TY  - JOUR
A1  - Helland, Vanessa Carolina Figuera
A1  - Gapelyuk, Andrej
A1  - Suhrbier, Alexander
A1  - Riedl, Maik
A1  - Penzel, Thomas
A1  - Kurths, Jürgen
A1  - Wessel, Niels
T1  - Investigation of an automatic sleep stage classification by means of multiscorer hypnogram
N2  - Objectives: Scoring sleep visually based on polysomnography is an important but time-consuming element of sleep medicine. Where-as computer software assists human experts in the assignment of sleep stages to polysomnogram epochs, their performance is usually insufficient. This study evaluates the possibility to fully automatize sleep staging considering the reliability of the sleep stages available from human expert sleep scorers. Methods: We obtain features from EEG, ECG and respiratory signals of polysomnograms from ten healthy subjects. Using the sleep stages provided by three human experts, we evaluate the performance of linear discriminant analysis on the entire polysomnogram and:only on epochs where the three experts agree in their-sleep stage scoring. Results: We show that in polysomnogram intervals, to which all three scorers assign the same sleep stage, our algorithm achieves 90% accuracy. This high rate of agreement with the human experts is accomplished with only a small set of three frequency features from the EEG. We increase-the performance to 93% by including ECG and respiration features. In contrast, on intervals of ambiguous sleep stage, the sleep stage classification obtained from our algorithm, agrees with the human consensus scorer in approximately 61%. Conclusions: These findings suggest that machine classification is highly consistent with human sleep staging and that error in the algorithm's assignments is rather a problem of lack of well-defined criteria for human experts to judge certain polysomnogram epochs than an insufficiency of computational procedures
Y1  - 2010
UR  - http://www.schattauer.de/index.php?id=103&L=1
U6  - https://doi.org/10.3414/Me09-02-0052
SN  - 0026-1270
ER  - 
TY  - JOUR
A1  - Riedl, Maik
A1  - van Leeuwen, Peter Jan
A1  - Suhrbier, Alexander
A1  - Malberg, Hagen
A1  - Groenemeyer, Dietrich
A1  - Kurths, Jürgen
A1  - Wessel, Niels
T1  - Testing foetal-maternal heart rate synchronization via model-based analyses
N2  - The investigation of foetal reaction to internal and external conditions and stimuli is an important tool in the characterization of the developing neural integration of the foetus. An interesting example of this is the study of the interrelationship between the foetal and the maternal heart rate. Recent studies have shown a certain likelihood of occasional heart rate synchronization between mother and foetus. In the case of respiratory-induced heart rate changes, the comparison with maternal surrogates suggests that the evidence for detected synchronization is largely statistical and does not result from physiological interaction. Rather, they simply reflect a stochastic, temporary stability of two independent oscillators with time-variant frequencies. We reanalysed three datasets from that study for a more local consideration. Epochs of assumed synchronization associated with short-term regulation of the foetal heart rate were selected and compared with synchronization resulting from white noise instead of the foetal signal. Using data-driven modelling analysis, it was possible to identify the consistent influence of the heartbeat duration of maternal beats preceding the foetal beats during epochs of synchronization. These maternal beats occurred approximately one maternal respiratory cycle prior to the affected foetal beat. A similar effect could not be found in the epochs without synchronization. Simulations based on the fitted models led to a higher likelihood of synchronization in the data segments with assumed foetal-maternal interaction than in the segment without such assumed interaction. We conclude that the data-driven model-based analysis can be a useful tool for the identification of synchronization.
Y1  - 2009
UR  - http://rsta.royalsocietypublishing.org/
U6  - https://doi.org/10.1098/rsta.2008.0277
SN  - 1364-503X
ER  -