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This study used a new approach of off-line, video-based physician annotations, showing that even with modern monitoring systems most alarms are not clinically relevant. As the majority of alarms are simple threshold alarms, statistical methods may be suitable to help reduce the number of false-positive alarms. Our study is also intended to develop a reference database of annotated monitoring alarms for further application to alarm algorithm research.

This study aims at answering two basic questions regarding the mechanisms with which hormones modulate functional cerebral asymmetries. Which steroids or gonadotropins fluctuating during the menstrual cycle affect perceptual asymmetries? Can these effects be demonstrated in a cross-sectional (follicular and midluteal cycle phases analyzed) and a longitudinal design, in which the continuous hormone and asymmetry fluctuations were measured over a time course of 6 weeks? To answer these questions, 12 spontaneously cycling right-handed women participated in an experiment in which their levels of progesterone, estradiol, testosterone, LH, and FSH were assessed every 3 days by blood-sample based radioimmunoassays (RIAs). At the same points in time their asymmetries were analyzed with visual half-field (VHF) techniques using a lexical decision, a figure recognition, and a face discrimination task. Both cross-sectional and longitudinal analyzes showed that an increase of progesterone is related to a reduction in asymmetries in a figure recognition task by increasing the performance of the left-hemisphere which is less specialized for this task. Cross-sectionally, estradiol was shown to have significant relationships to the accuracy and the response speed of both hemispheres. However, since these effects were in the same direction, asymmetry was not affected. This was not the case in the longitudinal design, where estradiol affected the asymmetry in the lexical decision and the figural comparison task. Overall, these data show that hormonal fluctuations within the menstrual cycle have important impacts on functional cerebral asymmetries. The effect of progesterone was highly reliable and could be shown in both analysis schemes. By contrast, estradiol mainly, but not exclusively, affected both hemispheres in the same direction.

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In this paper, we consider one-step outlier identication rules for multivariate data, generalizing the concept of so-called outlier identiers, as presented in Davies and Gather (1993) for the case of univariate samples. We investigate, how the nite-sample breakdown points of estimators used in these identication rules inuence the masking behaviour of the rules.

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Data from the automatic monitoring of intensive care patients exhibits trends, outliers, and level changes as well as periods of relative constancy. All this is overlaid with a high level of noise and there are dependencies between the different items measured. Current monitoring systems tend to deliver too many false warnings which reduces their acceptability by medical staff. The challenge is to develop a method which allows a fast and reliable denoising of the data and which can separate artifacts from clinical relevant structural changes in the patients condition (Gather et al., 2002). A simple median filter works well as long as there is no substantial trend in the data but improvements may be possible by approximating the data by a local linear trend. As a first step in this programme the paper examines the relative merits of the L 1 regression, the repeated median (Siegel, 1982) and the least median of squares (Hampel, 1975, Rousseeuw, 1984. The question of dependency between different items is a topic for future research.MSC: primary: 62G07; secondary: 62G35