Cognitive Function State Identification Model for Voice-Based Diagnosis
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Solution Overview
Problem
Current methods for diagnosing cognitive function states, such as Alzheimer's disease and dementia, often require invasive procedures and specialized equipment, leading to patient discomfort and rejection.
Innovation Solution
A method using a device with a cognitive function state identification model that processes user information, voice data, and speech time information to accurately diagnose cognitive function states without the need for invasive tests or special equipment, employing a converter to convert voice data into text, a logic-based event processor to extract linguistic and voice features, and multiple models to generate output data for diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive procedures and specialized equipment are used for cognitive function diagnosis, then measurement precision is improved, but patient comfort and acceptance deteriorate
Solution Approach 1:
The patent replaces invasive mechanical procedures (biopsy, blood collection) with non-invasive voice-based assessment. The cognitive function state identification model processes voice data, speech time information, and linguistic features to diagnose cognitive conditions without physical intrusion, thereby maintaining diagnostic accuracy while eliminating patient discomfort.
Solution Approach 2:
The patent introduces voice data and speech patterns as an intermediary medium for diagnosis. Instead of directly examining biological tissues or fluids, the system uses voice characteristics (pitch, rhythm, pauses, linguistic complexity) as a mediator to infer cognitive function state, reducing harm while preserving measurement precision.
2Measurement precision
If invasive procedures are used for diagnosis, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system replaces complex invasive procedures with simple voice recording and analysis. Users only need to speak naturally into a device, and the cognitive function state identification model automatically processes the voice data, speech time information, and linguistic features to provide accurate diagnosis, making the process accessible and easy to operate.
Solution Approach 2:
The patent enables self-diagnosis through automated voice analysis. The cognitive function state identification model independently processes user-provided voice data without requiring medical professionals to perform invasive procedures, allowing users to assess their cognitive function state conveniently and accurately.
3Measurement precision
If specialized equipment is used for diagnosis, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces specialized medical equipment (biopsy tools, blood analysis devices) with standard voice recording devices and computational models. The cognitive function state identification model, which processes voice data, speech time information, and linguistic features, can be implemented on common computing devices, eliminating the need for complex specialized equipment while maintaining diagnostic precision.
Data Source
AI summary
Disclosed is a method of identifying, by at least one processor of a device, a cognitive function state of a user. The method may include inputting user information, at least one voice data, and speech time information related to the at least one voice data to a cognitive function state identification model, and identifying a cognitive function state of the user based on first output data that is output by the cognitive function state identification model.