Non-Invasive Optical Brain-Computer Interface for High-Resolution Signal Decoding
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Solution Overview
Problem
Conventional brain-computer interfaces face challenges with low resolution and limited application due to invasive methods or poor signal quality in non-invasive approaches, restricting their use to binary data and requiring lengthy training times for machine learning algorithms.
Innovation Solution
A non-invasive brain-computer interface platform utilizing optical-based signal acquisition and processing, including optodes and wearable devices, to decode neural activities for enhanced data collection and processing, enabling high-resolution activity tracking and nuanced interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive brain-computer interface methods are used, then measurement precision and data quality improve, but device complexity and ease of operation deteriorate due to surgical requirements and support needs
Solution Approach 1:
The patent replaces invasive mechanical/electrical electrode implantation with non-invasive optical detection methods. Optical sensors and cameras detect brain activity through skull transmission and surface blood flow changes, eliminating the need for surgical implantation while maintaining measurement capability through photodetection and optical signal processing
Solution Approach 2:
The patent changes the detection parameter from direct electrical neural signals (requiring invasive electrodes) to optical parameters such as light absorption, scattering, and blood flow dynamics. This parameter shift enables non-invasive measurement by detecting hemodynamic responses and optical property changes in brain tissue through the skull
2Ease of operation
If conventional non-invasive EEG devices are used, then ease of operation improves, but measurement precision deteriorates due to poor signal-to-noise ratio and low resolution
Solution Approach 1:
The patent introduces optical sensors and cameras as intermediary devices that detect brain activity indirectly through optical properties of brain tissue and skull. These intermediaries convert biological optical signals into detectable electronic signals, enabling non-invasive high-resolution measurement without direct electrical contact with neural tissue
Solution Approach 2:
The patent substitutes conventional electrical EEG electrodes with optical detection systems. Instead of measuring electrical potentials through scalp contact, the system uses optical sensors to detect light absorption and scattering changes caused by brain activity, achieving higher signal-to-noise ratio through optical contrast
3Device complexity
If binary data classification is used in brain-computer interfaces, then device complexity is reduced, but adaptability deteriorates due to limited application scope
Solution Approach 1:
The patent transitions from one-dimensional binary classification to multi-dimensional continuous signal analysis. By extracting multiple features from optical brain signals (amplitude, frequency, temporal patterns, spatial distribution) and applying advanced algorithms, the system achieves nuanced interpretation of brain states beyond simple binary decisions
Solution Approach 2:
The patent implements dynamic, adaptive classification that adjusts to individual users and evolving brain states. The system continuously learns from optical signal patterns, adapting classification thresholds and parameters to capture subtle variations in brain activity for diverse applications such as gaze tracking, cognitive state monitoring, and intent recognition
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 solution provides high-resolution, portable, and accurate brain signal decoding, enabling natural and nuanced user interactions beyond binary data, with reduced training times and expanded application possibilities.
Implementation Method 1
optical-based signal acquisition and processing, including optodes and wearable devices, to decode neural activities
Data Source
AI summary
Systems and methods associated with brain computer interfaces (BCIs) are disclosed. Embodiments herein include features related to one or more of optical-based brain signal acquisition and/or processing, decoding/encoding modalities, brain-computer interfacing, AR/VR content interaction, and/or electronic wave (E-wave) detection, determination and/or processing, among other features. Certain example implementations may include or involve aspects or processes such as monitoring the gaze and brain activity of a user (e.g., via a BCI, etc.) interacting with a user interface (UI), detecting that the gaze of the user is directed at an element of the UI, detecting or processing an E-wave in temporal conjunction with the gaze at the element, determining that the users intends to interact with the element, and/or triggering an interaction with the element. Further, aspects of present systems and methods may be configured to leverage BCIs and/or non-invasive wearable device features to provide enhanced user interactions for various devices.