Abstract:

BACKGROUND: Previous studies suggest that auditory evoked potentials (AEP) may be used to monitor anaesthetic depth. However, during surgery and anaesthesia, the quality of AEP recordings may be reduced by artefacts. This can affect the interpretation of the data and complicate the use of the method. We assessed differences in expert ratings of the signal quality of perioperatively recorded AEPs. METHODS: Signal quality of 180 randomly selected AEP, recorded perioperatively during a European multicentre study, was rated independently by five experts as 'invalid' (0), 'poor' (1), or 'good' (2). Average (n=5) quality rating was calculated for each signal. Differences between quality ratings of the five experts were calculated for each AEP: inter-rater variability (IRV) was calculated as the difference between the worst and best classification of a signal. RESULTS: Average signal quality of 57% of the AEPs was rated as 'invalid', 39% as 'poor', and only 4% as 'good'. IRV was 0 in only 6%, 1 in 62%, and 2 in 32% of the AEP, that is in 32% one expert said signal quality was good, whereas a different expert thought the identical signal was invalid. CONCLUSIONS: There is poor agreement between experts regarding the signal quality of perioperatively recorded AEPs and, as a consequence, results obtained by one expert may not easily be reproduced by a different expert. This limits the use of visual AEP analysis to indicate anaesthetic depth and may affect the comparability of AEP studies, where waveforms were analysed by different experts. An objective automated method for AEP analysis could solve this problem.

Abstract:

The inverse problem of electrocardiography, consisting of the reconstruction of bioelectrical sources on the heart from measured body surface potentials, is an ill-posed problem. The human body with its tissue inbetween the heart and the body surface behaves like a filter, that damps or even eliminates higher spatial frequencies of source distributions on the heart. The source distributions leading to body surface potentials which are smaller than noise cannot be measured and belong to the nullspace. The extent of the nullspace for a given model of the human body and for a given measurement accuracy depends strongly on the chosen electrode positions and the source locations. Without regarding any modelling error, this study investigates the limits of reconstructable source patterns for two different finite element models. To determine the reconstruction limits for these datasets, the best electrode positions and the accurate number and locations of bioelectrical sources on the heart must be found

Abstract:

The spatial resolution of Bioelectric Imaging of the Heart was investigated. Based on the measurement of a multichannel Electrocardiogram (ECG) or Magnetocardiogram (MCG) images of epicardial potential distributions can be reconstructed. The imaging properties of this method have been investigated using Computer simulations. The spatial resolution depends strongly on the number and arrangement of electrodes and magnetometers, on the noise level of the sensors and on the individual morphology of the patient. Artefacts show up if errors in the torso model (geometry and/or impedance values) occur.

Abstract:

A procedure to find the optimal electrode positions for multichannel electrocardiography is presented. The criterion is the ability to reconstruct images of the electrical activity of the heart. Singular value decomposition of the lead field matrix is the chosen approach. The finite element method is used for numerical field calculation to determine the lead field matrix. Estimates on the expected measurement error play an important role in the optimization procedure. The optimal arrangement of electrodes is compared with other electrode positions reported in the literature using different optimization criteria. Body surface potential maps (BSPM) are measured on a healthy volunteer using the optimized electrode arrangement and preliminary epicardial potential patterns are reconstructed