Modelling and Analysis of Active Biopotential Signals in Healthcare, Volume 2: (IPEM-IOP Series in Physics and Engineering in Medicine and Biology)

Biopotential signals are often used by physicians to measure the activities of organs and tissues in the human body. This book describes the sources and characteristics of different biopotential signals and provides an understanding of how a range of signals can be modelled and analysed. The resulting information can be used to assist in the identification of disorders such as epilepsy, schizophrenia, PTSD and heart disease, among others. An emphasis is placed on the real challenges in biopotential signal processing due to the complex and non-stationary nature of signals. Following on from volume one, this book starts with a collection of chapters covering some of the latest developments in electroencephalography (EEG) signal analysis, then moves on to applications of electrocardiography (ECG) and otoscope signals. The volume concludes with a discussion of other monitoring techniques. The chapters include biomedical examples and discussions of how each method can be used to study human organs. It is a valuable guide for all researchers and practitioners who are engaged in studies and research in the area of biomedical signals and their applications. Key Features Modelling and acquisition of biomedical signals for different disorders Implementation of methodologies and their impact on different cases Case studies and research directions Design and simulation examples

Table of Contents:
Preface Acknowledgements Editor biographies Contributors Chapter 1 - Classification of motor-imagery tasks from EEG Signals using the rational dilation wavelet transform Chapter 2 - A deep learning framework for emotion recognition using improved time-frequency image analysis of electroencephalography signals Chapter 3 - Multivariate phase synchrony based on fuzzy statistics: application to PTSD EEG signals Chapter 4 - A study on the influence of meditation and music therapy on the vital parameters of the human body through EEG signal analysis: a review Chapter 5 - Cross-wavelet transform aided focal and non-focal electroencephalography signal classification employing deep feature extraction Chapter 6 - Local binary pattern based feature extraction and machine learning for epileptic seizure prediction and detection Chapter 7 - Increasing the usability of the Devanagari script input based P300 speller Chapter 8 - A comprehensive review of the fabrication and performance evaluation of dry electrodes for long-term ECG monitoring Chapter 9 - Effective cardiac health diagnosis using event-driven ECG processing with subband feature extraction and machine learning techniques Chapter 10 - Analysis of heart patients using a tree based ensemble model Chapter 11 - Heartbeat classification using parametric and time–frequency methods Chapter 12 - Segmentation of ECG waves using LSTM networks Chapter 13 - Deep convolutional neural network based diagnosis of COVID-19 using x-ray images Chapter 14 - Otitis media diagnosis model for tympanic membrane images processed in two-stage processing blocks Chapter 15 - Modelling and analysis for active infrared thermography for breast cancer screening Chapter 16 - Photoacoustic microscopy: fundamentals, instrumentation and applications Chapter 17 - Rigorous performance assessment of computer-aided medical diagnosis and prognosis systems: a biostatistical perspective on data mining

About the Author :
Varun Bajaj is Subject Editor-in-Chief of IET Electronics Letters (SCI) on biomedical technology and has also authored more than 90 research papers in various reputed international journals/conferences including IEEE Transactions, Elsevier, Springer and IOP Publishing. The citation impact of his publications is around 1762 citations, with a h-index of 19, and i10 index of 39 (Google Scholar June 2020). G R Sinha has published more than 200 research papers, edited four books on similar research areas to this book, and has authored key books on medical image processing and biometrics. He is Visiting Professor (honorary) at Sri Lanka Technological Campus Colombo. He is ACM Distinguished Speaker, IEEE Senior Member, Fellow of IETE and IEI, and has been an IEEE Distinguished Lecturer. He has more than 12 research and teaching based awards at international and national level to his credit.