Problem
Research questions and friction points this paper is trying to address.
neck exoskeleton
gaze control
eye-head coordination
personalization
head-neck mobility
A Biomimetic Gaze Control to Restore Head-Neck Movements
🤖 AI Summary
This study addresses the limitation that existing neck exoskeleton control strategies lack a biomimetic foundation, resulting in unnatural head movements. To restore head-neck mobility in patients with cervical muscle weakness, this work proposes a biomimetic controller based on eye tracking and the vestibulo-ocular reflex (VOR). Specifically, it establishes the first VOR dynamic model and introduces a personalized parameter-tuning algorithm to facilitate natural human-machine synergy. Experimental results demonstrate that the velocity profiles generated by the proposed system more closely align with physiological characteristics. Furthermore, intention detection accuracy is improved by an average of 24%, effectively restoring head-neck mobility for affected individuals.
📝 Abstract
Powered neck exoskeletons are developed to restore head-neck motions for those with neck muscle weakness. Current methods using hand-held input devices to control these robotic systems are unintuitive or non-viable for these populations. Alternatively, the eyes coordinate with the head to accomplish many daily tasks. Therefore, movements of the eyes can be a useful signal to control the neck exoskeletons without needing to use the hands. However, previous control models lack biobehavioral basis as well as means to personalize the control behavior, causing unnatural head-neck movements. This paper presents a novel eye-tracking controller design leveraging the vestibulo-ocular reflex to emulate natural eyehead coordination. Personalization tools were also designed, consisting of sliders to allow users to adjust the parameters of this controller. Here, we present the technical design and validation of this system in human users. Compared to the previous eye-tracking model, the new controller provides natural head motions personalized to the user through more natural velocity profiles and a 24 percent average increase of accurate motion intent detection. This system provides a powerful platform for studying eye-tracking controllers in the context of personalization and preference, and ultimately restoring the lost head-neck mobility in patient populations.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Biomimetic Gaze Control
Neck Exoskeleton
Vestibulo-Ocular Reflex
Eye-Tracking Controller
Personalization
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