Einleitung: SSEP sind etabliert, um Patienten intraoperativ zu überwachen, wenn sie sich Operationen im zerebrovaskulären System unterziehen. Das EEG ist eine weitere Methode zur neurophysiologischen Überwachung. In dieser Studie wurde die Wertigkeit des simultanen Ableitens von SSEP und EEG Signalen untersucht. Methode: Dreizehn Patienten (7 Frauen, 6 Männer, mittleres Alter 53.5 Jahre), welche sich dem Clipping eines intrakraniellen Aneurysma unterzogen, wurden eingeschlossen. Die SSEP Latenz 1 (Lat1), Latenz 2 (Lat2) und Amplitude (Amp) wurden kontinuierlich gemessen. Verminderung der Amplitude > 50% oder Verlängerungen der Latenzen > 10% gegenüber den Ausgangswerten wurden als signifikante Ereignisse bewertet. Das EEG wurde mittels einer subduralen Grid-Elektrode gemessen. Alpha % (Al%), Alpha-Delta-Ratio (ADR) und Total Power (TP) wurden ausgewertet. Resultate: Circa 9000 Einzelwerte wurden analysiert. Statistisch signifikante Korrelationen traten zwischen Al% und Amp (K=0.5) auf. Dabei zeigten sich die Veränderungen im EEG (Al%) 6 Minuten vor Ereignissen im SSEP (Amp). Statistisch signifikante Korrelationen traten ebenfalls zwischen Al% und Amp-Ereignissen (K=-0.4) auf. In 6/7 Patienten traten die Al%-Änderungen 7 Minuten vor den Amp-Änderungen auf. Noch stärkere Beziehungen ergaben sich zwischen Lat2 und allen EEG Modalitäten, jedoch reichte die Gesamtzahl der Datenpunkte nicht aus, um statistische Signifikanzen herzuleiten. Schlussfolgerung: Dies ist die erste Beschreibung von signifikanten Beziehungen zwischen quantitativem SSEP und EEG während zerebrovaskulären Operationen. Das quantitative EEG hat das Potenzial, frühe ischämische Ereignisse eher zu detektieren als dies mit SSEP möglich ist. / Introduction: SSEP is established for monitoring patients undergoing cerebrovascular procedures. EEG is another means of neurophysiologic monitoring. The value of a simultaneous SSEP and EEG monitoring was investigated. Methods: Thirteen patients (7 women, 6 men; mean 53.5 years) undergoing cerebral aneurysm clipping were included. SSEP Latency 1 (Lat1), Latency 2 (Lat 2) and Amplitude (Amp) were measured. An Amp decrease >50% or prolongation of Lat >10% were considered significant events. Subdural grid electrodes were utilized to measure EEG. Alpha% (Al%), Alpha-Delta Ratio (ADR) and Total Power (TP) were computed. Results: Approximately 9000 values were analyzed. Statistically significant correlations occurred between Al% and Amp (K=-0.5). EEG (Al%) changes occurred 6 minutes prior to SSEP (Amp) changes. Statistically significant correlations between Al% and Amp events (K0-0.4) occurred, with Al% values changing 7 minutes prior to Amp values in 6/7 patients. A stronger relationship was found between Lat 2 and EEG modalities, but there were not enough data points to achieve statistical significance. Conclusion: This is the first description of significant relationships between quantitative SSEP and EEG during cerebrovascular surgery. Quantitative EEG has the potential to detect early ischemic events prior to SSEP.

Background Camera-based photoplethysmography (cbPPG) is a measurement technique which enables remote vital sign monitoring by using cameras. To obtain valid plethysmograms, proper regions of interest (ROIs) have to be selected in the video data. Most automated selection methods rely on specific spatial or temporal features limiting a broader application. In this work, we present a new method which overcomes those drawbacks and, therefore, allows cbPPG to be applied in an intraoperative environment. Methods We recorded 41 patients during surgery using an RGB and a near-infrared (NIR) camera. A Bayesian skin classifier was employed to detect suitable regions, and a level set segmentation approach to define and track ROIs based on spatial homogeneity. Results The results show stable and homogeneously illuminated ROIs. We further evaluated their quality with regards to extracted cbPPG signals. The green channel provided the best results where heart rates could be correctly estimated in 95.6% of cases. The NIR channel yielded the highest contribution in compensating false estimations. Conclusions The proposed method proved that cbPPG is applicable in intraoperative environments. It can be easily transferred to other settings regardless of which body site is considered.

Background Camera-based photoplethysmography (cbPPG) is a measurement technique which enables remote vital sign monitoring by using cameras. To obtain valid plethysmograms, proper regions of interest (ROIs) have to be selected in the video data. Most automated selection methods rely on specific spatial or temporal features limiting a broader application. In this work, we present a new method which overcomes those drawbacks and, therefore, allows cbPPG to be applied in an intraoperative environment. Methods We recorded 41 patients during surgery using an RGB and a near-infrared (NIR) camera. A Bayesian skin classifier was employed to detect suitable regions, and a level set segmentation approach to define and track ROIs based on spatial homogeneity. Results The results show stable and homogeneously illuminated ROIs. We further evaluated their quality with regards to extracted cbPPG signals. The green channel provided the best results where heart rates could be correctly estimated in 95.6% of cases. The NIR channel yielded the highest contribution in compensating false estimations. Conclusions The proposed method proved that cbPPG is applicable in intraoperative environments. It can be easily transferred to other settings regardless of which body site is considered.