# Surgical task expertise detected by a self-organizing neural network map

arXiv: https://arxiv.org/abs/2106.08995 · HTML: https://mlsanity.com/paper/2106.08995/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 14 references that are in the map.
- First posted on arXiv 3 Jun 2021.

## Builds on (most cited first, 10 of 10)

- [Deep Reinforcement Learning for the Control of Robotic Manipulation: A Focussed Mini-Review](https://mlsanity.com/paper/2102.04148/) (2021)
- [Getting nowhere fast: trade-off between speed and precision in training to execute image-guided hand-tool movements](https://mlsanity.com/paper/1803.11280/) (2018)
- [Effects of 2D and 3D image views on hand movement trajectories in the surgeons peripersonal space in a computer controlled simulator environment](https://mlsanity.com/paper/1803.11283/) (2018)
- [Seeing virtual while acting real: Visual display and strategy effects on the time and precision of eye-hand coordination](https://mlsanity.com/paper/1804.00974/) (2018)
- [Towards expert-based speed-precision control in early simulator training for novice surgeons](https://mlsanity.com/paper/1904.06710/) (2019)
- [The quantization error in a Self-Organizing Map as a contrast and colour specific indicator of single-pixel change in large random patterns](https://mlsanity.com/paper/2011.03970/) (2020)
- [Wearable Sensors for Individual Grip Force Profiling](https://mlsanity.com/paper/2011.05863/) (2020)
- [Sensors for expert grip force profiling: towards benchmarking manual control of a robotic device for surgical tool movements](https://mlsanity.com/paper/2011.06449/) (2020)
- [Correlating grip force signals from multiple sensors highlights prehensile control strategies in a complex task-user system](https://mlsanity.com/paper/2011.06452/) (2020)
- [Pixel precise unsupervised detection of viral particle proliferation in cellular imaging data](https://mlsanity.com/paper/2011.05209/) (2020)

## Abstract (arXiv)

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.