Diabetes Management System Pattern Recognition for Glucose Data
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Solution Overview
Problem
Interpreting large numbers of glucose concentration measurements in logbooks is complex and time-consuming for both patients with diabetes and physicians, compounded by limited time constraints, especially when assessing insulin effects and other physiological or external parameters.
Innovation Solution
A diabetes management system that analyzes glucose concentration measurements to identify patterns such as hypoglycemic, hyperglycemic, and blood glucose variability patterns, providing warnings and compliance messages through a user-friendly interface on devices like glucose meters and personal computers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a large number of glucose concentration measurements are recorded and analyzed manually, then comprehensive glycemic data is available, but interpretation becomes complex and time-consuming
Solution Approach 1:
The patent introduces an automated analysis system that acts as an intermediary between the raw glucose measurement data and the clinician/patient. This system automatically processes large datasets, identifies patterns, and generates actionable insights, eliminating the need for manual interpretation of numerous measurements while preserving all available data.
Solution Approach 2:
The patent replaces the mechanical process of manual data review and interpretation with an automated computational system. The system uses algorithms to analyze glucose patterns, identify trends, and generate reports, substituting human cognitive effort with automated processing that can handle large volumes of data efficiently.
2Reliability
If comprehensive assessment of insulin effects and physiological parameters is performed, then better diabetes management is achieved, but the complexity of analysis increases
Solution Approach 1:
The patent segments the complex analysis task into distinct functional modules: data collection from multiple sources, pattern recognition algorithms, statistical analysis, and report generation. Each module handles a specific aspect of the analysis, making the overall complex system manageable and maintainable while providing comprehensive assessment capabilities.
Solution Approach 2:
The patent creates a multi-functional analysis system that can simultaneously evaluate insulin effects, physiological parameters, glucose patterns, and treatment compliance. The system performs multiple assessment functions through a unified platform, reducing the need for separate analysis tools and simplifying the user experience despite the comprehensive nature of the analysis.
3Loss of time
If physicians spend more time with each patient for thorough assessment, then better guidance is provided, but office visit capacity decreases
Solution Approach 1:
The patent performs preliminary analysis of patient data before the clinical encounter. The automated system processes glucose measurements, identifies patterns, and prepares summary reports in advance, allowing the physician to review key findings before meeting the patient. This preliminary action enables more focused and efficient in-person consultations.
Solution Approach 2:
The patent creates digital copies and summaries of complex patient data that can be quickly reviewed. Instead of requiring the physician to examine all raw measurements during the visit, the system generates condensed representations and pattern summaries that capture the essential information, enabling rapid assessment while maintaining thorough analysis capabilities.
Data Source
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AI summary
A diabetes management system or process is provided herein that may be used to analyze and recognize patterns for a large number of blood glucose concentration measurements and other physiological parameters related to the glycemia of a patient. In particular, a method of monitoring glycemia in a patient may include storing a patient's data on a suitable device, such as, for example, a blood glucose meter. The patient's data may include blood glucose concentration measurements. The diabetes management system or process may be installed on, but is not limited to, a personal computer, an insulin pen, an insulin pump, or a glucose meter. The diabetes management system or process may identify a plurality of pattern types from the data including a testing/dosing pattern, a hypoglycemic pattern, a hyperglycemic pattern, a blood glucose variability pattern, and a comparative pattern. After identifying a particular pattern with the data management system or process, a warning message may be displayed on a screen of a personal computer or a glucose meter. Other messages can also be provided to ensure compliance of any prescribed diabetes regiments or to guide the patient in managing the patient's diabetes.