| Autor: |
Dax JF; Institut für Maschinelles Sehen und Darstellen, BCI-Lab, Technische Universität Graz, Inffeldgasse 16a, 8010 Graz, Osterreich., Müller-Putz GR, Pfurtscheller K, Urlesberger B, Müller W, Pfurtscheller G |
| Jazyk: |
němčina |
| Zdroj: |
Biomedizinische Technik. Biomedical engineering [Biomed Tech (Berl)] 2005 Jan-Feb; Vol. 50 (1-2), pp. 19-24. |
| DOI: |
10.1515/BMT.2005.004 |
| Abstrakt: |
Recordings of the electroencephalogram (EEG) and of the heart rate variability (HRV) of preterm neonates can give important information on the actual state of the nervous system. Both signals, EEG and HRV, are affected by parameters such as gestational age, stage of maturation and behavioral state. This work describes a method for automatic detection of slow wave EEG-bursts and a tool to average changes in the EEG and the corresponding heart rate. The detection is based on the hjorth activity (HA), calculated from the EEG. HA spikes (HAS) are identified by the determination of the beginning and end of existing spikes. HAS maxima and the time between two consecutive HAS are the basis for the triggering of the bursts. EEG power and time synchronized HR changes are averaged with a time window length of 20 s. Resultant, HR increase and duration are determined. These parameters, obtained by the automatic detection, proved to be comparable to the results of an expert. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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