Brain State Representation for Cross-Device Biomarker Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing biosignal data analysis methods struggle with dimensionality, noise, and device variability, leading to inefficiencies in processing and accuracy when determining neurological biomarkers.
Innovation Solution
A system and method that transforms biosignal data into a standardized brain state representation, segmenting it into beneficial and non-beneficial segments, and using a unified model to predict biomarkers across diverse devices and users, enabling efficient and accurate biomarker determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If biosignal data is processed using existing analysis methods, then biomarker determination can be performed, but computational load is high and processing efficiency is low due to dimensionality and noise
Solution Approach 1:
The patent segments the brain state representation into multiple segments, where each segment corresponds to a specific biomarker or aspect of brain function. This segmentation allows parallel processing of different biomarkers, reducing overall computational load while maintaining comprehensive analysis.
Solution Approach 2:
The patent extracts only the beneficial segments from the brain state representation that are relevant to specific biomarkers, discarding non-beneficial segments. This extraction process reduces the dimensionality of the data that needs to be processed, thereby decreasing computational load and improving processing efficiency.
2Adaptability or versatility
If biosignal data from diverse devices is analyzed, then versatility is improved, but measurement precision deteriorates due to device variability
Solution Approach 1:
The patent creates a universal brain state representation that can be generated from biosignal data collected by diverse devices with different configurations. This universal representation serves as a common intermediary format that maintains the essential brain state information while being device-agnostic, thereby enabling versatile device compatibility without sacrificing measurement precision.
Solution Approach 2:
The brain state representation acts as an intermediary between the raw biosignal data from diverse devices and the final biomarker determination. This intermediary transformation standardizes the data from different device configurations into a unified format, eliminating device variability effects while preserving the underlying brain state information needed for accurate biomarker measurement.
3Measurement precision
If full brain state representation is processed, then measurement precision is maintained, but loss of time increases due to processing complexity
Solution Approach 1:
The patent extracts only the beneficial segments from the brain state representation that are relevant to specific biomarkers, discarding non-beneficial segments. This extraction process reduces the dimensionality of the data that needs to be processed, thereby decreasing processing time while maintaining the precision needed for accurate biomarker determination.
Solution Approach 2:
The patent applies partial processing by focusing only on the necessary segments of the brain state representation that contribute to biomarker determination. Rather than processing the entire brain state representation in full detail, the system selectively processes only the relevant portions, reducing processing time while maintaining sufficient measurement precision for the intended applications.
Data Source
AI summary
A method for biosignal data transformation can include: determining a set of biosignal data, determining a brain state representation (e.g., an embedding) based on the biosignal data, and determining a biomarker value based on the brain state representation. The method can optionally include training a model (e.g., training a model used to determine the brain state representation), and/or any other suitable steps. A system for biosignal data transformation can include a biosignal device and a computing system.