. - Analog circuits and signal processing..

Chapter1: Challenges and Opportunities in Wearable Biomedical Interfaces -- Chapter2: Adaptive Sampling for Ultra-low Power Electrocardiogram (ECG) Readouts -- Chapter3: Introduction to Compressive Sampling (CS) -- Chapter4: Compressed Domain Feature Extraction -- Chapter5: A Low Power Compressive Sampling (CS) Photoplethysmogram (PPG) Read-out With Embedded Feature Extraction -- Chapter6: Conclusions and Future Work.

This book discusses the design and implementation aspects of ultra-low power biosignal acquisition platforms that exploit analog-assisted and algorithmic approaches for power savings.The authors describe an approach referred to as "analog-and-algorithm-assisted" signal processing.This enables significant power consumption reductions by implementing low power biosignal acquisition systems, leveraging analog preprocessing and algorithmic approaches to reduce the data rate very early in the signal processing chain.They demonstrate savings for wearable sensor networks (WSN) and body area networks (BAN), in the sensors' stimulation power consumption, as well in the power consumption of the digital signal processing and the radio link. Two specific implementations, an adaptive sampling electrocardiogram (ECG) acquisition and a compressive sampling (CS) photoplethysmogram (PPG) acquisition system, are demonstrated. First book to present the so called, "analog-and-algorithm-assisted" approaches for ultra-low power biosignal acquisition and processing platforms; Covers the recent trend of "beyond Nyquist rate" signal acquisition and processing in detail, including adaptive sampling and compressive sampling paradigms; Includes chapters on compressed domain feature extraction, as well as acquisition of photoplethysmogram, an emerging optical sensing modality, including compressive sampling based PPG readout with embedded feature extraction; Discusses emerging trends in sensor fusion for improving the signal integrity, as well as lowering the power consumption of biosignal acquisition systems.

ISBN: 9783030058708

Standard No.: 10.1007/978-3-030-05870-8doiSubjects--Topical Terms:

666781
Signal processing
--Digital techniques

LC Class. No.: TK5102.9 / .P368 2019

Dewey Class. No.: 621.3822

Analog-and-algorithm-assisted ultra-low power biosignal acquisition systems
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100 1 $a Pamula, Venkata Rajesh. $3 3382995
245 1 0 $a Analog-and-algorithm-assisted ultra-low power biosignal acquisition systems $h [electronic resource] / $c by Venkata Rajesh Pamula, Chris Van Hoof, Marian Verhelst.
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300 $a xxiii, 114 p. : $b ill., digital ; $c 24 cm.
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505 0 $a Chapter1: Challenges and Opportunities in Wearable Biomedical Interfaces -- Chapter2: Adaptive Sampling for Ultra-low Power Electrocardiogram (ECG) Readouts -- Chapter3: Introduction to Compressive Sampling (CS) -- Chapter4: Compressed Domain Feature Extraction -- Chapter5: A Low Power Compressive Sampling (CS) Photoplethysmogram (PPG) Read-out With Embedded Feature Extraction -- Chapter6: Conclusions and Future Work.
520 $a This book discusses the design and implementation aspects of ultra-low power biosignal acquisition platforms that exploit analog-assisted and algorithmic approaches for power savings.The authors describe an approach referred to as "analog-and-algorithm-assisted" signal processing.This enables significant power consumption reductions by implementing low power biosignal acquisition systems, leveraging analog preprocessing and algorithmic approaches to reduce the data rate very early in the signal processing chain.They demonstrate savings for wearable sensor networks (WSN) and body area networks (BAN), in the sensors' stimulation power consumption, as well in the power consumption of the digital signal processing and the radio link. Two specific implementations, an adaptive sampling electrocardiogram (ECG) acquisition and a compressive sampling (CS) photoplethysmogram (PPG) acquisition system, are demonstrated. First book to present the so called, "analog-and-algorithm-assisted" approaches for ultra-low power biosignal acquisition and processing platforms; Covers the recent trend of "beyond Nyquist rate" signal acquisition and processing in detail, including adaptive sampling and compressive sampling paradigms; Includes chapters on compressed domain feature extraction, as well as acquisition of photoplethysmogram, an emerging optical sensing modality, including compressive sampling based PPG readout with embedded feature extraction; Discusses emerging trends in sensor fusion for improving the signal integrity, as well as lowering the power consumption of biosignal acquisition systems.
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