Biomedical subjects

M Jobert

Publications and source records attributed to M Jobert.

10 recordsLinked to original sources

PubMed1995

Methodological considerations for the evaluation of EEG mapping data: a practical example based on a placebo/diazepam crossover trial.

Quantitative EEG is a sensitive method for measuring pharmacological effects on the central nervous system. Nowadays, computers enable EEG data to be stored and spectral parameters to be computed for signals obtained from a large number of electrode locations. However, the statistical analysis of such vast amounts of EEG data is complicated due to the limited number of subjects usually involved in pharmacological studies. In the present study, data from a trial aimed at comparing diazepam and placebo were used to investigate different properties of EEG mapping data and to compare different methods of data analysis. Both the topography and the temporal changes of EEG activity were investigated using descriptive data analysis, which is based on an inspection of patterns of pd values (descriptive p values) assessed for all pair-wise tests for differences in time or treatment. An empirical measure (tri-mean) for the computation of group maps is suggested, allowing a better description of group effects with skewed data of small samples size. Finally, both the investigation of maps based on principal component analysis and the notion of distance between maps are discussed and applied to the analysis of the data collected under diazepam treatment, exemplifying the evaluation of pharmacodynamic drug effects.

Adult↗

PubMed1995

ECG activity in the sleep of insomniac patients under the influence of lormetazepam and zopiclone.

The influence of the benzodiazepine hypnotic lormetazepam (1 mg) and the cyclopyrrolone hypnotic zopiclone (7.5 mg) on heart rate activity was studied in 16 elderly insomniacs in a placebo-controlled, randomised, 3-fold crossover trial. After digital preprocessing of the ECG, QRS complexes were automatically recognised by a detection technique based on adaptative thresholds. Both R-R periodicity and heart rate variability were analysed as a function of sleep stages and time of night. Under placebo, heart rate decreased significantly from the first to the second half of the night. The relationship between sleep stages and heart rate remained constant under both hypnotics. Although the two substances significantly modified the distribution of sleep stages, no relevant changes in ECG activity were observed when the proportion of the different sleep stages was taken into consideration.

Aged↗

PubMed1995

On the choice of recording duration in pharmaco-EEG studies.

Quantitative EEG is a sensitive method used to assess the effects of pharmacological substances on the central nervous system (CNS) activity. A standard technique is to measure the EEG under vigilance-controlled and resting conditions for a short duration, for example 5 min. The aim of the present study was to investigate the stability of 5-min EEG recordings. While the time course of the EEG was fairly stable during the recording session under the vigilance-controlled condition, systematic trends became apparent under the resting condition. Pharmaco-sensitivity of the EEG and its reliability increased with the recording duration. Five minutes of EEG recording seem to be sufficient and well chosen to evaluate the influence of drugs on the EEG.

Adult↗

PubMed1994

Automatic analysis of sleep using two parameters based on principal component analysis of electroencephalography spectral data.

A computer program for the analysis of a sleep electroencephalogram (EEG) is presented. The method relies on two steps. First, a spectral analysis is performed for signals recorded from one or more electrode locations. Then, two EEG parameters are obtained by storing the spectral activity in a multidimensional space, whose dimension is reduced using principal component analysis (PCA) techniques. The main advantage of these parameters is in describing the process of sleep on a continuous scale as a function of time. Validation of the method was performed with the data collected from 16 subjects (8 young volunteers and 8 elderly insomniacs). Results showed that the parameters correlate highly with the hypnograms established by conventional visual scoring. This signal parametrisation, however, offers more information regarding the time course of sleep, since small variations within individual sleep stages as well as smooth transitions between stages are assessed. Finally, the concurrent use of both parameters provides an original way of considering sleep as a dynamic process evolving cyclically in a single plane.

Adult↗

PubMed1994

Effects of hypericum extract on the sleep EEG in older volunteers.

The effects of treatment with high doses (300 mg three times daily) of hypericum extract LI 160 on sleep quality and well-being were investigated over a 4-week period. The double-blind, placebo-controlled study was conducted with 12 older, healthy volunteers in a cross-over design, which included a 2-week wash-out phase between both treatment phases. A hypostatic influence of the REM sleep phases, which is typical for tricyclic antidepressants and MAO inhibitors, could not be shown for this phytopharmacon. Instead, LI 160 induced an increase of deep sleep during the total sleeping period. This could be shown consistently in the visual analysis of the sleeping phases 3 and 4, as well as in the automatic analysis of slow-wave EEG activities. The continuity of sleep was not improved by LI 160; this was also the case for the onset of the sleep, the intermittent wake-up phases, and total sleep duration.

