This book examines non-invasive, electrical-based methods for disease diagnosis and assessment of heart function. In particular, a formalized signal model is proposed since this offers several advantages over methods that rely on measured data alone. By using a formalized representation, the parameters of the signal model can be easily manipulated and/or modified, thus providing mechanisms that allow researchers to reproduce and control such signals. In addition, having such a formalized signal model makes it possible to develop computer tools that can be used for manipulating and understanding how signal changes result from various heart conditions, as well as for generating input signals for experimenting with and evaluating the performance of e.g. signal extraction methods. The work focuses on bioelectrical information, particularly electrical bio-impedance (EBI). Once the EBI has been measured, the corresponding signals have to be modelled for analysis. This requires a structured approach in order to move from real measured data to the model of the corresponding signals. This book proposes a generic framework for this procedure. It can be used as a guide for modelling impedance cardiography (ICG) and impedance respirography (IRG) signals, as well as for developing the corresponding bio-impedance signal simulator (BISS).

The analysis of bioelectrical signals continues to receive wide attention in research as well as commercially because novel signal processing techniques have helped to uncover valuable information for improved diagnosis and therapy. This book takes a unique problem-driven approach to biomedical signal processing by considering a wide range of problems in cardiac and neurological applications–the two "heavyweight" areas of biomedical signal processing. The interdisciplinary nature of the topic is reflected in how the text interweaves physiological issues with related methodological considerations. Bioelectrical Signal Processing is suitable for a final year undergraduate or graduate course as well as for use as an authoritative reference for practicing engineers, physicians, and researchers. - A problem-driven, interdisciplinary presentation of biomedical signal processing - Focus on methods for processing of bioelectrical signals (ECG, EEG, evoked potentials, EMG) - Covers both classical and recent signal processing techniques - Emphasis on model-based statistical signal processing - Comprehensive exercises and illustrations - Extensive bibliography

Changes in the neurological functions of the human brain are often a precursor to numerous degenerative diseases. Advanced EEG systems and other monitoring systems used in preventive diagnostic procedures incorporate innovative features for brain monitoring functions such as real-time automated signal processing techniques and sophisticated amplifiers. Highlighting the US, Europe, Australia, New Zealand, Japan, Korea, China, and many other areas, EEG/ERP Analysis: Methods and Applications examines how researchers from various disciplines have started to work in the field of brain science, and explains the different techniques used for processing EEG/ERP data. Engineers can learn more about the clinical applications, while clinicians and biomedical scientists can familiarize themselves with the technical aspects and theoretical approaches. This book explores the recent advances involved in EEG/ERP analysis for brain monitoring, details successful EEG and ERP applications, and presents the neurological aspects in a simplified way so that those with an engineering background can better design clinical instruments. It consists of 13 chapters and includes the advanced techniques used for signal enhancement, source localization, data fusion, classification, and quantitative EEG. In addition, some of the chapters are contributed by neurologists and neurosurgeons providing the clinical aspects of EEG/ERP analysis. Covers a wide range of EEG/ERP applications with state-of-the-art techniques for denoising, analysis, and classification Examines new applications related to 3D display devices Includes MATLAB® codes EEG/ERP Analysis: Methods and Applications is a resource for biomedical and neuroscience scientists who are working on neural signal processing and interpretation, and biomedical engineers who are working on EEG/ERP signal analysis methods and developing clinical instrumentation. It can also assist neurosurgeons, psychiatrists, and postgraduate students doing research in neural engineering, as well as electronic engineers in neural signal processing and instrumentation.

This book constitutes the refereed proceedings of the 13th Colombian Conference on Computing, CCC 2018, held in Cartagena, Colombia, in September 2018. The 46 revised full papers presented were carefully reviewed and selected from 194 submissions. The papers deal with the following topics: information and knowledge management, software engineering and IT architectures, educational informatics, intelligent systems and robotics, human-computer interaction, distributed systems and large-scale architectures, image processing, computer vision and multimedia, security of the information, formal methods, computational logic, and theory of computation.

Functional magnetic resonance imaging (fMRI) and Electronecephalography (EEG) are very important and complementary modalities since fMRI offers high spatial resolution and EEG is a direct measurement of neuronal activity with high temporal resolution. Interest in the integration of both types of data is growing rapidly as it promises to provide important new insights into human brain activity as it has already done so in the field of epilepsy. The availability of good quality instrumentation capable of providing interference-free data in both modalities means that electrophysiological and haemodynamic characteristics of individual brain events can be captured for the first time. Consequently, it seems certain that the integration of fMRI and EEG will play an increasing role in neuroscience and of the clinical study of brain disorders such as epilepsy. The proposed book will discuss in detail the physiological principles, practical aspects of measurement, artefact reduction and analysis and also applications of the integration of fMRI and EEG. All applications, which are mainly in the fields of sleep research, cognitive neuroscience and clinical use in neurology and psychiatry will be reviewed.