Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias
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...
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| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cham :
Springer International Publishing,
2018.
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| Ausgabe: | 1st ed. 2018. |
| Schriftenreihe: | Analog Circuits and Signal Processing,
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| Schlagworte: | |
| ISBN: | 9783319639734 |
| ISSN: | 1872-082X |
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| 041 | |a eng | ||
| 100 | 1 | |a Saleh, Hani. |4 aut | |
| 245 | 1 | 0 | |a Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias |h [electronic resource] / |c by Hani Saleh, Nourhan Bayasi, Baker Mohammad, Mohammed Ismail. |
| 250 | |a 1st ed. 2018. | ||
| 260 | 1 | |a Cham : |b Springer International Publishing, |c 2018. | |
| 300 | |a XVI, 74 p. 46 illus., 34 illus. in color. |b online resource. | ||
| 490 | 1 | |a Analog Circuits and Signal Processing, |x 1872-082X | |
| 500 | |a Engineering | ||
| 505 | 0 | |a Introduction -- Literature Review -- System Design and Development -- Hardware Design and Implementation -- Performance and Result -- Conclusions -- Bibliography -- Index. | |
| 516 | |a text file PDF | ||
| 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. | ||
| 650 | 0 | |a Electronic circuits. | |
| 650 | 0 | |a Microprocessors. | |
| 650 | 0 | |a Biomedical engineering. | |
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