Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias
Saleh, Hani
Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias by Hani Saleh, Nourhan Bayasi, Baker Mohammad, Mohammed Ismail. - 1 recurso en línea (XVI, 74 páginas 46 ilustraciones, 34 ilustraciones a color) - Analog Circuits and Signal Processing, 1872-082X Engineering (Springer-11647) .
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.
9783319639734
10.1007/978-3-319-63973-4 doi
Electrocardiografía
RG628.3 2018 EB
Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias by Hani Saleh, Nourhan Bayasi, Baker Mohammad, Mohammed Ismail. - 1 recurso en línea (XVI, 74 páginas 46 ilustraciones, 34 ilustraciones a color) - Analog Circuits and Signal Processing, 1872-082X Engineering (Springer-11647) .
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.
9783319639734
10.1007/978-3-319-63973-4 doi
Electrocardiografía
RG628.3 2018 EB