gms | German Medical Science

59th Annual Meeting of the German Society of Neurosurgery (DGNC)
3rd Joint Meeting with the Italian Neurosurgical Society (SINch)

German Society of Neurosurgery (DGNC)

1 - 4 June 2008, Würzburg

Automated real-time monitoring: Intraoperative evaluation of facial nerve function during vestibular schwannoma surgery

Automatisiertes Echtzeit-Monitoring: Die intraoperative Beurteilung der Fazialisfunktion bei Operationen an Vestibularisschwannomen

Meeting Abstract

  • corresponding author J. Prell - Department of Neurosurgery, Martin-Luther-University Halle-Wittenberg
  • S. Rampp - Department of Neurosurgery, Martin-Luther-University Halle-Wittenberg
  • J. Rachinger - Department of Neurosurgery, Martin-Luther-University Halle-Wittenberg
  • C. Scheller - Department of Neurosurgery, Martin-Luther-University Halle-Wittenberg
  • C. Strauss - Department of Neurosurgery, Martin-Luther-University Halle-Wittenberg

Deutsche Gesellschaft für Neurochirurgie. Società Italiana di Neurochirurgia. 59. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie e.V. (DGNC), 3. Joint Meeting mit der Italienischen Gesellschaft für Neurochirurgie (SINch). Würzburg, 01.-04.06.2008. Düsseldorf: German Medical Science GMS Publishing House; 2008. DocP 100

The electronic version of this article is the complete one and can be found online at:

Published: May 30, 2008

© 2008 Prell et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Objective: One of the main problems of neurophysiologic monitoring is the ubiquitous time delay needed for analysis of the aquired data. Thus, real-time neuromonitoring is a strongly desired goal. The electrophysiological parameter “traintime” is known to be closely correlated with the extent of postoperative facial nerve paresis. It is a quantitative expression of overall A-train activity. The system presented was designed to monitor traintime in real-time.

Methods: A dedicated hard- and software-platform for automated analysis of the intraoperative facial nerve EMG was specifically designed. It is capable of monitoring 16 EMG-channels simultaneously. The automatic detection of A-trains is performed by a software-algorithm which incorporates several new techniques for real-time analysis of non-stationary biosignals. It is based on morphology, frequency and rhythmic characteristics of electrophysiological EMG-patterns.

Results: Intraoperative A-trains can be detected and measured automatically by the described method for real-time analysis. With the occurrence of A-trains, an acoustic warning-signal is emitted. Each of the three main branches of the facial nerve is monitored with three overlapping channels of virtual bipolar EMG. The predominant channel of each branch is automatically detected and traintime from the three resulting, predominant channels is calculated automatically for the estimation of overall A-train „power“. Traintime is monitored continuously and in real-time via a “traffic lights” display and also shown as an absolute numerical value during the operation. The system was tested in a consecutive series of 16 patients. It correctly foresaw disfiguring facial nerve palsy with high reliability (sensitivity 100%, specificity 67%, negative predictive value 100%, positive predictive value 70%).

Conclusions: Automated real-time-analysis of the intraoperative facial nerve EMG can critically contribute to the estimation of functional outcome in the course of the operative procedure. This option for reliable prognostic statements at any time during the operation can aid in achieving better functional outcomes in acoustic neuroma surgery.