Self-powered SoC Platform for Analysis and Prediction of Cardiac Arrhythmias [Hardcover]

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.

Hani Saleh is an Associate professor of electronic engineering at Khalifa University (KU), he joined KU since Jan, 2012. He is a co-founder and an active member in KSRC (Khalifa University Research Center) where he leads a project for the development of wearable blood glucose monitor SOC and a mobile surveillance SOC and safe exercise monitoring device. Hani published 90 articles in peer-reviewed journals and conferences, he has 8 issued US patents and 9 pending patent applications. Hani has a total of 19 years of industrial experience in ASIC chip design, microprocessor design, DSP core design, graphics core design and embedded system design. His experience spans DSP core design, microprocessor peripherals design, microprocessors and graphics core deign. Prior to joining Khalifa University he worked as a Senior Chip Designer (Technical Lead) at Apple incorporation; where he worked on the design and implementation of Apple next generation graphics cores for its mobile products (iPad, iPhone, &etc.), prior to joining Apple, he worked for several leading semiconductor companies including Intl(