Multi-bio-signal Geriatric Cognitive Impairment Diagnosis

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Solution Overview

Problem

Existing geriatric cognitive impairment diagnosis technologies are limited by their high cost, invasiveness, and inability to comprehensively assess the nervous system, relying on single bio-signals such as brain waves, heart rate variability, or gait analysis.

Innovation Solution

A multi-bio-signal-based diagnosis method and device that simultaneously evaluates brain waves, heart rate variability, and gait measurement values using a cognitive impairment diagnosis model constructed with a logistic function to determine the probability of geriatric cognitive impairment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If imaging diagnostic equipment is used for geriatric cognitive impairment diagnosis, then diagnostic accuracy is improved, but cost and invasiveness increase

Engineering Contradiction:
Improvediagnostic accuracyVSAvoidcost and invasiveness
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent uses bio-signal copies (EEG, ECG, EMG signals) as substitutes for direct imaging diagnostic procedures. Instead of using expensive and invasive imaging equipment, the system collects electrical signal copies from the body that reflect nervous system function, thereby achieving diagnostic purposes with lower cost and invasiveness while maintaining diagnostic accuracy through multi-signal integration analysis

Inventive Principle:
Principle #26Copying

2Device complexity

If single bio-signal analysis is used for diagnosis, then device complexity is reduced, but measurement precision deteriorates

Engineering Contradiction:
Improvediagnosis system complexityVSAvoiddiagnosis accuracy
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

The patent merges multiple bio-signal sources (central nervous system EEG signals, autonomic nervous system ECG signals, and motor function EMG signals) into a unified diagnostic system. By combining these different signal types and analyzing them together through integrated algorithms, the system achieves comprehensive nervous system assessment and improved diagnostic accuracy that surpasses single-signal analysis

Inventive Principle:
Principle #5Merging (Combining)

3Device complexity

If questionnaire-based psychological tests are used, then cost is reduced, but measurement precision deteriorates due to limited scope

Engineering Contradiction:
Improvediagnosis costVSAvoidassessment comprehensiveness
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

The patent replaces the mechanical/questionnaire-based psychological testing system with a physiological signal-based diagnostic system. Instead of relying on subjective patient responses to questions, the system objectively measures and analyzes electrical bio-signals from the nervous system, thereby eliminating the limitations of questionnaire methods while maintaining cost-effectiveness through the use of standard medical equipment

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250064379A1Multi-bio-signal-based geriatric cognitive impairment diagnosis method and device
Publication Date: 2025.02.27 SEOUL NATIONAL UNIVERSITY R&DB FOUNDATION
  • US20250064379A1 patent drawing
  • US20250064379A1 patent drawing
  • US20250064379A1 patent drawing

AI summary

A multi-bio-signal-based geriatric cognitive impairment diagnosis method includes collecting multiple bio-signals including brain waves, heart rate variability, and gait measurement values of a subject during walking; calculating a probability value of a geriatric cognitive impairment disease by using a cognitive impairment diagnosis model, based on the multiple bio-signals; and determining whether there is a geriatric cognitive impairment disease, based on a calculated probability value, wherein the cognitive impairment diagnosis model is a model constructed by applying brain waves, heart rate variability, and gait measurement values of a patient with a geriatric cognitive impairment disease to a logistic function.