Anthracenes↗

PubMed1992

Pattern recognition by matched filtering: an analysis of sleep spindle and K-complex density under the influence of lormetazepam and zopiclone.

The evaluation of sleep EEG patterns is mostly accomplished by visual analysis. With modern personal computers however, it is possible to perform signal detection within a reasonable length of time automatically. This paper presents a method for signal processing based on matched filtering. This allows the detection of sleep spindles and K-complexes in a sleep EEG recording with a high degree of accuracy. First the technique is described, and the results of a validation study based on the comparison of visual evaluations and computer analysis are presented. Thereafter, results of an application study are presented. Sleep spindle and K-complex density under the influence of lormetazepam and zopiclone were examined. Under both medications sleep spindle density increased while K-complex density decreased. Computation of Pearson's correlation coefficients demonstrated that the interindividual sleep spindle and K-complex variations under both treatments are highly correlated. The data suggest that lormetazepam and zopiclone, although chemically different, have a similar mode of action and display comparable effects on the sleep EEG.

Adult↗

PubMed1992

Topographical analysis of sleep spindle activity.

There is evidence for two types of sleep spindle activity, one with a frequency of about 12 cycles/s (cps) and the other of about 14 cps. Visual examination indicates that both spindle types occur independently, whereby the 12-cps spindles are more pronounced in the frontal and the 14-cps spindles in the parietal region. The purpose of this paper is to provide more information about the exact topography of these patterns. First the occurrence of distinct signals in anterior and posterior brain regions was verified using pattern recognition techniques based on matched filtering. Thus the existence of two distinct sources of activity located in the frontal and parietal region of the brain, respectively, was demonstrated using EEG frequency mapping. Evaluation of sleep recordings showed high stability both in the frequency and location of the presumed spindle generators across sleep. Pharmacological effects of lormetazepam and zopiclone on both spindle types were investigated. Both substances enhanced the sleep spindle activity recorded from the frontal and parietal electrodes, but this increase was more pronounced in the parietal brain region.

Adult↗

PubMed1991

[Pattern recognition techniques in sleep polygraphy].

The evaluation of EEG-patterns is usually accomplished by visual analysis. Nowadays however, even personal computers are fast enough for an efficient pattern recognition of EEG signals. Using sleep spindles and K-complexes as examples, our aim was to demonstrate how patterns can be detected in an EEG signal with a high degree of accuracy. Furthermore, recognition of K-complexes has been improved by applying an additional "adaptive algorithm" allowing individual adjustments to the signal's form and amplitude.

Algorithms↗

PubMed1989

[The effect of age on sleep spindle and K complex density].

The amount of sleep spindles and K-complexes shows a great interindividual variety of combinations, such as many or few sleep spindles and K-complexes respectively. There seems to be no direct correlation between the amount of sleep spindles and K-complexes intraindividually. In our unselected population - age range between 18 and 77 years - the mean sleep spindle density is at 2.59 +/- 1.85/min and the mean K-complex density at 1.96 +/- .96/min stage 2. The diffuse individual distribution, however, does not reflect the age factor involved. The sleep spindle and K-complex density were practically half the amount for the age group above 50 years as compared to the age group of less than 30 years.

Adolescent↗

PubMed1989

[A system for continuous digitizing and evaluation of 32 biosignals from all-night sleep leads].

In all-night sleep recordings usually 12 to 16 channel electroencephalographs are used to record the electrical activity of the brain. A detailed analysis of EEG sleep activity, however, requires the inclusion of at least 19 electrodes placed according to the international 10-20 system in order to compare the variations of the activities in different brain areas. In addition polygraphic parameters such as ECG, respiration and actogram, to mention just a few, have to be recorded depending on the type of study. Therefore the number of recording channels has to be increased for a complete polygraphic investigation. We developed a 32 channel unit with a personal computer and corresponding hardware interfaces allowing the continuous digitalization of up to 32 bioelectrical signals throughout the whole night (8 hours). The recorded data can be presented graphically and evaluated according to the usual methods such as power spectrum, coherence and periodicity analysis. Additionally the use of algorithms for pattern detection permits automatic analysis of EEG segments regarding particular sleep patterns e.g. sleep spindles and K-complexes.

Electroencephalography↗