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EVA: laparoscopic instrument tracking based on Endoscopic Video Analysis for psychomotor skills assessment
Ignacio Oropesa1, Patricia Sánchez-González, Magdalena K Chmarra
1Bioengineering and Telemedicine Centre (GBT), ETSI Telecomunicación, Universidad Politécnica de Madrid, Avda Complutense, 30, 28040 Madrid, Spain. ioropesa@gbt.tfo.upm.es
Introduction:
The EVA (Endoscopic Video Analysis) tracking system is a new system for extracting motions of laparoscopic instruments based on nonobtrusive video tracking. The feasibility of using EVA in laparoscopic settings has been tested in a box trainer setup.
Methods:
EVA makes use of an algorithm that employs information of the laparoscopic instrument's shaft edges in the image, the instrument's insertion point, and the camera's optical center to track the three-dimensional position of the instrument tip. A validation study of EVA comprised a comparison of the measurements achieved with EVA and the TrEndo tracking system. To this end, 42 participants (16 novices, 22 residents, and 4 experts) were asked to perform a peg transfer task in a box trainer. Ten motion-based metrics were used to assess their performance.
Results:
Construct validation of the EVA has been obtained for seven motion-based metrics. Concurrent validation revealed that there is a strong correlation between the results obtained by EVA and the TrEndo for metrics, such as path length (ρ = 0.97), average speed (ρ = 0.94), or economy of volume (ρ = 0.85), proving the viability of EVA.
Conclusions:
EVA has been successfully validated in a box trainer setup, showing the potential of endoscopic video analysis to assess laparoscopic psychomotor skills. The results encourage further implementation of video tracking in training setups and image-guided surgery.
