Surgical task expertise detected by a self-organizing neural network map
arXiv:2106.08995
Abstract
Individual grip force profiling of bimanual simulator task performance of experts and novices using a robotic control device designed for endoscopic surgery permits defining benchmark criteria that tell true expert task skills from the skills of novices or trainee surgeons. Grip force variability in a true expert and a complete novice executing a robot assisted surgical simulator task reveal statistically significant differences as a function of task expertise. Here we show that the skill specific differences in local grip forces are predicted by the output metric of a Self Organizing neural network Map (SOM) with a bio inspired functional architecture that maps the functional connectivity of somatosensory neural networks in the primate brain.
arXiv commentConference on Automation in Medical Engineering AUTOMED21, University Hospital Basel, Switzerland, 2021, June 8-9
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