Voice Data Disease Management System Using Segmented Feature Extraction
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Solution Overview
Problem
Current health management systems rely heavily on wearable devices and IoT technologies for collecting health-related data, but they lack an effective method for predicting and managing diseases using voice data.
Innovation Solution
A voice-based disease management system that receives and processes user voice data to extract context and out-of-context data, generating disease management data for prediction and monitoring purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If voice data is used for disease prediction and management, then new diagnostic capabilities and personalized health management are enabled, but system complexity and data processing requirements increase
Solution Approach 1:
The voice data analysis system is segmented into multiple specialized modules: acoustic feature extraction module, linguistic feature extraction module, context data extraction module, out-of-context data extraction module, and disease prediction module. Each module handles specific aspects of voice analysis, reducing overall system complexity while enabling comprehensive disease prediction capabilities.
Solution Approach 2:
The patent introduces voice data as an intermediary medium between traditional health monitoring methods and disease prediction outcomes. Voice data serves as a non-invasive bridge that captures physiological and psychological states, enabling disease prediction without direct physical intervention while managing complexity through standardized data processing pipelines.
2Measurement precision
If comprehensive voice data analysis is performed to extract context and out-of-context data, then measurement precision for disease detection is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary action by pre-extracting and storing acoustic features, linguistic features, context data, and out-of-context data from voice recordings before disease analysis is needed. This preprocessing approach enables faster real-time disease detection while maintaining high measurement precision, as the computationally intensive feature extraction is completed in advance.
Solution Approach 2:
The patent implements periodic action through scheduled voice data collection and analysis cycles. Voice data is collected at regular intervals, processed through the comprehensive analysis pipeline periodically, and used to update disease prediction models. This periodic approach balances measurement precision with processing time by not requiring continuous real-time analysis.
Data Source
AI summary
A method of disease management using voice data and an apparatus for performing the method can including receiving, by a voice based disease management device, user's voice data. The method and apparatus can also include generating, by the voice based disease management device, disease management data based on the voice data. Optionally, the step of generating disease management data can include extracting context data and out-of-context data based on the voice data.