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 novel ECG processing techniques introduced in this book are highly effective and suitable for real-time implementation on ASICs. Read More

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. Read Less

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  	This is a digital edition of this title. Rent eBook (5 Options) 30 Day Rental: $41.70 (Expires Jun 28, 2024) 60 Day Rental: $55.60 (Expires Jul 28, 2024) 90 Day Rental: $69.50 (Expires Aug 27, 2024) 120 Day Rental: $83.40 (Expires Sep 26, 2024) 180 Day Rental: $90.35 (Expires Nov 25, 2024) Title: Self-Powered Soc Platform for Analysis and Prediction of Cardiac Arrhythmias by Hani Saleh; Nourhan Bayasi; Baker Mohammad; Mohammed Ismail Publisher: Springer Nature Print ISBN: 9783319639727, 3319639722 eText ISBN: 9783319639734 Edition: 2017 2018 edition Format: PDF eBook	$41.70 Rent eBook This is a digital eBook Nothing will be shipped to you Works with web browsers and the VitalSource app on all Windows, Mac, Chromebook, Kindle Fire, iOS, and Android devices Most eBooks are returnable within 14 days of purchase Questions? See our eBook FAQ