Motor Cortical Training Device Using EEG and Visual Stimuli
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Solution Overview
Problem
Current methods for training motor cortical areas of the brain, such as those affected by stroke, are limited in effectiveness and accessibility, particularly for patients who are paralyzed or immobilized, and often require specialized equipment or medical intervention.
Innovation Solution
A device that uses a combination of visual and auditory stimuli, along with sensors to measure cognitive, kinematic, and EEG responses, to estimate motor adaptation and improve training of motor cortical areas. The device employs a processing unit to analyze responses and adjust the training program dynamically, utilizing a trained neural network to personalize the training based on individual responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional physical rehabilitation is used, then motor function recovery is improved, but it requires presence of medical staff and is not possible when patient is paralyzed or immobilized
Solution Approach 1:
The patent replaces physical mechanical rehabilitation with a computational system that uses visual stimuli and neural network processing to train motor cortical areas. The system substitutes hands-on physical therapy with a digital interface that displays visual patterns and measures neural responses through EEG, enabling rehabilitation without requiring physical contact or movement assistance.
Solution Approach 2:
The patent introduces a computer-based intermediary system that mediates between the patient's motor cortical areas and the rehabilitation process. The system uses visual stimuli as an intermediary to activate and train neural pathways, and employs EEG technology as an intermediary to measure and analyze neural responses without requiring physical interaction.
2Reliability
If exoskeletons and robotic devices are used, then motor function training is improved, but they are expensive and require specialized technical environment
Solution Approach 1:
The patent extracts the essential function of motor training from complex physical devices and isolates it to a computational processing function. Instead of using entire exoskeleton systems, the invention extracts and utilizes only the neural stimulation and measurement aspects through visual stimuli and EEG, eliminating the need for complex mechanical components and specialized environments.
Solution Approach 2:
The patent replaces expensive, complex robotic devices with a simpler, more accessible computational system. The invention uses standard computer hardware, display devices, and EEG sensors that are more widely available and less costly than specialized exoskeletons, making motor cortical training accessible in ordinary clinical settings.
3Productivity
If virtual reality training is used, then patient engagement is improved, but training is performed in artificial sensory context that limits transfer to everyday gestures
Solution Approach 1:
The patent creates a training system with universal applicability by using visual stimuli that can represent various real-world gestures and movements. The system is designed to train motor cortical areas for multiple different gestures through standardized visual patterns, making the training transferable to various everyday activities rather than being limited to a single artificial virtual environment.
4Reliability
If repetitive movement training is used, then motor coordination is improved, but it takes many years of practice and perseverance
Solution Approach 1:
The patent applies preliminary action by directly stimulating motor cortical areas through visual stimuli before actual physical movement is required. The system pre-activates and trains neural pathways associated with specific gestures through visual patterns, so that when physical movement is eventually performed, the neural pathways are already strengthened and coordinated, significantly reducing the time needed for motor skill acquisition.
Solution Approach 2:
The patent replaces years of repetitive physical practice with a computational approach that directly targets and trains motor cortical areas through visual stimulation and neural response measurement. This substitution accelerates the training process by working directly with the neural substrate of motor control rather than relying on slow, iterative physical repetition.
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
The device enhances the efficiency and effectiveness of motor cortical training by creating a realistic sensory environment that promotes transfer of learning to everyday activities, improving motor adaptation and adaptation over time, and allowing for personalized and adaptive training programs.
Implementation Method 1
measuring with a second sensor using electroencephalogram techniques, desynchronization of alpha waves of the brain, of low beta and Mu rhythm
Data Source
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AI summary
The invention notably relates to a device for training motor cortical areas of a brain of a human subject. The device comprises a display for providing the human subject with a set of visual stimuli, a speaker for providing the human subject with auditory stimuli, sensors for collecting responses of the human subject to the stimuli. A first sensor data collects a cognitive response of the human subject, a second sensor measures desynchronization of alpha waves of the brain, of low beta and Mu rhythm by using electroencephalogram techniques, a third sensor measures kinematics of at least one part of the body of the subject. From the collected responses, estimating by a processing unit a motor adaptation of the subject in response to one or more of the provided stimuli.