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.

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This paper describes a next-generation nursing education simulator, the endotracheal suctioning training environment simulator (ESTE-SIM), which is capable of interactively reproducing vital reactions. With the spread of home treatment, care providers who have received a certain level of nursing education should be increased, not limited to conventional health-care professionals. A great gap exists between simulations under restricted conditions that have been practiced in conventional nursing education and those in the actual clinical site, thus creating a burden on nurses and patients. If a simulator that approaches real clinical situations can be developed, it will not only contribute to lessening the burden on nurses but also improve the quality of nursing care. The ESTE-SIM, which simulates endotracheal suctioning, can measure the movements of the suction catheter inserted in the trachea. The measurement information is used to estimate the progress of the nursing maneuver, which is then used to reproduce vital reactions, including dynamic facial expression changes based on projection mapping and monitor-displayed vital signs. To design and control the vital reactions, a mathematical model to determine the behavior of the simulator is formulated based on the actual measurement data of the vital reactions of patients and the experiential knowledge of nurses. By integrating these element technologies, we developed a novel interactive nursing education simulator capable of recreating typical vital reactions that occur during the basic endotracheal suctioning maneuver.