Atmospheric Pressure Variation is a Delayed Trigger for Aneurysmal Subarachnoid Hemorrhage.

OBJECTIVE: There is an ongoing search for conditions that induce spontaneous subarachnoid hemorrhage (SAH). The seasonal pattern of SAH is shown in a large meta-analysis of the literature, but its explanation remains undecided. There is a clear need for sound meteorologic data to further elucidate the seasonal influence on SAH. Because of the stable and densely monitored atmospheric situation in the north of the Netherlands, we reviewed our unique cohort on the seasonal incidence of SAH and the association between SAH and local atmospheric changes. METHODS: Our observational cohort study included 1535 patients with spontaneous SAH admitted to our neurovascular center in the north of the Netherlands between 2000 and 2015. Meteorologic data could be linked to the day of the ictus. To compare SAH incidences over the year and to test the association with meteorologic conditions, incidence rate ratios (IRRs) with corresponding 95% confidence intervals (CIs) were used, calculated by Poisson regression analyses. RESULTS: Atmospheric pressure variations were significantly associated with aneurysmal SAH. In particular, the pressure change on the second and third day before the ictus was independently correlated to a higher incidence of aneurysmal SAH (IRR, 1.11; 95% CI, 1.00-1.23). The IRR for aneurysmal SAH in July was calculated 0.67 (95% CI, 0.49-0.92) after adjustment for temperature and atmospheric pressure changes. CONCLUSIONS: Atmospheric pressure variations are a delayed trigger for aneurysmal SAH. Also, a significantly decreased incidence of aneurysmal SAH was noted in July.

A robust fetal ECG detection method for abdominal recordings.

In this paper, we propose a new method for FECG detection in abdominal recordings. The method consists of a sequential analysis approach, in which the a priori information about the interference signals is used for the detection of the FECG. Our method is evaluated on a set of 20 abdominal recordings from pregnant women with different gestational ages. Its performance in terms of fetal heart rate (FHR) detection success is compared with that of independent component analysis (ICA). The results show that our sequential estimation method outperforms ICA with a FHR detection rate of 85% versus 60% of ICA. The superior performance of our method is especially evident in recordings with a low signal-to-noise ratio (SNR). This indicates that our method is more robust than ICA for FECG detection.

Artifact reduction in maternal abdominal ECG recordings for fetal ECG estimation.

Monitoring the fetal electrocardiogram (fECG) is currently one of the most promising methods to assess fetal health. However, the main problem associated with this method is that the signals recorded from the maternal abdomen are affected by noise and interferences: the maternal electrocardiogram (mECG) being the dominant interference. In this paper a mECG removal technique is described, which is based on dynamic segmentation of the mECG and subsequent linear prediction of the mECG segments. Moreover, as the linear prediction is significantly affected by artifacts, a signal validation technique is presented to suppress the effect of artifacts on the mECG prediction. The performance of the presented technique is evaluated by comparison to the performance of three other mECG removal techniques: the presented technique outperforms the other techniques for all recordings.