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A modified Linear Estimation Approach was performed to reconstruct current sources within the heart. Based on MRI data sets the Boundary Element Method was used to create tailored multicompartment models of the human thorax which were used to solve the forward problem of magnetocardiography. The ability of the proposed method was demonstrated for the localization of a single current dipole as an example of a focal source. By means of introducing small shiftings to all reconstruction dipoles during linear estimation solution as well as performing a successive focussing strategy ignoring places without significant electrical activity the method could easily be extended to the reconstruction of real 3D sources. Based on a special minimum-norm solution the source volume can be estimated applying a finite element approximation using cube elements. The size of an extended current source can be estimated by superimposing the reconstructed dipoles to an equivalent dipole and comparing the corresponding volume with the sphere which would be related to the equivalent dipole. The deviation of these volumes can be taken as a criterion for non-dipolarity of sources.

This second, completely updated and extended edition of the only reference work in this growing field of medical physics focuses on biomagnetic instrumentation as well as applications in cardiology and neurology. New chapters have been added on fetal magnetography and magnetic field therapy, as well as the safety aspects of magnetic fields. Written by well-known specialists from Germany, USA, Canada, Japan, the Netherlands and Scandinavia, the result is a manual for researchers in this field as well as for those who apply modern methods based on magnetism in medical practice. It equally provides a detailed overview for newcomers to the field as well as for experts familiar with only one part of the area.

An important guide that reviews the basics of magnetic biosensor modeling and simulation Magnetic Sensors for Biomedical Applications offers a comprehensive review of magnetic biosensor modelling and simulation. The authors—noted experts on the topic—explore the model's strengths and weaknesses and discuss the competencies of different modelling software, including homemade and commercial (for example Multi-physics modelling software). The section on sensor materials examines promising materials whose properties have been used for sensing action and predicts future smart-materials that have the potential for sensing application. Next, the authors present classifications of sensors that are divided into different sub-types. They describe their working and highlight important applications that reveal the benefits and drawbacks of relevant designs. The book also contains information on the most recent developments in the field of each sensor type. This important book: Provides an even treatment of the major foundations of magnetic biosensors Presents problem solution methods such as analytical and numerical Explains how solution methods complement each other, and offers information on their materials, design, computer aided modelling and simulation, optimization, and device fabrication Describes modeling work challenges and solutions Written for students in electrical and electronics engineering, physics, chemistry, biomedical engineering, and biology, Magnetic Sensors for Biomedical Applications offers a guide to the principles of biomagnetic sensors, recent developments, and reveals the impact of sensor modelling and simulation on magnetic sensors.

An outgrowth of the Biennial International Congress on Holter and Noninvasive Electrocardiology held in Ulm, Germany, in May 1998. The 46 papers provide a snapshot of the field at the end of the century for clinical cardiologists and internists who use electrocardiographic procedures in managing their patients, researchers actively involved in the field, and students who will be working in it. They cover physiology and pathophysiology from genes and phenotypes to the autonomic nervous system, aspects investigated by different methods such as P-wave and QRS and T-wave alternans/repolarization, ischemic heart disease, ambulatory blood pressure monitoring and other methods, and non-linear dynamics and newer signal detection and analysis techniques.

This two-volume handbook offers a comprehensive and coordinated presentation of SQUIDs (Superconducting Quantum Interference Devices), including device fundamentals, design, technology, system construction and multiple applications. It is intended to bridge the gap between fundamentals and applications, and will be a valuable textbook reference for graduate students and for professionals engaged in SQUID research and engineering. It will also be of use to specialists in multiple fields of practical SQUID applications, from human brain research and heart diagnostics to airplane and nuclear plant testing to prospecting for oil, minerals and buried ordnance. While the first volume presents the theory and fabrication of SQUIDs, the second volume is devoted to applications. It starts with an important aspect of the analysis of measured magnetic signals generated by current sources (the inverse problem), and includes several chapters devoted to various areas of application, namely biomagnetism (research on and diagnostics of human brain, heart, liver, etc.), detection of extremely weak signals, for example electromagnetic radiation and Nuclear Magnetic Resonance. The volume closes with a chapter on motion detectors and the detection of gravity waves.

Over the past several decades, much progress has been made in understanding the mechanisms of electrical activity in biological tissues and systems, and for developing non-invasive functional imaging technologies to aid clinical diagnosis of dysfunction in the human body. The book will provide full basic coverage of the fundamentals of modeling of electrical activity in various human organs, such as heart and brain. It will include details of bioelectromagnetic measurements and source imaging technologies, as well as biomedical applications. The book will review the latest trends in the field and comment on the future direction in this fast developing line of research.

Neural activity in the human brain generates coherent synaptic and intracellular currents in cortical columns that create electromagnetic signals which can be measured outside the head using magnetoencephalography (MEG) and electroencephalography (EEG). Electromagnetic brain imaging refers to techniques that reconstruct neural activity from MEG and EEG signals. Electromagnetic brain imaging is unique among functional imaging techniques for its ability to provide spatio-temporal brain activation profiles that reflect not only where the activity occurs in the brain but also when this activity occurs in relation to external and internal cognitive events, as well as to activity in other brain regions. Adaptive spatial filters are powerful algorithms for electromagnetic brain imaging that enable high-fidelity reconstruction of neuronal activity. This book describes the technical advances of adaptive spatial filters for electromagnetic brain imaging by integrating and synthesizing available information and describes various factors that affect its performance. The intended audience include graduate students and researchers interested in the methodological aspects of electromagnetic brain imaging.

This textbook provides a comprehensive and didactic introduction from the basics to the current state of the art in the field of EEG/MEG source reconstruction. Reconstructing the generators or sources of electroencephalographic and magnetoencephalographic (EEG/MEG) signals is an important problem in basic neuroscience as well as clinical research and practice. Over the past few decades, an entire theory, together with a whole collection of algorithms and techniques, has developed. In this textbook, the authors provide a unified perspective on a broad range of EEG/MEG source reconstruction methods, with particular emphasis on their respective assumptions about sources, data, head tissues, and sensor properties. An introductory chapter highlights the concept of brain imaging and the particular importance of the neuroelectromagnetic inverse problem. This is followed by an in-depth discussion of neural information processing and brain signal generation and an introduction to the practice of data acquisition. Next, the relevant mathematical models for the sources of EEG and MEG are discussed in detail, followed by the neuroelectromagnetic forward problem, that is, the prediction of EEG or MEG signals from those source models, using biophysical descriptions of the head tissues and the sensors. The main part of this textbook is dedicated to the source reconstruction methods. The authors present a theoretical framework of the neuroelectromagnetic inverse problem, centered on Bayes’ theorem, which then serves as the basis for a detailed description of a large variety of techniques, including dipole fit methods, distributed source reconstruction, spatial filters, and dynamic source reconstruction methods. The final two chapters address the important topic of assessment, including verification and validation of source reconstruction methods, and their actual application to real-world scientific and clinical questions. This book is intended as basic reading for anybody who is engaged with EEG/MEG source reconstruction, be it as a method developer or as a user, including advanced undergraduate students, PhD students, and postdocs in neuroscience, biomedical engineering, and related fields.