Retinal Signal Processing for Medical Condition Detection

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Solution Overview

Problem

Current methods for determining medical conditions, such as psychiatric and neurological conditions, using electroretinograms (ERG) are limited by the volume and density of information collected, making it difficult to differentiate between conditions accurately.

Innovation Solution

The development of a refined methodology for processing retinal signal data with higher density and volume, known as retinal signal processing and analysis (RSPA), which includes collecting and analyzing retinal signal data at higher sampling frequencies and for extended periods, capturing additional features like impedance and light parameters, and using mathematical modeling to identify biomarkers and biosignatures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If conventional electroretinogram (ERG) methods are used to collect retinal signal data, then the measurement process is simple and quick, but the volume and density of information collected are limited, making it difficult to differentiate between medical conditions

Engineering Contradiction:

Improvevolume and density of retinal signal informationVSAvoidcomplexity of data collection and processing system

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent transforms conventional ERG from a single-dimensional voltage-time recording to a multi-dimensional dataset by incorporating multiple parameters simultaneously: voltage, circuit impedance, optical parameters (light wavelength, spectrum, intensity), and temporal extensions. This dimensional expansion enables comprehensive characterization of retinal function while maintaining clinical feasibility through integrated measurement protocols

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Measurement precision

If retinal signal data is collected at higher sampling frequencies and for longer periods with additional parameters, then the information density and volume increase, but the data processing complexity and computational requirements increase

Engineering Contradiction:

Improveprecision of medical condition detectionVSAvoidcomplexity of mathematical modeling and analysis

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the complex retinal signal analysis into distinct functional components: voltage waveform analysis, impedance spectroscopy, optical parameter correlation, and temporal pattern recognition. Each segment can be processed independently using specialized algorithms, then integrated to form a comprehensive diagnostic assessment, reducing overall computational complexity while maintaining high measurement precision

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent employs parameter transformation techniques to convert raw high-dimensional retinal signal data into standardized biomarkers and biosignatures. By changing the parameter representation from raw time-series data to frequency-domain features, impedance spectra, and normalized amplitude ratios, the system achieves precise condition detection with reduced computational burden

Inventive Principle:

Principle #35Parameter changes

3Reliability

If multiple parameters of retinal signal data are analyzed simultaneously, then the ability to identify biomarkers and biosignatures improves, but the difficulty of detecting and measuring increases

Engineering Contradiction:

Improvereliability of medical condition differentiationVSAvoiddifficulty of processing multimodal retinal data

Core Design Contradiction:

ReliabilityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent develops a universal retinal signal processing framework that simultaneously handles multiple data types (voltage, impedance, optical parameters) through a single integrated analysis system. This multi-functional approach uses common reference standards and unified normalization procedures across all parameter types, enabling reliable biomarker identification while simplifying the measurement process through standardized protocols

Inventive Principle:

Principle #6Universality (Multi-functionality)

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

This approach enables more accurate detection and discrimination between medical conditions, improving the identification of biosignatures and enabling earlier and more effective interventions.

Implementation Method 1

systems and methods for processing retinal signal data generated by light stimulation

Methodology Applied

Scientific EffectPhotoelectric Effect: Photoelectric Effect

Data Source

PatentUS20240389950A1Systems and methods for processing retinal signal data and identifying conditions

Publication Date: 2024.11.28 DIAMENTIS INC

AI summary

There is disclosed a method and system for predicting a likelihood that a patient is subject to one or more conditions. Retinal signal data corresponding to the patient may be received. Retinal signal features may be extracted from the retinal signal data. The retinal signal features may be applied to a mathematical model. The mathematical model may correspond to a condition. A predicted probability for the condition may be output by the mathematical model. The predicted probability may be displayed on an interface.