Anzeige
Erschienen in:
2015 | OriginalPaper | Buchkapitel
Lempel Ziv Complexity of EEG in Depression
verfasst von : Maie Bachmann, Kaia Kalev, Anna Suhhova, Jaanus Lass, Hiie Hinrikus
Erschienen in: 6th European Conference of the International Federation for Medical and Biological Engineering
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Diagnosis of depression is still based mainly on evaluation of the intensity of subjective symptoms by psychiatrists. This study is aimed to give additional objective information about major depressive disorder analyzing the electroencephaolographic (EEG) signal using the method of Lempel Ziv Complexity (LZC). LZC measures the algorithmic complexity by counting the number of distinct segments in a signal. EEG recordings were carried out on the groups of depressive and healthy subjects of 17 female volunteers each. The LZC was calculated on resting EEG signals recorded in eyes closed condition from 18 channels at a length of 5 minutes. The results revealed increased complexity in depression compared to controls in all channels. The highest statistically significant difference appeared in channel F4-Cz (p=0.0098). Our results demonstrate that the analysis of single channel EEG signal can provide statistically significant difference in algorithmic complexity, the LZC value, between control and depressive group.