Jaakko Malmivuo

Bio: Jaakko Malmivuo is an academic researcher from Tampere University of Technology. The author has contributed to research in topics: Impedance cardiography & Electroencephalography. The author has an hindex of 23, co-authored 138 publications receiving 3347 citations. Previous affiliations of Jaakko Malmivuo include Stanford University.

Sensitivity distributions of EEG and MEG measurements

Abstract: It is generally believed that because the skull has low conductivity to electric current but is transparent to magnetic fields, the measurement sensitivity of the magnetoencephalography (MEG) in the brain region should be more concentrated than that of the electroencephalography (EEG). It is also believed that the information recorded by these techniques is very different. If this were indeed the case, it might be possible to justify the cost of MEG instrumentation which is at least 25 times higher than that of EEG instrumentation. The localization of measurement sensitivity using these techniques was evaluated quantitatively in an inhomogeneous spherical head model using a new concept called half-sensitivity volume (HSV). It is shown that the planar gradiometer has a far smaller HSV than the axial gradiometer. However, using the EEG it is possible to achieve even smaller HSVs than with whole-head planar gradiometer MEG devices. The micro-superconducting quantum interference device (SQUID) MEG device does have HSVs comparable to those of the EEG. The sensitivity distribution of planar gradiometers, however, closely resembles that of dipolar EEG leads and, therefore, the MEG and EEG record the electric activity of the brain in a very similar way.

Measurement of noise and impedance of dry and wet textile electrodes, and textile electrodes with hydrogel

Abstract: � Abstract—Textile sensors, when embedded into clothing, can provide new ways of monitoring physiological signals, and improve the usability and comfort of such monitoring systems in the areas of medical, occupational health and sports. However, good electrical and mechanical contact between the electrode and the skin is very important, as it often determines the quality of the signal. This paper introduces a study where the properties of dry textile electrodes, textile electrodes moistened with water, and textile electrodes covered with hydrogel were studied with five different electrode sizes. The aim was to study how the electrode size and preparation of the electrode (dry electrode / wet electrode / electrode covered with hydrogel membrane) affect the measurement noise, and the skin-electrode impedance. The measurement noise and skin- electrode impedance were determined from surface biopotential measurements. These preliminary results indicate that noise level increases as the electrode size decreases. The noise level is high in dry textile electrodes, as expected. Yet, the noise level of wet textile electrodes is quite low and similar to that of textile electrodes covered with hydrogel. Hydrogel does not seem to improve noise properties, however it may have effects on movement artifacts. Thus, it is feasible to use textile embedded sensors in physiological monitoring applications when moistening or hydrogel is applied.

EEG/MEG source imaging: methods, challenges, and open issues

Abstract: We present the four key areas of research--preprocessing, the volume conductor, the forward problem, and the inverse problem-- that affect the performance of EEG and MEG source imaging. In each key area we identify prominent approaches and methodologies that have open issues warranting further investigation within the community, challenges associated with certain techniques, and algorithms necessitating clarification of their implications. More than providing definitive answers we aim to identify important open issues in the quest of source localization.

Comparison of the Properties of EEG and MEG in Detecting the Electric Activity of the Brain

Abstract: Since the detection of the first biomagnetic signals in 1963 there has been continuous discussion on the properties and relative merits of bioelectric and biomagnetic measurements. In this review article it is briefly discussed the early history of this controversy. Then the theory of the independence and interdependence of bioelectric and biomagnetic signals is explained, and a clinical study on ECG and MCG that strongly supports this theory is presented. The spatial resolutions of EEG and MEG are compared in detail, and the issue of the maximum number of electrodes in EEG is also discussed. Finally, some special properties of EEG and MEG methods are described. In brief, the conclusion is that EEG and MEG are only partially independent and their spatial resolutions are about the same. Recording both of them brings some additional information on the bioelectric activity of the brain. These two methods have certain unique properties that make either of them more beneficial in certain applications.

ACC/AHA 2002 Guideline Update for Exercise Testing: Summary Article A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Update the 1997 Exercise Testing Guidelines)

Abstract: The American College of Cardiology (ACC)/American Heart Association (AHA) Task Force on Practice Guidelines regularly reviews existing guidelines to determine when an update or full revision is needed. This process gives priority to areas where major changes in text, and particularly recommendations

Introduction to the Finite Element Method

Abstract: This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems. Although we discuss the main points in the application of the finite element method to electromagnetic design, including formulation and implementation, those who seek deeper understanding of the finite element method should consult some of the works listed in the bibliography section.

Handbook of Blind Source Separation: Independent Component Analysis and Applications

Abstract: Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time frequency approaches. This Handbook is an ideal reference for university researchers, RD algebraic identification of under-determined mixtures, time-frequency methods, Bayesian approaches, blind identification under non negativity approaches, semi-blind methods for communicationsShows the applications of the methods to key application areas such as telecommunications, biomedical engineering, speech, acoustic, audio and music processing, while also giving a general method for developing applications