Abstract
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.