As part of the publication of the excellent paper “Automatic detection of rhythmic and periodic patterns in critical care EEG based on American Clinical Neurophysiology Society (ACNS) standardized terminology”, the AIT scientist Franz Fürbass and colleagues were honored by covering the title page of the international journal NCCN - Neurophysiologie Clinique / Clinical Neurophysiology with a picture of their novel patient monitoring software.
Authors:
F. Fürbass, M.M. Hartmann, J.J. Halford, J. Koren, J. Herta, A. Gruber, C. Baumgartner, T. Kluge
Abstract:
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.