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A Novel Smart-Phone Based Motion Analysis Platform for Real Time Measurement of Surgical Performance
Vivian E. De Ruijter*1, Catherine Wong1, Adrian Rodriguez1, Kiruthiga Nandagopal1, Lee L. Swanstrom2, James N. Lau1
1General Surgery, Stanford University, Menlo Park, CA; 2Division of Minimally Invasive Surgery, IHU Strasbourg S/c IRCAD, Strasbourg, France
INTRODUCTION As the need for objective and structured assessment of technical performance and proficiency of surgical skills grows, new methods and measurement tools have emerged over the last few years. Several studies have been devoted to the development of metrics for skills assessment and supported evidence for the use of motion analysis for laparoscopic skills assessment. However, motion analysis carries limitations including high costs and access issues. We hypothesize that the use of a portable metric competency platform using widely available mobile technology will allow a low cost interface for real time surgical performance for education and training purposes.
AIM The aim of this study is to establish a proof of concept of a smart-phone based motion analysis assessment system for laparoscopic surgery.
METHODS The proposed assessment system consists of a 1) smart-phone, 2) yellow bio-compatible colored tape applied to the instrument tip for marking, and 3) dedicated optical tracking software developed with OpenCV4Android SDK, combining accelerometer data with optical color tracking of the surgical instruments. A proof of concept was performed of the tracking platform in a laparoscopic box trainer using the Fundamentals of Laparoscopic Surgery (FLSR). This included a peg transfer and an intra-corporeal suturing task. The researchers preliminarily tested the current tracking software and determined: 1) the percentage of time during which the software identified contour and color of the tracked instrument, 2) time of task completion in seconds (s), and 3) an instrument path length in pixel (px) coordinates.
RESULTS Out of 20 tests performed, the optical tracking software tracked the laparoscopic instruments an average of 98.21% of the time for both FLS tasks, respectively 98.47% for the peg transfer and 98.21% for the intra-corporeal suturing task. The peg transfer task was completed on average in 69.5s (SD 3.2) and provided an average path length of 10.22px (SD 4.97) for the right instrument and 42.57px (SD 11.70) for the left instrument. The intra-corporeal suturing task was completed in 102.6s (SD 25.96) and an average path length was measured of 42.34px (SD 13.27) for the right instrument and 64.08px (SD 18.32) for the left instrument.
CONCLUSION This study provided preliminary data and demonstrated feasibility of a smart-phone based portable competency platform for real time laparoscopic performance based on motion tracking. The software used has the ability to run on both android-based phones and head-mounted displays, making it possible to use this during real time surgical procedures and possibly to other surgical and endoscopic disciplines. Further studies are ongoing to demonstrate the feasibility and reliability of this platform in clinical practice.
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