Biomimetic eye-controlled system enhances neck exoskeleton movements
A Biomimetic Gaze Control to Restore Head-Neck Movements
Robotics
Summary
Some people with weak neck muscles need help moving their heads naturally. The authors created a robotic neck device controlled by eye movements instead of hands, making it easier to use. Their system mimics how eyes and head work together in the body, so movements feel more natural. It also lets users adjust settings to fit their own preferences, resulting in better control and accuracy.
What this means in practice
- •For medical device engineers: Build eye-tracking neck exoskeletons with natural and user-personalized control for patients with neck muscle weakness.$Commercial implications: Enables production of neck assistive devices that use biomimetic eye-based control for improved patient use and comfort.
- •For assistive technology developers: Create interfaces that use eye movement signals to replace hand controls for users with limited arm or hand mobility.
Authors
Colin Rubow, Haohan Zhang
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.