Prefrontal Cortex Neurological Signal Interface Control
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Solution Overview
Problem
Existing brain-computer interfaces rely on external stimuli, which require extensive setup, training, and are prone to noise and variability due to factors like mental state, fatigue, and distraction, limiting their reliability and practicality for controlling computer user interfaces.
Innovation Solution
A novel method utilizing neurological signals from the prefrontal cortex, independent of external stimuli, where the power and duration of these signals are analyzed against predefined thresholds to trigger or activate computer user interfaces, enabling reliable and fast interaction without the need for traditional paradigms like motor imagery, event-related potentials, or visual evoked potentials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional brain-computer interfaces use external stimuli (motor imagery, event related potentials, visual evoked potentials), then the interface can be triggered, but extensive setup and training time is required and the system is prone to noise from mental state, fatigue, and distraction
Solution Approach 1:
The patent extracts the triggering mechanism from external stimuli and internal mental imagery, instead using directly observable neurological signals from the prefrontal cortex. This removes the need for extensive training and setup while maintaining reliable signal detection, as the system directly measures neurological activity rather than inferring it from behavioral responses to stimuli.
Solution Approach 2:
The patent introduces an intermediary mechanism - using the prefrontal cortex's neurological signals as a mediator between user intent and interface control. This intermediary provides a more direct and reliable control pathway compared to traditional methods that rely on motor imagery or stimulus-response patterns, reducing both training time and signal noise.
2Adaptability or versatility
If event related potentials are used with P300 signal, then the interface can respond to oddball stimuli, but the signal is affected by noise from mental state, learning, fatigue, motivation, repetition blindness, distraction, habituation, eye blinks and other nonstationarities
Solution Approach 1:
The patent extracts the control mechanism from stimulus-response patterns that are vulnerable to physiological noise, and instead uses direct neurological signals from the prefrontal cortex. This extraction removes the system's vulnerability to mental state, fatigue, and distraction while maintaining adaptability to user intent.
Solution Approach 2:
The system uses the prefrontal cortex's inherent neurological signaling capabilities to directly control the interface, making the system self-service in terms of signal generation. This eliminates the need for external stimuli and reduces dependency on stable physiological states, as the prefrontal cortex naturally generates the necessary signals for control.
3Measurement precision
If visual evoked potentials are used with visual flickers, then the occipital cortex response can be measured, but multiple repeated training sessions are required and mental and visual fatigue occurs with decreased arousal level
Solution Approach 1:
The patent extracts the measurement target from visual response patterns in the occipital cortex and instead measures neurological signals directly from the prefrontal cortex. This extraction eliminates the need for repeated visual stimulation and training sessions, providing precise measurement of user intent without inducing mental or visual fatigue.
Data Source
AI summary
A method of and system for human interactions with a computer user interface using neurological signals from the frontal part of the human brain, also known as the prefrontal cortex. In one embodiment, the system comprised a brain-computer interface system and a method of filtering, processing and analyzing neurological signals over a specific period of time to trigger, activate or control on-demand a computer user interface without the need of any preliminary brain state recording nor traditionally-required external stimulus.