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Updated: Dec 9, 2025
Step By Step: Microsurgical training method combining two nonliving animal models
Published on: May 9, 2015
Motion analysis for better understanding of psychomotor skills in laparoscopy: objective assessment-based simulation
Koki Ebina1, Takashige Abe2, Madoka Higuchi3
1Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan.
Background:
Our aim was to characterize the motions of multiple laparoscopic surgical instruments among participants with different levels of surgical experience in a series of wet-lab training drills, in which participants need to perform a range of surgical procedures including grasping tissue, tissue traction and dissection, applying a Hem-o-lok clip, and suturing/knotting, and digitize the level of surgical competency.
Methods:
Participants performed tissue dissection around the aorta, dividing encountered vessels after applying a Hem-o-lok (Task 1), and renal parenchymal closure (Task 2: suturing, Task 3: suturing and knot-tying), using swine cadaveric organs placed in a box trainer under a motion capture (Mocap) system. Motion-related metrics were compared according to participants' level of surgical experience (experts: 50 ≤ laparoscopic surgeries, intermediates: 10-49, novices: 0-9), using the Kruskal-Wallis test, and significant metrics were subjected to principal component analysis (PCA).
Results:
A total of 15 experts, 12 intermediates, and 18 novices participated in the training. In Task 1, a shorter path length and faster velocity/acceleration/jerk were observed using both scissors and a Hem-o-lok applier in the experts, and Hem-o-lok-related metrics markedly contributed to the 1st principal component on PCA analysis, followed by scissors-related metrics. Higher-level skills including a shorter path length and faster velocity were observed in both hands of the experts also in tasks 2 and 3. Sub-analysis showed that, in experts with 100 ≤ cases, scissors moved more frequently in the "close zone (0 ≤ to < 2.0 cm from aorta)" than those with 50-99 cases.
Conclusion:
Our novel Mocap system recognized significant differences in several metrics in multiple instruments according to the level of surgical experience. "Applying a Hem-o-lok clip on a pedicle" strongly reflected the level of surgical experience, and zone-metrics may be a promising tool to assess surgical expertise. Our next challenge is to give completely objective feedback to trainees on-site in the wet-lab.
