PubMed Health⌕ Search

PubMed · 10720006

Systematic errors in multi-frequency EIT.

Abstract

Systematic errors have been measured with a multi-frequency data-collection system operating between 10.24 and 81.92 kHz. The errors were present even though a conventional background measurement on a uniform saline phantom had already been subtracted. Errors due to changes in transimpedance between the calibration and the tissue measurements, cable movement and electrode-skin contact impedance were simulated giving a total systematic error estimate equivalent to a 9% change in tissue conductivity. It was shown that more than 89% of the image was above the total error magnitude, indicating that most of the image revealed true changes in tissue conductivity. In three human subjects, the largest conductivity changes were in two regions, located posteriorly on either side of the midline, and were interpreted as due to the erector spinae muscles. These regions showed increases in conductivity of 73-104%. Identification of other anatomical features was difficult because of the poor spatial resolution of the images.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J Schlappa, E Annese, H Griffiths. 2000. Systematic errors in multi-frequency EIT.. https://doi.org/10.1088/0967-3334%2F21%2F1%2F314

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Estimating the value of an internal biostatistical consulting service.

Biostatistical consulting is a service business. Although a consulting biostatistician's goal is long-term collaborative relationships with investigators, this is the same as the long-term goal of any business: having a group of contented, satisfied customers. In this era of constrained resources, we must be able to demonstrate that the benefit a biostatistical consulting group provides to its organization exceeds its actual cost to the institution. In this paper, I provide both a theoretical framework for assessing the value of a biostatistical service and provide an ad hoc method to value the contribution of a biostatistical service to a grant. Using the methods described, our biostatistics group returns more than $6 for each dollar spent on institutional support in 1998.

Biometry↗

Repeated measures in clinical trials: simple strategies for analysis using summary measures.

The summary measures approach to analysing repeated measures is described. The circumstances under which it can be advantageous to use such measures are considered. Strategies for baseline adjustment where there are multiple baselines are examined, as is the choice of appropriate summary statistic. A compromise trend/mean measure, regression through the origin, is proposed as being useful under some circumstances. An analysis using this measure is illustrated with a suitable example.

Biometry↗

Generalized averaging and noise levels in evoked responses.

A formal relationship between the mean square noise level in an evoked potential experiment, the number of averages and the autocorrelation function of the noise is derived. The generalized averaging process is recast as a filter applied to the noise signal. This filter is computed for a number of different types of evoked potential experiments in which various weighting factors and stochastic stimulation times are allowed. Although the variance in noise level estimates can be large, there is a general trend for noise reduction to occur more slowly than the expected 1/N when the total time over which averaging occurs is small in comparison to the correlation time of the noise. When the total averaging time exceeds the temporal extent of the autocorrelation function, the expected 1/N behavior is observed.

Biometry↗