Blood Glucose Pattern Matching for Personalized Management
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Solution Overview
Problem
Diabetes patients face challenges in managing their blood glucose levels effectively due to the need for continuous monitoring and personalized treatment, which is not efficiently addressed by existing home tele-monitoring services.
Innovation Solution
A method and apparatus that compare a patient's blood glucose change pattern with stored data to identify similar patterns, extracting relevant information for providing personalized management recommendations, including a system with a determination unit, extraction unit, and interface unit for delivering tailored blood glucose management information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If home tele-monitoring service is used for remote patient management, then medical expenses and hospital visits are reduced, but the accuracy and personalization of treatment recommendations deteriorate
Solution Approach 1:
The system pre-processes and stores blood glucose information from multiple users in advance, organizing it by similarity metrics. When a new user seeks treatment recommendations, the system can quickly retrieve and compare against pre-organized similar cases, providing personalized recommendations without requiring extensive real-time analysis or frequent hospital visits.
Solution Approach 2:
The system creates simplified representations (copies) of complex blood glucose patterns by extracting key features and storing them in a database. These copied patterns can be efficiently compared and matched against new patient data, maintaining treatment accuracy while reducing the computational and temporal resources needed for analysis.
2Measurement precision
If blood glucose information from multiple users is collected and stored, then personalized treatment accuracy is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments the large volume of blood glucose data by organizing it into distinct user records with standardized fields for blood glucose measurements, timestamps, and treatment information. This segmentation allows the system to process and compare individual patterns independently while maintaining overall system manageability.
Solution Approach 2:
The system transforms raw blood glucose data into standardized parameters and metrics that facilitate comparison across users. By converting diverse data formats into uniform parameters (e.g., blood glucose levels, time intervals, treatment responses), the system reduces processing complexity while preserving the information needed for accurate personalized recommendations.
3Measurement precision
If blood glucose change patterns are compared and analyzed in real-time, then treatment accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary organization of blood glucose patterns by pre-calculating similarity metrics and structuring data for efficient comparison. This advance preparation enables rapid pattern matching when new patient data arrives, achieving high treatment accuracy without requiring extensive real-time computational resources.
Data Source
AI summary
An apparatus and method of providing blood glucose management information includes a determination unit that determines a similarity of a blood glucose change pattern of a user by comparing blood glucose information obtained from the user and stored blood glucose information, an extraction unit that extracts at least one piece of blood glucose information from the stored blood glucose information according to the similarity and generates extracted blood glucose information, and an interface unit which provides the blood glucose management information, which corresponds to the extracted blood glucose information, to the user.