Soft-NeuroAdapt: A 3-DOF Neuro-Adaptive Patient Pose Correction System For Frameless and Maskless Cancer Radiotherapy

March 10, 2017 Β· Declared Dead Β· πŸ› 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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