BCI Text Prediction via Neuroimaging Signal Reconstruction

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Solution Overview

Problem

Conventional communication methods in online social networks, such as voice-to-text options, are often inaccurate and raise privacy concerns, making it difficult for individuals with disabilities or those who find typing cumbersome to engage effectively, particularly in public settings.

Innovation Solution

A brain-computer interface (BCI) system that analyzes neuroimaging signals to predict text, enabling unspoken communications by employing multiple predictive models to interpret input and output signals from the brain, without requiring explicit understanding of underlying neurobiological activity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If voice-to-text options are used for communication, then communication speed is improved, but accuracy deteriorates and privacy concerns arise

Engineering Contradiction:

Improvecommunication speedVSAvoidtext prediction accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent replaces conventional voice-to-text mechanical systems with a neuroimaging-based brain computer interface system. Instead of using acoustic sensors and speech recognition algorithms, the system uses optical sensors to detect neurobiological activity patterns in the brain, fundamentally substituting the input mechanism from acoustic to optical domain while maintaining communication functionality

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces an intermediary layer of neural signal processing between the user's intent and the text output. Multiple trained predictive models act as intermediaries that translate complex neurobiological activity patterns into predicted text, providing a sophisticated mediation layer that improves accuracy over direct voice-to-text conversion

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If physical typing is required for communication, then text input accuracy is improved, but ease of operation deteriorates

Engineering Contradiction:

Improvetext input accuracyVSAvoidcommunication convenience

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system enables self-service communication by directly reading the user's intended text from their brain activity without requiring manual typing or voice articulation. The brain computer interface system autonomously captures neurobiological signals, processes them through predictive models, and generates text output, allowing users with disabilities to communicate independently

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical typing process with a neuroimaging-based detection system. Instead of requiring physical interaction with keyboards or text fields, the system uses optical sensors to detect brain activity patterns and automatically generates text, substituting mechanical input with optical neural detection

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If voice-to-text is used in public settings, then communication efficiency is improved, but privacy protection deteriorates

Engineering Contradiction:

Improvecommunication efficiencyVSAvoidprivacy exposure

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent introduces a private intermediary channel for communication by reading directly from the user's brain activity. This neural intermediary layer bypasses public voice articulation, allowing the user to communicate their intended text privately without vocalizing it in public spaces, thus protecting privacy while maintaining communication efficiency

Inventive Principle:

Principle #24Intermediary (Mediator)

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

Enables efficient and private communication for individuals who cannot type, providing accurate text prediction for online interactions without the need for physical input, thus improving accessibility and user experience.

Implementation Method 1

the BCI system can employ optical sources and optical detectors that are positioned in contact with the individual's head for performing optical tomography

Methodology Applied

Scientific EffectOptical tomography: Tomography

Data Source

PatentUS11468351B1Predicting text by reconstructing neuroimaging signals

Publication Date: 2022.10.11 META PLATFORMS INC

AI summary

A brain computer interface (BCI) system predicts text based on input and output signals obtained in relation to an individual that are informative for determining an individual's neurobiological activity. The BCI system applies a first predictive model to the input signal and a second predictive model to the output signal. The first predictive model predicts the forward propagation of the input signal through the individual's head whereas the second predictive model predicts the backward propagation of the output signal through the individual's head. Each of the first predictive model and second predictive model predicts characteristics of their respective signal at a common plane such as the cortical surface of the individual's brain. The BCI system predicts text by applying a third predictive model to the predicted signal characteristics at the common plane outputted by the first predictive model and the second predictive model.