Methods, systems, and non-transitory computer-readable mediums for SSVEP detection optimization
Inventors
Kim, Insoo • Shishavan, Hossein Hamidi • Golzari, Kia • Farooq, Muhamed • Dede, Ercan M.
Assignees
Denso Corp • Toyota Motor Corp • Mirise Technologies Corp • University of Connecticut Health Center
Publication Number
US-11934576-B2
Publication Date
2024-03-19
Expiration Date
2042-01-14
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Abstract
In accordance with one embodiment of the present disclosure, a method includes measuring brain activity for a target frequency and a second harmonic frequency based on a default value of display parameters for a plurality of icons, determining whether a strength of the target frequency and the second harmonic frequency are below a threshold level, and modifying one or more display parameters in response to the strength of the target frequency and the second harmonic frequency being below the threshold level.
Core Innovation
The invention involves methods, systems, and non-transitory computer-readable mediums for optimizing steady-state visually evoked potentials (SSVEP) detection in brain-computer interface (BCI) systems. This optimization is achieved by measuring brain activity at a target frequency and its second harmonic frequency based on default display parameters for multiple icons presented to a user. If the strength of these frequencies is below a certain threshold, the system modifies display parameters such as frequency, duty cycle, color, arrangement, position, and background until the measured brain activity reaches the threshold level.
The problem addressed is that SSVEP-based BCI systems require strong and clear brain signals to accurately determine user intent when interacting with flickering icons on an electronic display. Visual distractions, such as a transparent display or reduced contrast between icons and their background, can reduce the effectiveness of evoking brain activity at the desired frequencies. Thus, visual environmental factors negatively impact the reliability and accuracy of SSVEP detection.
The invention solves this problem by calibrating and dynamically adjusting the presentation of the user interface based on real-time measurements of the user's brain activity and changes in the background environment. For example, the system monitors ambient light and location to detect environmental changes and recalibrates display parameters accordingly. This results in enhanced brain signal strength at targeted frequencies, alleviating the challenges posed by visual distractions and improving detection performance in various environments.
Claims Coverage
The patent contains three independent claims covering a method, a system, and a non-transitory computer-readable medium, each directed to optimizing SSVEP detection by measuring brain activity and adjusting display parameters.
Measuring brain activity for target and second harmonic frequencies
The invention measures brain activity specifically at a target frequency and its second harmonic based on default display parameters for a plurality of icons presented to the user.
Determining signal strength below threshold
It determines whether the measured strength of the target frequency and the second harmonic frequency are below a predefined threshold level.
Modifying display parameters to reach threshold
In response to the measured strengths being below threshold, the system modifies one or more display parameters—such as frequency, duty cycle, color, arrangement, position, and background—until the target and second harmonic frequency strengths meet or exceed the threshold.
Measuring brain activity for third harmonic frequency and threshold comparison
Optionally, the invention measures brain activity at the third harmonic frequency and sets the threshold level greater than the third harmonic frequency to ensure the target and second harmonic frequencies dominate.
Adjusting display parameters based on environmental changes
The invention establishes a baseline level of environment activity (based on ambient light level, location, or both), detects changes beyond a predetermined amount, and modifies display parameters accordingly to maintain optimal detection.
Updating default display parameters based on modifications
After modifications, the default values of display parameters may be updated to the newly modified parameters, allowing progressive calibration.
Overall, the claims cover a comprehensive approach to optimizing SSVEP detection by measuring specific brain activity frequencies, dynamically adjusting icon display parameters based on signal strength and environmental context, and incorporating this adaptive calibration into various system implementations.
Stated Advantages
Enhancement of SSVEP detection performance by maximizing brain activity signal strength at the target frequency and its second harmonic.
Overcoming visual distractions and environmental interferences such as transparency and background contrast through dynamic adjustment of display parameters.
Capability to adapt to changing ambient light and location environments by recalibrating interface presentation for consistent brain activity detection.
Reduction of detection time and increase in accuracy by leveraging the second harmonic frequency alongside the target frequency.
Documented Applications
SSVEP-based brain-computer interfaces utilizing electronic displays with flickering icons to allow user interaction through visual stimuli.
Head-up displays (HUDs) in vehicles where the user interface is shown in a transparent or semi-transparent manner, affecting evoked brain signals.
Automotive systems, including vehicle HUDs, being a primary reference environment for the disclosed concepts.
Other electronic displays having user interfaces, including personal computers and potentially any interface exposed to varying environmental lighting and complex backgrounds.
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