Article... IEEE International Conference on System Engineering and Technology. IEEE International Conference on System Engineering and Technology2021
Quantifying Performance in Robotic Surgery Training Using Muscle-Based Activity Metrics.
Article in ... IEEE International Conference on System Engineering and Technology. IEEE International Conference on System Engineering and Technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Training to perform robotic surgery is time-consuming with uncertain metrics of the level of achieved skill. We tested the feasibility of using muscle co-contraction as a metric to quantify robotic surgical skill in a virtual simulation environment. We recruited six volunteers with varying skill levels in robotic surgery. The volunteers performed virtual tasks using a robotic console while we recorded their muscle activity. A co-contraction metric was then derived from the activity of pairs of opposing hand muscles and compared to the scores assigned by the training software. We found that muscle-based metrics were more sensitive than motion-based scores in quantifying the different levels of skill between simulated tasks and in novices vs. experts across different tasks. Therefore, muscle-based metrics may help quantify in general terms the level of robotic surgical skill and could potentially be used for biofeedback to increase the rate of learning.
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