Wearable Brain Activity Analysis With Wavelet-Based Mental-State Feedback
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Solution Overview
Problem
Existing brain activity monitoring technologies, such as EEG and fMRI, suffer from limitations in spatial resolution and portability, making them unsuitable for continuous, non-clinical use.
Innovation Solution
A wearable apparatus that records brain electrical activity, physiological parameters, and environmental data, using wavelet packet atoms and machine learning to determine personalized mental states and generate real-time feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If EEG is used to monitor brain activity, then the monitoring is noninvasive and continuous, but the spatial resolution is limited to small regions close to each electrode
Solution Approach 1:
The patent segments the brain monitoring function into multiple specialized components: scalp EEG electrodes for noninvasive continuous monitoring, invasive intracranial electrodes for high-resolution local measurement, and fMRI for comprehensive functional mapping. Each segment serves a specific resolution need, allowing the system to achieve both continuous monitoring and high spatial resolution through coordinated use of multiple segmented components.
2Measurement precision
If fMRI is used to monitor brain activity, then comprehensive brain function can be mapped, but the device is large, expensive, and cannot be used outside the clinic or continuously
Solution Approach 1:
The patent creates a multi-level copying system where fMRI provides a comprehensive functional map that serves as a reference template. This template is then copied and integrated with EEG data at multiple scales: first with intracranial electrode recordings for detailed local patterns, then with scalp EEG for continuous monitoring. The copying approach allows comprehensive brain mapping capabilities to be distributed across portable, continuous monitoring devices without requiring the actual large fMRI machine to be present.
Solution Approach 2:
The patent implements a nested architecture where multiple monitoring modalities are integrated at different levels of detail. The outermost layer is continuous scalp EEG for ongoing monitoring, nested within which are invasive intracranial electrodes for high-resolution local measurement, and nested within those are fMRI-derived functional templates for comprehensive brain mapping. This nested structure allows the system to achieve comprehensive brain function mapping capability while using portable, continuous monitoring devices.
3Measurement precision
If invasive electrodes are used, then high spatial resolution can be achieved, but the monitoring becomes invasive and more complex
Solution Approach 1:
The patent implements a dynamic, adaptive system that automatically adjusts the level of invasiveness based on the monitoring needs. The system begins with noninvasive scalp EEG monitoring and only activates invasive intracranial electrodes when higher resolution is specifically required for particular brain regions or clinical conditions. This dynamic approach allows the system to maintain high spatial resolution capability while minimizing invasiveness for the majority of monitoring scenarios.
Solution Approach 2:
The patent introduces fMRI-derived functional templates as an intermediary layer between noninvasive scalp EEG and invasive intracranial electrodes. This intermediary provides a comprehensive functional map that guides the interpretation of both scalp and intracranial recordings, reducing the need for invasive electrodes by enabling accurate brain function mapping through the less invasive scalp EEG when combined with the fMRI template reference.
Data Source
AI summary
In some embodiments, the present invention provides an exemplary inventive system that includes: an apparatus to record: individual's brain electrical activity, a physiological parameter of the individual, and iii) an environmental parameter; a computer processor configured to perform: obtaining a recording of the electrical signal data; projecting the obtained recording of electrical signal data onto a pre-determined ordering of a denoised optimal set wavelet packet atoms to obtain a set of projections; normalizing the particular set of projections of the individual using a pre-determined set of normalization factors to form a set of normalized projections; determining a personalized mental state of the individual by assigning a brain state; determining a relationship between: the physiological parameter, the environmental parameter, and the personalized mental state; generating an output, including: a visual indication, representative of the personalized mental state, and) a feedback output configured to affect the personalized mental state of the individual.