Soft-NeuroAdapt: A 3-DOF Neuro-Adaptive Patient Pose Correction System For Frameless and Maskless Cancer Radiotherapy
March 10, 2017 Β· Declared Dead Β· π IEEE/RJS International Conference on Intelligent RObots and Systems
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Authors
Olalekan Ogunmolu, Adwait Kulkarni, Yonas Tadesse, Xuejun Gu, Steve Jiang, Nicholas Gans
arXiv ID
1703.03821
Category
cs.RO: Robotics
Citations
4
Venue
IEEE/RJS International Conference on Intelligent RObots and Systems
Last Checked
4 months ago
Abstract
Precise patient positioning is fundamental to successful removal of malignant tumors during treatment of head and neck cancers. Errors in patient positioning have been known to damage critical organs and cause complications. To better address issues of patient positioning and motion, we introduce a 3-DOF neuro-adaptive soft-robot, called Soft-NeuroAdapt to correct deviations along 3 axes. The robot consists of inflatable air bladders that adaptively control head deviations from target while ensuring patient safety and comfort. The adaptive-neuro controller combines a state feedback component, a feedforward regulator, and a neural network that ensures correct adaptation. States are measured by a 3D vision system. We validate Soft-NeuroAdapt on a 3D printed head-and-neck dummy, and demonstrate that the controller provides adaptive actuation that compensates for intrafractional deviations in patient positioning.
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