Tongue Localization System Using EEG and EMG Sensors
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Solution Overview
Problem
Current technologies lack effective methods for human-to-computer interaction, particularly for individuals with disabilities, to fully participate in a computer-based society, as existing interfaces do not adequately utilize tongue movements for communication.
Innovation Solution
A system comprising EEG, EMG, and SKD sensors to detect and analyze brain signals, muscle activity, and skin surface deformations associated with tongue movements, correlating these signals with tongue location areas to enable tongue-on-teeth typing, allowing users to interact with computers by tapping on specific areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional voice-based or keyboard interfaces are used, then communication is possible, but individuals with paralysis or severe disabilities cannot effectively interact with computer systems
Solution Approach 1:
The patent replaces traditional mechanical input devices (keyboards, mice, voice recognition systems) with a tongue-based interface that detects electrical signals from tongue muscles. This substitution enables individuals with paralysis to communicate without relying on limb movement or vocal cord function, directly addressing the accessibility barrier for disabled users
2Measurement precision
If multiple sensors (EEG, EMG, SKD) are integrated to detect tongue movements, then detection accuracy reaches up to 96%, but device complexity increases
Solution Approach 1:
The patent combines three different sensor types (EEG for brain electrical activity, EMG for muscle electrical activity, and SKD for skin deformation) into a single integrated tongue interface system. This merging of multiple sensing modalities allows the system to cross-validate signals and achieve high detection accuracy (up to 96%) while managing the complexity through unified signal processing algorithms
Solution Approach 2:
The patent introduces a sophisticated signal processing system that acts as an intermediary between the raw sensor data and the final tongue location determination. This intermediary layer filters, integrates, and interprets signals from multiple sensors, resolving the complexity of handling multiple sensor types while maintaining high measurement precision
3Adaptability or versatility
If tongue-on-teeth typing is implemented to enable communication, then individuals with disabilities can type and send commands, but the system requires precise correlation of tongue movements with specific teeth areas
Solution Approach 1:
The patent maps three-dimensional tongue movements onto a two-dimensional surface of the teeth/gingiva. By detecting tongue position in 3D space and correlating it with 2D tooth locations, the system enables precise typing on teeth surfaces. This dimensional transformation simplifies the detection task while maintaining the ability to distinguish between different key locations for communication
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 system achieves high accuracy in detecting tongue movements and locations, enabling users to type or send commands by tapping on teeth areas, providing a reliable means of communication for individuals with paralysis or disabilities, with accuracy rates of up to 96% in detecting specific tongue pressing areas and 97% in detecting typing events.
Implementation Method 1
detect an electroencephalography ('EEG') signal from an EEG sensor. The EEG sensor is configured to sense the EEG signal generated by a brain in association with a tongue movement
Implementation Method 2
detect the EMG signal from the EMG sensor. The EMG sensor is configured to sense the EMG signal generated by cranial nerve stimulation of muscles associated with the tongue movement
Implementation Method 3
The SKD sensor is configured to sense the skin surface deformation caused by the tongue movement
Data Source
AI summary
A computer-implemented method for identifying tongue movement comprises detecting an electroencephalography (“EEG”) signal from an EEG sensor. The EEG sensor is configured to sense the EEG signal generated by a brain in association with a tongue movement. The method also comprises detecting the EMG signal from the EMG sensor. The EMG sensor is configured to sense the EMG signal generated by cranial nerve stimulation of muscles associated with the tongue movement. The method also includes identifying the tongue movement based on the EEG signal and the EMG signal. The method then includes correlating the tongue movement with one of a plurality of tongue location areas.