Granted Patent B2

US 12,510,963 · App. 18/931,882 · Granted Dec 30, 2025

Inventor: Rajshekar Guda Subhash (San Jose, CA)

G06F3/013G06F3/015G06F3/016

Abstract

Claims (35)

1 . A human-computer interface system for selecting a target presented on a display, the system comprising:

an eye-tracking unit configured to capture gaze patterns of a user;

a neural signal capture unit configured to detect neural signals dependent on brain electrical activity from the user; and

a processing unit configured to:

analyze the gaze patterns to identify user fixation on a particular displayed target,

analyze the neural signals to identify an anticipatory negative potential associated with the user's intent to select the particular target; and

initiate a target selection of the particular target based, at least partially, on the identified anticipatory negative potential;

wherein said processing unit is further configured to employ a real-time prediction model to analyze the gaze patterns and neural signals to predict an intention to select the particular target, and to initiate a target selection of the particular target based at least partially on the predicted intention to select; and

wherein the anticipatory negative potential comprises at least one pattern selected from the group of a Stimulus-Preceding Negativity (SPN) and a Contingent Negative Variation (CNV).

2 . The system of claim 1 wherein the gaze patterns comprise at least one dynamic selected from the group of gaze coordinates, gaze direction, gaze origin vectors, pupil dilation/constriction rate, saccade velocity, gaze velocity, fixation duration, saccade amplitude, and micro-saccade distribution.

3 . The system of claim 1 , further comprising a feedback unit configured to provide feedback to the user in response to the initiated target selection, the feedback including at least one feedback from the group of visual feedback, audio feedback, and tactile/haptic feedback.

4 . The system of claim 3 , wherein the feedback comprises a change in at least one visual characteristic of the selected target.

5 . The system of claim 1 wherein said processing unit is further configured to allow de-selection of a previously selected target.

6 . A method for selecting a target presented on a display, comprising the steps of:

capturing gaze patterns of a user using an eye-tracking unit;

detecting neural signals of the user using a neural signal capture unit;

analyzing the gaze patterns and neural signals to identify an anticipatory negative potential associated with the user's intent to select a particular target; and

initiating a target selection of the particular target based, at least partially, on the identified anticipatory negative potential; and

employing a real-time prediction model to analyze the gaze patterns and neural signals to predict an intention to select the particular target, and to initiate a target selection of the particular target based at least partially on the predicted intention to select;

wherein the anticipatory negative potential comprises at least one pattern selected from the group of a Stimulus-Preceding Negativity (SPN) and a Contingent Negative Variation (CNV).

7 . The method of claim 6 , wherein the gaze patterns comprise at least one dynamic selected from the group of gaze coordinates, gaze direction, gaze origin vectors, pupil dilation/constriction rate, saccade velocity, gaze velocity, fixation duration, saccade amplitude, and micro-saccade distribution.

8 . The method of claim 6 , further comprising providing feedback to the user in response to the initiated target selection, the feedback including at least one feedback from the group of visual feedback, audio feedback, and tactile/haptic feedback.

9 . The method of claim 8 , wherein the feedback comprises a change in at least one visual characteristic of the selected target.

10 . The method of claim 6 further comprising the step of:

responsive to input from the user, canceling said step of initiating a target selection, wherein said input includes at least one input selected from the group of deliberate input entered by action of the user and neural signals indicating a false positive.

11 . A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform a method for selecting a target presented on a display, the method comprising the steps of:

receiving gaze patterns of a user from an eye-tracking unit;

receiving neural signals of the user from a neural signal capture unit;

analyzing the gaze patterns and neural signals to identify an anticipatory negative potential associated with the user's intent to select a particular target; and

initiating a target selection of the particular target based, at least partially, on the identified anticipatory negative potential;

wherein said processor employs a real-time prediction model to analyze the gaze patterns and neural signals to predict an intention to select the particular target, and to initiate a target selection of the particular target based at least partially on the predicted intention to select; and

wherein the anticipatory negative potential comprises at least one pattern selected from the group of a Stimulus-Preceding Negativity (SPN) and a Contingent Negative Variation (CNV).

12 . The non-transitory computer-readable medium of claim 11 , wherein the gaze patterns comprise at least one dynamic selected from the group of gaze coordinates, gaze direction, gaze origin vectors, pupil dilation/constriction rate, saccade velocity, gaze velocity, fixation duration, saccade amplitude, and micro-saccade distribution.

13 . The non-transitory computer-readable medium of claim 11 , wherein the method further comprises providing feedback to the user in response to the initiated target selection, the feedback including at least one feedback from the group of visual feedback, audio feedback, and tactile/haptic feedback.

14 . The non-transitory computer-readable medium of claim 13 , wherein the feedback comprises a change in at least one visual characteristic of the selected target.

Continuity (2)

References Cited (17)