Eye-contact training system using gaze feedback
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Solution Overview
Problem
Current eye tracking systems primarily focus on tracing a user's gaze but lack the capability to direct the user's gaze to specific areas for effective eye-contact training, which is crucial for improving public speaking skills and confidence.
Innovation Solution
A computer-implemented method that uses eye-gaze data to guide a user's gaze towards desired areas on a display, providing real-time feedback based on predefined rules to enhance eye contact during speeches or presentations, utilizing a virtual audience interface to simulate eye contact with spectators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If eye tracking systems only trace user gaze without providing guidance, then the system complexity remains low, but the effectiveness for eye-contact training is insufficient
Solution Approach 1:
The system provides real-time feedback by evaluating the user's gaze direction against desired gaze areas and delivering feedback signals to guide the user's eye movements. This feedback mechanism transforms a simple tracking system into an effective training tool by continuously monitoring and guiding user behavior.
Solution Approach 2:
The system introduces an intermediary evaluation component that mediates between the raw gaze data and the training objective. This intermediary layer processes gaze coordinates, compares them with target areas, and generates guidance signals, effectively bridging the gap between tracking and training functions.
2Reliability
If the system provides detailed real-time feedback and guidance, then the training effectiveness improves, but the ease of operation decreases
Solution Approach 1:
The system enables self-service training by automatically evaluating gaze data and providing guidance without requiring manual intervention. The automated evaluation and feedback delivery allow users to independently conduct eye-contact training sessions, maintaining ease of operation while ensuring training effectiveness.
3Measurement precision
If the system tracks and evaluates gaze direction continuously, then the measurement precision of eye contact level improves, but the use of energy increases
Solution Approach 1:
The system employs periodic evaluation rather than continuous processing, assessing gaze direction at regular intervals or at key moments during speech. This periodic approach maintains measurement precision for eye-contact evaluation while reducing the computational load and energy consumption associated with constant real-time processing.
Data Source
AI summary
The present disclosure relates to digital solutions for eye-contact training. According to a first aspect, the disclosure relates to a computer-implemented method for eye-contact training. The method comprises presenting S1, on the one or more displays, one or more user interface objects indicative of one or more desired gaze areas representing one or more spectators of a virtual audience of the user. The method further comprises obtaining S3, using the camera, eye-gaze data indicative of the user's actual gaze direction and evaluating S4 a level of eye contact between the user and the virtual audience based on one or more rules defining a level of eye contact. The method also comprises providing S5 user feedback indicative of the evaluated level of eye-contact to the user. The disclosure also relates to an electronic user device and to a computer program configured to perform the method.