6533b873fe1ef96bd12d4f6d
RESEARCH PRODUCT
Postprocessing algorithm for automated analysis of pelvic intraoperative neuromonitoring signals
Thilo B. KruegerCeline WegnerKlaus-peter HoffmannDaniel W. KauffWerner Kneistsubject
Signal processingpostprocessing algorithmbusiness.industryRBiomedical Engineeringpelvic intraoperative neuromonitoringsignal analysis03 medical and health sciences0302 clinical medicine030220 oncology & carcinogenesisMedicineMedicine030211 gastroenterology & hepatologyComputer visionArtificial intelligencebusinessdescription
Abstract Two dimensional pelvic intraoperative neuromonitoring (pIONM®) is based on electric stimulation of autonomic nerves under observation of electromyography of internal anal sphincter (IAS) and manometry of urinary bladder. The method provides nerve identification and verification of its’ functional integrity. Currently pIONM® is gaining increased attention in times where preservation of function is becoming more and more important. Ongoing technical and methodological developments in experimental and clinical settings require further analysis of the obtained signals. This work describes a postprocessing algorithm for pIONM® signals, developed for automated analysis of huge amount of recorded data. The analysis routine includes a graphical representation of the recorded signals in the time and frequency domain, as well as a quantitative evaluation by means of features calculated from the time and frequency domain. The produced plots are summarized automatically in a PowerPoint presentation. The calculated features are filled into a standardized Excel-sheet, ready for statistical analysis.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2016-09-01 | Current Directions in Biomedical Engineering |