Ongoing EEG artifact correction using blind source separation

Objective: Analysis of the electroencephalogram (EEG) for epileptic spike and seizure detection or brain-computer interfaces can be severely hampered by the presence of artifacts. The aim of this study is to describe and evaluate a fast automatic algorithm for ongoing correction of artifacts in continuous EEG recordings, which can be applied offline and online. Methods: The automatic algorithm for ongoing correction of artifacts is based on fast blind source separation. It uses a sliding window technique with overlapping epochs and features in the spatial, temporal and frequency domain to detect and correct ocular, cardiac, muscle and powerline artifacts. Results: The approach was validated in an independent evaluation study on publicly available continuous EEG data with 2035 marked artifacts. Validation confirmed that 88% of the artifacts could be removed successfully (ocular: 81%, cardiac: 84%, muscle: 98%, powerline: 100%). It outperformed state-of-the-art algorithms both in terms of artifact reduction rates and computation time. Conclusions: Fast ongoing artifact correction successfully removed a good proportion of artifacts, while preserving most of the EEG signals. Significance: The presented algorithm may be useful for ongoing correction of artifacts, e.g., in online systems for epileptic spike and seizure detection or brain-computer interfaces.Comment: 16 pages, 4 figures, 3 table

Microbiome analysis in women with endometriosis: Does a microbiome exist in peritoneal fluid and ovarian cystic fluid?

Abstract Purpose To investigate the relationship between the microbiome of the female genital tract and endometriosis. Methods This prospective cohort study included 36 women who underwent laparoscopic surgery for ovarian tumor from July 2019 to April 2020. Of them, 18 had endometriosis, and 18 did not have endometriosis. Vaginal secretions, endometrial fluid, peritoneal fluid, and ovarian cystic fluid were collected during surgery. Next‐generation sequencing of bacterial 16S rRNA was performed to characterize the microbiome. Results Specific microbiomes were not detected in either peritoneal fluid or ovarian cystic fluid regardless of the presence or absence of endometriosis and the type of cyst. When the cutoff value of infectious bacterial abundance in the vagina was set as 64.3%, there were many cases more than a cutoff value in the endometriosis group significantly (p = 0.01). When the cutoff value of infectious bacterial abundance in the endometrium was set as 18.6%, there were many cases more than a cutoff level in the endometriosis cases significantly (p = 0.02). Conclusion Peritoneal fluid and ovarian cystic fluid are almost sterile, although dysbiosis may occur in the vaginal and endometrial microbiome in women with endometriosis