Soft-NeuroAdapt: A 3-DOF neuro-adaptive patient pose correction system for frameless and maskless cancer radiotherapy
Olalekan Ogunmolu, Adwait Kulkarni, Yonas Tadesse, Xuejun Gu, Steve Jiang, Nicholas Gans
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.
BibTeX
@inproceedings{iros2017_softneuroadapta3,
title = {Soft-NeuroAdapt: A 3-DOF neuro-adaptive patient pose correction system for frameless and maskless cancer radiotherapy},
author = {Olalekan Ogunmolu and Adwait Kulkarni and Yonas Tadesse and Xuejun Gu and Steve Jiang and Nicholas Gans},
booktitle = {IROS 2017},
year = {2017}
}