High Performance and Power Efficient Electrocardiogram Detectors

Ashish Kumar · Manjeet Kumar · Rama S. Komaragiri

2022年10月 · Springer Nature

关于此电子书

This book details the characteristics of an ECG signal through the functionality and electrical activity of the human heart. This book provides a basic introduction and needs for developing implantable cardiac pacemaker systems. This book provides comprehensive details on ECG signal processing techniques that are useful for fast and accurate diagnosis of cardiovascular diseases. The book discusses the characteristics and parameters of a typical ECG signal and various noises that can corrupt an ECG signal. It also covers various challenges involved in different stages of signal acquisition, preprocessing, and detection of an ECG signal. The book also presents a detailed survey of various ECG signal detection and data compression techniques. The book contains detailed information on ECG signals and various noises that corrupt an ECG signal. It also includes de-noising techniques, ECG peak detection techniques, and ECG data compression techniques. It also includes step-by-step details to design various filters in MATLAB. This book, through detailed explanations, provides the reader with necessary information on ECG signal, ECG signal acquisition process, noise removal techniques, and the detection of ECG peaks.

作者简介

Ashish Kumar received the B.Tech. degree in Electronics and Communication Engineering from Kurukshetra University, India, in 2012, the M. Tech degree in VLSI Design from Galgotias University, Uttar Pradesh, India, in 2015, and the Ph.D. degree from the Department of Electronics and Communication Engineering, Bennett University, Greater Noida, India, in 2020. Since 2020, he has been an Assistant Professor in the School of Electronics Engineering, Vellore Institute of Technology, Chennai, India. He authored many research articles in reputed international journals and conferences. His research interests include biomedical systems design, signal analysis, healthcare assistive techniques, and low-power biomedical system design.

Rama Komaragiri received a Ph.D. from the Department of Electrical Engineering and Information Technology, TU Darmstadt, Germany, in 2006. From 2006 to 2009, he worked as a System Expert at Qimonda Technologies GmbH, Dresden, Germany. From 2009 to2016, he was with the Department of Electronics and Communication Engineering, NIT Calicut, where he has been an Associate Professor since 2012. Since 2016, he has been a Professor and Head of the Department of Electronics and Communication Engineering at Bennett University, India. His research interests include biomedical systems, MEMS/NEMS sensors, semiconductor device modeling and simulation, and low-power CMOS VLSI circuit design.

Manjeet Kumar received a B.Tech degree in Electronics and Telecommunication Engineering from Kurukshetra University, Kurukshetra, India, in 2008, an M.Tech degree in Signal Processing from Guru Gobind Singh Indraprastha University, Delhi, India, in 2011, and a Ph.D. degree from the Department of Electronics and Communication Engineering, Netaji Subhas Institute of Technology (NSIT) Delhi, affiliated to University of Delhi, India, in 2017. He served as Assistant Professor in the Department of Electronics and Communication Engineering, Bennett University, Greater Noida, from June 2016 to July 2020. From July 2020, he is working as Assistant Professor in the Electronics and Communication Engineering department at Delhi Technological University, Delhi. He has authored over thirty-five research articles and twenty conference papers in reputed international journals and conferences. He also served as a reviewer in many International Journals. His research interests include Signal Processing, Biomedical Signal Processing, the Internet of Medical Things, Image Processing, Fractional Systems, Optimization Algorithms, and Artificial Intelligence in Healthcare. He was awarded the "Commendable Research Award'' in 2021 by Delhi Technological University, Delhi, India. His last five-year citations are 1071 with h-index 21 and i-10-index 33.