Journal of clinical monitoring and computing
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J Clin Monit Comput · Dec 2002
Comparative StudyComparison of two spatially resolved NIRS oxygenation indices.
We compared the percentage haemoglobin oxygenation indices from two near infrared spectrophotometers (NIRS) to determine whether the devices reported similar changes in response to induced changes in oxygenation. ⋯ There was close agreement between the INVOS 5100 and NIRO-300 in response to major physiological change, although absolute values of (rSO2) and TOI were not identical. There was less agreement during baseline measurements or minimal physiologic change.
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J Clin Monit Comput · Dec 2002
Does the EEG during isoflurane/alfentanil anesthesia differ from linear random data?
Bispectral analysis of the electroencephalogram (EEG) has been used to monitor depth of anesthesia. In the majority of publications this has been done using the so called Bispectral (BIS) Index. The exact relation of this index to bispectral quantities like the bispectrum and its normalized version the bicoherence has not yet been published. In case the EEG is a linear random process the bicoherence is trivial. It is a mere constant independent of the EEG frequency. If the signal is a linear Gaussian random process this constant is zero. In this case both the bispectrum and bicoherence are zero. The aim of this study was to determine the proportion of EEG epochs with non-trivial bicoherence during anesthesia with isoflurane/nitrous oxide. ⋯ As expected the test procedure correctly identified for the Lorenz data for 95% of all epochs a non-trivial bicoherence. For the original EEG data we could not find a significant greater percentage of epochs with non-trivial bicoherence than for the pr data and the synthetic Gaussian data. We conclude that the EEG during anesthesia with isoflurane/alfentanil appears to be largely a linear random process.
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J Clin Monit Comput · Dec 2002
Integrated image analysis solutions for PET datasets in damaged brain.
To identify and discuss the problems inherent in the processing of multiparametric functional imaging datasets from patients with acute brain injury, using "triple oxygen" positron emission tomography (PET) as an example. To present an integrated imaging solution for analysis of such datasets and report on its use in practice. ⋯ While modules from several imaging software suites can be usefully combined to allow analysis of multiparametric PET data sets from patients with acute brain injury, sequential use of these modules for various steps in image analysis is fraught with difficulty. Careful automation and integration of these steps greatly facilitates the interrogation of information-rich data sets and increases research productivity.
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We studied the performance of several lossless compression algorithms on eye movement signals recorded in otoneurological balance and other physiological laboratories. Despite the wide use of these signals their compression has not been studied prior to our research. The compression methods were based on the common model of using a predictor to decorrelate the input and using an entropy coder to encode the residual. We found that these eye movement signals recorded at 400 Hz and with 13 bit amplitude resolution could losslessly be compressed with a compression ratio of about 2.7.