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171103 ||| eng |
| 020 |
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|a 9783319639734
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| 100 |
1 |
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|a Saleh, Hani
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| 245 |
0 |
0 |
|a Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias
|h Elektronische Ressource
|c by Hani Saleh, Nourhan Bayasi, Baker Mohammad, Mohammed Ismail
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| 250 |
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|a 1st ed. 2018
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2018, 2018
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| 300 |
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|a XVI, 74 p. 46 illus., 34 illus. in color
|b online resource
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| 505 |
0 |
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|a Introduction -- Literature Review -- System Design and Development -- Hardware Design and Implementation -- Performance and Result -- Conclusions -- Bibliography -- Index
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| 653 |
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|a Biomedical engineering
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| 653 |
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|a Biomedical Engineering and Bioengineering
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| 653 |
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|a Electronic circuits
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| 653 |
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|a Processor Architectures
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| 653 |
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|a Microprocessors
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| 653 |
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|a Electronic Circuits and Systems
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| 653 |
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|a Computer architecture
|
| 700 |
1 |
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|a Bayasi, Nourhan
|e [author]
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| 700 |
1 |
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|a Mohammad, Baker
|e [author]
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| 700 |
1 |
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|a Ismail, Mohammed
|e [author]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
|
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|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
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|a Analog Circuits and Signal Processing
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| 028 |
5 |
0 |
|a 10.1007/978-3-319-63973-4
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-63973-4?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 6,213,815
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| 520 |
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|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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