Search

Summary Aims of the study Continuous EEG from critical care patients needs to be evaluated time efficiently to maximize the treatment effect. A computational method will be presented that detects rhythmic and periodic patterns according to the critical care EEG terminology (CCET) of the American Clinical Neurophysiology Society (ACNS). The aim is to show that these detected patterns support EEG experts in writing neurophysiological reports. Materials and methods First of all, three case reports exemplify the evaluation procedure using graphically presented detections. Second, 187 hours of EEG from 10 critical care patients were used in a comparative trial study. For each patient the result of a review session using the EEG and the visualized pattern detections was compared to the original neurophysiology report. Results In three out of five patients with reported seizures, all seizures were reported correctly. In two patients, several subtle clinical seizures with unclear EEG correlation were missed. Lateralized periodic patterns (LPD) were correctly found in 2/2 patients and EEG slowing was correctly found in 7/9 patients. In 8/10 patients, additional EEG features were found including LPDs, EEG slowing, and seizures. Conclusion The use of automatic pattern detection will assist in review of EEG and increase efficiency. The implementation of bedside surveillance devices using our detection algorithm appears to be feasible and remains to be confirmed in further multicenter studies. [ABSTRACT FROM AUTHOR]

Long-term community-based monitoring of narwhals (Monodon monoceros) is needed because narwhals are important to local Inuit and are facing changes in their environment. We examined the suitability of passive acoustic recording for monitoring narwhals, using data gathered in the Canadian Arctic from an autonomous acoustic recorder (Repulse Bay, 2006) and a hand-held digital recorder (Koluktoo Bay, 2006 - 08). We found a relationship between the number of narwhals observed passing a fixed point and the number of calls heard. In addition, we found that an automated call detector could isolate segments of recording containing narwhal vocalizations over long recording periods containing non-target sound, thus decreasing the time spent on the analysis. Collectively, these results suggest that combining passive acoustic sampling with an automated call detector offers a useful approach for local monitoring of the presence and relative abundance of narwhals. [ABSTRACT FROM AUTHOR]