Cognitive Function Evaluation via Speech Formant Analysis
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Solution Overview
Problem
Current cognitive function evaluation methods, such as the Hasegawa's Dementia Scale-Revised and Mini-Mental State Examination, are burdensome and prone to memorization issues when repeatedly administered, necessitating a more efficient and accurate assessment technique.
Innovation Solution
A cognitive function evaluation device and system that utilizes speech data analysis by extracting vowels from speech utterances to calculate feature values based on formant frequencies and amplitudes, enabling accurate cognitive function evaluation without requiring extensive test times or memorization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional paper-based cognitive function evaluation tests are used, then evaluation can be conducted with simple equipment, but the test time becomes long and the subject bears a heavy burden
Solution Approach 1:
The patent replaces the mechanical paper-based test administration system with an automated speech analysis system. Speech recognition technology and formant analysis algorithms automatically evaluate cognitive function by analyzing vowel sounds, eliminating the need for lengthy paper tests while maintaining evaluation accuracy.
Solution Approach 2:
The patent changes the evaluation parameter from written test responses to acoustic parameters of speech (formant frequencies F1, F2, F3). By analyzing the spectral characteristics of vowels in spontaneous speech, the system achieves rapid cognitive assessment without requiring the subject to complete time-consuming test items.
2Reliability
If the same paper-based test is repeatedly administered to evaluate cognitive changes, then longitudinal tracking is possible, but the subject may memorize answers reducing evaluation accuracy
Solution Approach 1:
The patent uses dynamic speech parameters (formant frequencies and their temporal variations) that naturally vary with cognitive state rather than static test responses. This allows repeated assessments using the same speech-based protocol without memorization effects, as each speech sample provides unique acoustic information about current cognitive function.
3Measurement precision
If detailed speech analysis with formant extraction is performed, then cognitive function evaluation accuracy improves, but the calculation complexity increases
Solution Approach 1:
The patent extracts only the essential acoustic features (formant frequencies F1, F2, F3) from speech signals that are most relevant to cognitive function evaluation. By focusing on these specific spectral parameters rather than analyzing the entire speech signal, the system achieves high evaluation precision while keeping the computational requirements manageable.
Solution Approach 2:
The patent transforms complex speech signals into simplified formant parameter representations. This parameter transformation reduces the dimensionality of the data while preserving the critical information needed for cognitive assessment, enabling accurate evaluation without requiring extremely complex computational systems.
4Measurement precision
If traditional cognitive tests are used, then professional training is required for administration, but this increases operational complexity and cost
Solution Approach 1:
The patent creates a self-administered speech evaluation system that automatically collects and analyzes speech samples without requiring trained professionals. The system autonomously performs formant extraction and cognitive function assessment from recorded speech, making the evaluation process accessible to non-experts while maintaining scientific rigor.
Data Source
AI summary
A cognitive function evaluation device includes: an obtainment unit configured to obtain speech data indicating speech uttered by a subject; a calculation unit configured to extract a plurality of vowels from the speech data obtained by the obtainment unit, and calculate, for each of the plurality of vowels, a feature value based on a frequency and an amplitude of at least one formant obtained from a spectrum of the vowel; an evaluation unit configured to evaluate a cognitive function of the subject from the feature value calculated by the calculation unit; and an output unit configured to output an evaluation result of the evaluation unit.