Compared with traditional open surgery,laparoscopic surgery significantly reduces bodily trauma,postoperative pain,and hospitalization duration.However,owing to the small size of incisions and the counterintuitive mot...Compared with traditional open surgery,laparoscopic surgery significantly reduces bodily trauma,postoperative pain,and hospitalization duration.However,owing to the small size of incisions and the counterintuitive motion of surgical tools,longer training cycles are required for surgeons to achieve fine operational skills.This paper presents a laparoscopic surgery simulator with haptic-feedback control(LSHC-6)that provides a reliable and cost-effective training alternative for surgeons.In addition to the structural diagram,kinematic analysis,and gravity compensation algorithm,a particle swarm optimization algorithm(PSO)is applied to optimize the structural parameters of the simulator by evaluating its workspace,global dexterity,and gravity compensation ability.A prototype system was developed and evaluated using two training experiments.The results demonstrate that the simulator exhibits good operational fluidity,workspace,and stable force output,effectively meeting the needs of laparoscopic surgical training.展开更多
基金Supported by the National Key Research and Development Program of China(Grant No.2022YFB4500604)in part by the Natural Science Foundation of Guangdong Province,China(Grant No.2022A1515010100 and 2024A1515010140).
文摘Compared with traditional open surgery,laparoscopic surgery significantly reduces bodily trauma,postoperative pain,and hospitalization duration.However,owing to the small size of incisions and the counterintuitive motion of surgical tools,longer training cycles are required for surgeons to achieve fine operational skills.This paper presents a laparoscopic surgery simulator with haptic-feedback control(LSHC-6)that provides a reliable and cost-effective training alternative for surgeons.In addition to the structural diagram,kinematic analysis,and gravity compensation algorithm,a particle swarm optimization algorithm(PSO)is applied to optimize the structural parameters of the simulator by evaluating its workspace,global dexterity,and gravity compensation ability.A prototype system was developed and evaluated using two training experiments.The results demonstrate that the simulator exhibits good operational fluidity,workspace,and stable force output,effectively meeting the needs of laparoscopic surgical training.
