Non-Invasive Brain-Computer Interface for Silent Communication
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Solution Overview
Problem
Individuals with progressive neurodegenerative diseases like ALS, particularly those in a 'locked-in' state, face challenges in communication due to the inability to control voice interfaces, and existing methods for decoding brain signals are invasive and unreliable.
Innovation Solution
The development of non-invasive systems that convert brain signals associated with spatiotemporal movements into text or speech, using passive haptic learning to teach coded language systems, such as Braille, through wearable devices providing tactile stimulation, enabling communication and teaching chorded systems without active attention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If invasive implanted electrodes or electrode arrays are used to decode speech from brain signals, then communication reliability is improved, but safety and device complexity worsen
Solution Approach 1:
The patent replaces invasive mechanical electrode implantation with non-invasive functional magnetic resonance imaging (fMRI) to detect brain activity. This substitution eliminates the harmful effects of implanted electrodes while maintaining the ability to decode brain signals for communication, directly resolving the contradiction between reliability and safety.
2Ease of operation
If traditional speech-generating devices are used, then communication is enabled, but communication speed is too slow (below 3 words per minute)
Solution Approach 1:
The patent implements a training phase where users learn to associate specific body movements with letters or words before actual communication. This preliminary action of learning movement patterns enables faster communication during the actual decoding phase, as the brain activity patterns are already established and recognizable, significantly improving communication speed beyond traditional SGD limits.
Solution Approach 2:
The system enables continuous communication by detecting brain activity patterns in real-time during movement execution, rather than requiring discrete, slow selections. The fMRI scanner continuously monitors brain activity, allowing for faster communication rates compared to traditional step-by-step SGD interfaces.
3Ease of operation
If voice interfaces are used by SGD users, then communication is possible, but user comfort deteriorates in public spaces
Solution Approach 1:
The patent replaces voice-based interfaces with a movement-based brain-computer interface. Users perform physical movements (such as finger tapping or body gestures) that are detected through brain activity patterns via fMRI, eliminating the need for voice output. This substitution removes the social discomfort of using voice interfaces in public while maintaining full communication capability.
4Adaptability or versatility
If motor function diminishes to complete lock-in state, then communication ability is lost, but need for communication remains
Solution Approach 1:
The patent inverts the traditional approach by not requiring direct motor control of communication devices. Instead of controlling a device with movements, the system detects brain activity patterns associated with intended movements and decodes communication from those patterns. This inversion allows individuals in complete lock-in state to communicate using their thoughts and imagined movements, even when physical motor control is completely lost.
Data Source
AI summary
An exemplary embodiment of the present disclosure provides a method of communication, the method comprising receiving a signal from a subject, wherein the signal represents activity in a brain of the subject associated with one or more spatiotemporal movements of one or more portions of the subject's body, correlating the signal to a portion of a coded language system and outputting the portion of the coded language system.