INTRODUCTION: Simulation and training in surgery are very promising tools for enhancing a surgeon's skill base. Accurate tracking of hand movements can be a strategy for objectively gauging a surgeon's dexterity, although "open" work is much more difficult to evaluate than are laparoscopic tasks. To the authors' knowledge, a system taking into account the movements of each finger joint has never been applied to open surgery simulation. This work intends to make up for this shortcoming and to perform a data analysis of the surgeon's entire gesture. MATERIALS AND METHODS: The authors developed a sensory glove to measure flexion/extension of each finger joint and wrist movement. Totally 9 experts and 9 novices performed a basic suturing task and their manual performances were recorded within 2 days of measurements. Intraclass correlation coefficients were calculated to assess the ability of the executors to repeat and reproduce the proposed exercise. Wilcoxon signed-rank tests and Mann-Whitney U-tests were used to determine whether the 2 groups differ significantly in terms of execution time, repeatability, and reproducibility. Finally, a questionnaire was used to gather operators' subjective opinions. RESULTS: The experts needed a similar reduced execution time comparing the 2 recording sessions (p = 0.09), whereas novices spent more time during the first day (p = 0.01). Repeatability did not differ between the 2 days, either for experts (p = 0.26) or for novices (p = 0.86). The 2 groups performed differently in terms of time (p < 0.001), repeatability (p = 0.01), and reproducibility (p < 0.001) of the same gesture. The system showed an overall moderate repeatability (intraclass correlation coefficient: experts = 0.64; novices = 0.53) and an overall high reproducibility. The questionnaire revealed performers' positive feedback with the glove. CONCLUSIONS: This initial experience confirmed the validity and reliability of the proposed system in objectively assessing surgeons' technical skill, thus paving the way to a more complex project involving open surgery simulation.
INTRODUCTION: Simulation and training in surgery are very promising tools for enhancing a surgeon's skill base. Accurate tracking of hand movements can be a strategy for objectively gauging a surgeon's dexterity, although "open" work is much more difficult to evaluate than are laparoscopic tasks. To the authors' knowledge, a system taking into account the movements of each finger joint has never been applied to open surgery simulation. This work intends to make up for this shortcoming and to perform a data analysis of the surgeon's entire gesture. MATERIALS AND METHODS: The authors developed a sensory glove to measure flexion/extension of each finger joint and wrist movement. Totally 9 experts and 9 novices performed a basic suturing task and their manual performances were recorded within 2 days of measurements. Intraclass correlation coefficients were calculated to assess the ability of the executors to repeat and reproduce the proposed exercise. Wilcoxon signed-rank tests and Mann-Whitney U-tests were used to determine whether the 2 groups differ significantly in terms of execution time, repeatability, and reproducibility. Finally, a questionnaire was used to gather operators' subjective opinions. RESULTS: The experts needed a similar reduced execution time comparing the 2 recording sessions (p = 0.09), whereas novices spent more time during the first day (p = 0.01). Repeatability did not differ between the 2 days, either for experts (p = 0.26) or for novices (p = 0.86). The 2 groups performed differently in terms of time (p < 0.001), repeatability (p = 0.01), and reproducibility (p < 0.001) of the same gesture. The system showed an overall moderate repeatability (intraclass correlation coefficient: experts = 0.64; novices = 0.53) and an overall high reproducibility. The questionnaire revealed performers' positive feedback with the glove. CONCLUSIONS: This initial experience confirmed the validity and reliability of the proposed system in objectively assessing surgeons' technical skill, thus paving the way to a more complex project involving open surgery simulation.
Authors: Manuel González-Sánchez; Maria Ruiz-Muñoz; Ana Belén Ávila-Bolívar; Antonio I Cuesta-Vargas Journal: BMC Med Educ Date: 2016-10-06 Impact factor: 2.463
Authors: Giovanni Saggio; Pietro Cavallo; Mariachiara Ricci; Vito Errico; Jonathan Zea; Marco E Benalcázar Journal: Sensors (Basel) Date: 2020-07-11 Impact factor: 3.576