Minimally invasive surgery training using multiple port sites to improve performance
Minimally invasive surgery training using multiple port sites to improve performance
复制标题
使用多个端口站点进行微创手术培训以提高性能
DOI：
10.1007/s00464-013-3307-7
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
J. Lodge
中科院分区：
文献类型：
--
作者：
A. White;Oscar T. Giles;R. Sutherland;O. Ziff;M. Mon;R. Wilkie;J. Lodge
背景资料
结构学习理论认为，经历运动任务的变化，使中枢神经系统提取一般规则的任务具有类似的结构，规则，随后可以应用到新的情况。复杂的微创手术（MIS）需要不同的端口位置，但切换端口会改变产生手术器械相同终点控制所需的肢体运动。本研究的目的是确定结构学习理论是否可以应用于MIS通知training methods.MethodsA平板电脑运行定制软件被放置在腹腔镜箱教练和连接到位于眼睛水平的显示器。参与者（右手，非外科医生，平均年龄= 23.2岁）使用标准腹腔镜抓钳在屏幕上的位置之间移动。有两个训练组：M组（n = 10）使用多个端口站点进行训练，S组（n = 10）使用单个端口站点进行训练。一个新的港口网站被用来作为一个测试的泛化。性能指标是速度和准确性（SACF）和标准化加加速度的组合（NJ;运动“平滑度”的测量）.ResultsThe M组在测试中表现出比S组统计学上显著的性能优势，如由改进的SACF（p < 0.05）和NJ（p < 0.05）.ConclusionsThis study has demonstrated the potential benefits of incorporating a structural learning approach within MIS training.这在培训初级外科医生和开发手术模拟设备时可能具有实际应用。
AbstractBackground
Structural learning theory suggests that experiencing motor task variation enables the central nervous system to extract general rules regarding tasks with a similar structure—rules that can subsequently be applied to novel situations. Complex minimally invasive surgery (MIS) requires different port sites, but switching ports alters the limb movements required to produce the same endpoint control of the surgical instrument. The purpose of the present study was to determine if structural learning theory can be applied to MIS to inform training methods.MethodsA tablet laptop running bespoke software was placed within a laparoscopic box trainer and connected to a monitor situated at eye level. Participants (right-handed, non-surgeons, mean age = 23.2 years) used a standard laparoscopic grasper to move between locations on the screen. There were two training groups: the M group (n = 10) who trained using multiple port sites, and the S group (n = 10) who trained using a single port site. A novel port site was used as a test of generalization. Performance metrics were a composite of speed and accuracy (SACF) and normalized jerk (NJ; a measure of movement ‘smoothness’).ResultsThe M group showed a statistically significant performance advantage over the S group at test, as indexed by improved SACF (p < 0.05) and NJ (p < 0.05).ConclusionsThis study has demonstrated the potential benefits of incorporating a structural learning approach within MIS training. This may have practical applications when training junior surgeons and developing surgical simulation devices.
前馈和反馈控制中的结构学习。
影响因子：
2.5
作者：
Yousif N
通讯作者：
Yousif N
练习期间增强的机械透明度阻碍了复杂工具的开环控制
影响因子：
2
作者：
Sülzenbrück
通讯作者：
Sülzenbrück