Mental Disease Estimation via Acoustic Parameter Segmentation
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Solution Overview
Problem
Current techniques for estimating mental/neurological diseases from speech data have limited precision and are restricted to estimating emotional states such as anger, joy, tension, sadness, or depressive symptoms, with low accuracy.
Innovation Solution
A medical apparatus that calculates acoustic parameters from voice data, uses a computational processing device to determine a score based on feature quantities associated with specific diseases, and detects diseases by setting a reference range, enabling high-precision estimation of mental/neurological diseases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If emotional state estimation technique is used, then estimation range covers emotions like anger, joy, tension, but precision of disease estimation is low
Solution Approach 1:
The patent segments the acoustic parameter analysis into multiple independent components (pitch frequency, jitter, shimmer, spectral features, formant frequencies) that can be individually calculated and combined. This segmentation allows comprehensive disease estimation by integrating multiple independent measurements, thereby improving precision while maintaining broad adaptability across different mental and neurological diseases.
Solution Approach 2:
The patent creates a composite diagnostic approach by combining multiple acoustic parameters (pitch frequency, jitter, shimmer, spectral characteristics, formant frequencies) into an integrated disease estimation system. This composite methodology leverages the strengths of each individual parameter to achieve high precision in disease detection across various mental and neurological conditions.
2Reliability
If acoustic parameters are calculated from voice data, then disease detection capability is improved, but system complexity increases
Solution Approach 1:
The patent replaces complex mechanical or clinical diagnostic systems with computational acoustic analysis. By using automated calculation of acoustic parameters from voice recordings and comparing them against reference ranges through computational processing, the system achieves reliable disease detection without requiring complex physical apparatus or manual clinical assessment procedures.
Solution Approach 2:
The system performs self-service by automatically calculating acoustic parameters from input voice data, comparing results against pre-established reference ranges, and generating disease detection outputs without requiring manual intervention. The computational processing autonomously handles the entire diagnostic workflow, from parameter extraction to disease estimation, simplifying the overall system operation.
Data Source
AI summary
A medical apparatus for estimating a mental/neurological disease with high precision is provided. This medical apparatus includes a computational processing device, a recording device having an estimation program which causes the computational processing device to execute processing recorded therein, a calculation unit configured to calculate a score of a subject, a detection unit configured to detect a disease whose score exceeds a reference range, and an estimation unit configured to estimate a mental/neurological disease.