Morimasa Tomikawa, MD, PhD, Munenori Uemura, PhD, Kazuo Tanoue, MD, PhD, Makoto Hashizume, MD, PhD. Department of Advanced Medicine and Innovative Technology
Background: Hand motions of laparoscopic surgeons may reflect their skills and levels of proficiency.
Aim: This study was performed to examine the differences between the hand motions of the expert and the novice surgeons. There might be possible implication for laparoscopic surgical training.
Methods: The Kyushu University Training Center for Minimally Invasive Surgery holds a 2-day standardized laparoscopic surgical training program The instructors (group E; n=19), the trainees at pre-training (group Pre; n=27) and the trainees at post-training (group Post; n=27) underwent a laparoscopic surgical skills assessment task with a magnetic tracking sensor. The hand motions of the 3 groups were compared with detrended fluctuation analysis (DFA),unstable periodic orbit analysis (UPO), and an optimized 3-layer artificial neural network (ANN) that have learned to differentiate between novice and expert surgeons.
Results: Trend α of group E was closer to 1/f, and that of group Pre was assessed as brown noise with DFA (p<0.01). Stability of group E was significantly higher than that of group Pre with UPO (p<0.01). Total scores calculated by ANN (E/Pre/Post; 76.5/60.8/69.7) had significant differences between the 3 groups (p<0.01).
Conclusions: The hand motions of the expert surgeons were more natural and stable compared with those of the novice surgeons. Significant difference of hand motion of laparoscopic surgeon and result of training could be evaluated by mathematical analysis.
Presented at the SAGES 2017 Annual Meeting in Houston, TX.
Abstract ID: 78634
Program Number: P275
Presentation Session: Poster (Non CME)
Presentation Type: Poster