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Self-powered SoC platform for analys...

Saleh, Hani.

Self-powered SoC platform for analysis and prediction of cardiac arrhythmias

Record Type:	Electronic resources : Monograph/item
Title/Author:	Self-powered SoC platform for analysis and prediction of cardiac arrhythmiasby Hani Saleh ... [et al.].
other author:	Saleh, Hani.
Published:	Cham :Springer International Publishing :2018.
Description:	xvi, 74 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Heart rate monitoring.
Online resource:	http://dx.doi.org/10.1007/978-3-319-63973-4
ISBN:	9783319639734$q(electronic bk.)

Self-powered SoC platform for analysis and prediction of cardiac arrhythmias
Self-powered SoC platform for analysis and prediction of cardiac arrhythmias[electronic resource] /by Hani Saleh ... [et al.]. - Cham :Springer International Publishing :2018. - xvi, 74 p. :ill., digital ;24 cm. - Analog circuits and signal processing,1872-082X. - Analog circuits and signal processing..

Introduction -- Literature Review -- System Design and Development -- Hardware Design and Implementation -- Performance and Result -- Conclusions -- Bibliography -- Index.

This book presents techniques necessary to predict cardiac arrhythmias, long before they occur, based on minimal ECG data. The authors describe the key information needed for automated ECG signal processing, including ECG signal pre-processing, feature extraction and classification. The adaptive and novel ECG processing techniques introduced in this book are highly effective and suitable for real-time implementation on ASICs. Provides a full overview of ECG signal processing basics and contemporary advances in the field; Introduces a new set of novel ECG signal features for automated ECG signal analysis; Enables readers to invent new ECG signal features and determine if they can be effective in predicting or diagnosing cardiac arrhythmias and related disorders; Demonstrates results, supported by silicon validation and real-chip tape-outs.

ISBN: 9783319639734$q(electronic bk.)

Standard No.: 10.1007/978-3-319-63973-4doiSubjects--Topical Terms:

801311
Heart rate monitoring.

LC Class. No.: RG628.3.H42

Dewey Class. No.: 618.320754

Self-powered SoC platform for analysis and prediction of cardiac arrhythmias
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245 0 0 $a Self-powered SoC platform for analysis and prediction of cardiac arrhythmias $h [electronic resource] / $c by Hani Saleh ... [et al.].
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300 $a xvi, 74 p. : $b ill., digital ; $c 24 cm.
490 1 $a Analog circuits and signal processing, $x 1872-082X
505 0 $a Introduction -- Literature Review -- System Design and Development -- Hardware Design and Implementation -- Performance and Result -- Conclusions -- Bibliography -- Index.
520 $a This book presents techniques necessary to predict cardiac arrhythmias, long before they occur, based on minimal ECG data. The authors describe the key information needed for automated ECG signal processing, including ECG signal pre-processing, feature extraction and classification. The adaptive and novel ECG processing techniques introduced in this book are highly effective and suitable for real-time implementation on ASICs. Provides a full overview of ECG signal processing basics and contemporary advances in the field; Introduces a new set of novel ECG signal features for automated ECG signal analysis; Enables readers to invent new ECG signal features and determine if they can be effective in predicting or diagnosing cardiac arrhythmias and related disorders; Demonstrates results, supported by silicon validation and real-chip tape-outs.
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650 0 $a Cardiovascular instruments, Implanted. $3 338155
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