319 Analysis of the video motion tracking system ‘Kinovea’ to assess surgical movements during robot-assisted radical prostatectomy. assessment of the movements using kinovea was time consuming and had its challenges, Kinovea does give the researcher the means to simultaneously assess the anatomy during analysis of the surgical videos. One of the alternatives to Kinovea, the dVlogger, only provides raw movement data without the ability to correlate this to the surgical videos.8 The data represented in this study are the results of the parts were automated tracking was possible, no data was interpolated. During tracking the software was frequently not able to follow the selected pixels correctly, which was then manually corrected by the researcher by moving the tracking point back to the originally selected point on the instrument. The movement data due to the repositioning of the tracker point was deleted from the data after manual verification and checking of the path in the video file. The place of the surgery within the learning curve of the surgeon could influence the results of this type of analysis. Other studies have shown that arm movement analysis can be used to separate beginning surgeons from experts.9,16 In this study the selection of cases has been adjusted to take into account when the surgery was performed in order to reduce the influence of learning curve on the results of this study. The Kinovea program was able to assess surgeons’ skills using existing surgical videos rather than in a simulator, without needing extra equipment for movement tracking in laparoscopic surgery.9 The analysis in robot assisted surgery does not appear to be as valid as the analysis in laparoscopic surgery. In Robot assisted surgery the frequent manual replacement and moving of the tracking point during the Kinovea analysis adds a subjective component to an otherwise objective measurement. Further research with larger groups of patients and a different automated tracking system is needed in order to investigate the relation between surgical movements, surgical skills, and postoperative outcomes. A combination of video assessment and dVlogger data could hold the key to find metrics related to postoperative outcome. To the knowledge of this group no such analysis method is currently available to be used in a retrospective analysis without additional equipment for tracking the movements. The use of artificial intelligence in combining both video assessment and surgical movements assessment could eliminate human interference and lead to an objective and automated assessment of the surgical video.
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