Eye Tracking and BCI Fusion for Accurate Gaze Identification
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Solution Overview
Problem
Current brain-computer interface (BCI) systems and eye tracking devices face inaccuracies in determining user gaze direction, especially on complex user interfaces, and are aesthetically unpleasing due to the need for multiple visual stimuli, making interaction cumbersome for some individuals.
Innovation Solution
A system combining eye tracking and electrophysiological monitoring using a wearable interface to detect visually evoked potentials, allowing the client device to display unique frequencies for interactable objects and match these frequencies with brain activity signals to accurately identify the user's focus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If eye tracking devices are used to determine user gaze direction, then interaction efficiency is improved, but measurement precision deteriorates on complex user interfaces
Solution Approach 1:
The patent combines eye tracking technology with brain-computer interface (BCI) technology to create a hybrid system. The eye tracking component provides initial gaze direction estimation, while the BCI component using EEG signals provides verification and correction, resulting in more accurate object identification on complex interfaces than either technology alone could achieve.
2Measurement precision
If visual stimuli with unique frequencies are displayed for each interactable object, then object identification accuracy is improved, but device complexity increases
Solution Approach 1:
Instead of displaying visual stimuli for all interactable objects simultaneously, the system applies stimuli only to objects within the user's current gaze region. This partial application of the stimulus approach maintains identification accuracy for relevant objects while avoiding the complexity and aesthetic degradation that would result from stimulating all objects on the interface.
Solution Approach 2:
The visual stimuli with unique frequencies are applied locally to specific regions of the interface based on eye tracking data, rather than uniformly across the entire interface. This localized application ensures that only the objects the user is actually looking at receive the frequency-coded stimuli, reducing overall system complexity while maintaining precision where needed.
3Measurement precision
If visual stimuli are displayed for each interactable object, then object identification is improved, but aesthetic quality deteriorates
Solution Approach 1:
Visual stimuli are displayed only for interactable objects within the user's current gaze region rather than for all objects on the interface. This selective stimulation maintains aesthetic quality by avoiding clutter while still providing sufficient visual cues for accurate object identification in the relevant area.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides accurate and efficient user interaction by reducing the need for multiple visual stimuli, enhancing user experience and interface aesthetics while improving interaction efficiency.
Implementation Method 1
a wearable brain computer interface (BCI) including electrodes configured to receive visually evoked signals from a body region of the user
Implementation Method 2
an eye tracking device operable to estimate a user's gaze direction
Data Source
AI summary
A brain computer interface system includes a wearable interface, an eye tracking device, and a client device for determining what object a user is looking at on an electronic display. The client device determines a region on the electronic display based on an estimated user gaze direction received from the eye tracking device. For each virtual object in the gaze region, the client device displays a visual stimulus with a unique frequency. The client device receives from the wearable interface an electrical potential signal measured at the user's brain and evoked by a visual stimulus on the electronic display. The client device identifies the object in the gaze region with a stimulus frequency matching a frequency derived from the potential signal, and executes instructions relating to the object.


