Smith Warren D, Berguer Ramon
Biomedical Engineering, California State University, Sacramento, 6000 J Street, Sacramento, CA 95819-6019, USA.
Stud Health Technol Inform. 2004;98:363-9.
Monitoring the workload of surgeons while they perform minimally invasive surgery (MIS) tasks can help them learn to reduce effort as they improve performance and can help develop better human-technology interfaces for MIS. To monitor workload, we developed a personal computer based virtual instrument (VI) that uses orientation sensors worn on the surgeon's left and right upper arms to measure upper arm flexion, abduction, and outward rotation angles. From these sensors, we compute indices of effort and integrated effort. One effort index is the upper arm elevation angle. The time integral of this index provides a corresponding integrated effort index. A second effort index is hand velocity. Hand trajectory length is the corresponding integrated effort index. We used the workload monitor VI to study 29 volunteer surgeon subjects while they performed a knot-tying task in a laparoscopic trainer at a standard MIS station. For five of these subjects, we also monitored the workload indices while they performed simulated MIS tasks on a virtual reality Procedicus MIST System. For the subject group, integrated effort, but not level of effort, decreased with increased performance. At each performance level, some subjects worked much harder than others, suggesting that these subjects could benefit by learning to reduce their effort levels. The workload measures from the arm sensors augmented the performance measures provided by the MIST system.
在外科医生进行微创手术（MIS）任务时监测其工作量，有助于他们在提高手术表现的同时学会减少用力，并有助于开发更好的MIS人机技术界面。为了监测工作量，我们开发了一种基于个人计算机的虚拟仪器（VI），它使用佩戴在外科医生左右上臂的方向传感器来测量上臂的屈曲、外展和向外旋转角度。根据这些传感器，我们计算用力指数和综合用力指数。一个用力指数是上臂抬高角度。该指数的时间积分提供相应的综合用力指数。第二个用力指数是手部速度。手部轨迹长度是相应的综合用力指数。我们使用工作量监测VI对29名志愿外科医生受试者进行了研究，他们在标准MIS工作站的腹腔镜训练器中进行打结任务。对于其中5名受试者，我们还在他们在虚拟现实Procedicus MIST系统上执行模拟MIS任务时监测了工作量指数。对于受试者组，随着表现的提高，综合用力而非用力水平下降。在每个表现水平上，一些受试者比其他受试者更加努力，这表明这些受试者可以通过学习降低用力水平而受益。来自手臂传感器的工作量测量补充了MIST系统提供的表现测量。
