Selective Data Transmission for Diabetes Care Systems
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Solution Overview
Problem
Diabetes care systems face challenges in reliable data transmission due to unpredictable wireless communication link durations and user limitations, leading to potential health risks from incomplete or incorrect data logging and transmission.
Innovation Solution
A diabetes care system that employs a selective data transmission method using a processor-controlled selection algorithm to prioritize and transmit a representative partial set of data, allowing for reliable information overview without requiring all data to be transmitted, and adapts transmission strategies based on probability and random functions to account for varying link durations and user behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data is transmitted sequentially using classical data transmission methods, then complete data logging is achieved, but the transmission time and user binding to base station increase significantly
Solution Approach 1:
The patent extracts and transmits only the most relevant data elements (last measured values, alarm events, status changes) rather than all accumulated data. This selective extraction reduces transmission volume while maintaining clinical decision-making capability, directly resolving the contradiction between complete data transmission and time efficiency.
Solution Approach 2:
The data set is segmented into different priority levels and types (critical measurements, alarms, status changes, routine data). The system transmits high-priority segments first during available communication windows, allowing critical information to be transmitted reliably without requiring transmission of the entire data set, thus reducing overall transmission time while maintaining reliability.
2Reliability
If wireless communication link duration is extended to ensure complete data transmission, then data completeness improves, but user mobility and comfort deteriorate
Solution Approach 1:
The system performs partial data transmission by sending only the most critical and recent data elements during brief communication windows. This partial action approach ensures that essential information is transmitted reliably without requiring the user to remain bound to the base station for extended periods, thus maintaining both reliability and user mobility.
Solution Approach 2:
The mobile component continuously pre-processes and prioritizes data in memory before transmission, identifying critical measurements and events in advance. This preliminary organization allows the system to transmit essential data efficiently during brief communication windows, eliminating the need for extended user binding while maintaining transmission reliability.
3Ease of operation
If data transmission is performed automatically without user monitoring, then user comfort improves, but data transmission reliability under varying link conditions deteriorates
Solution Approach 1:
The system dynamically adapts its data transmission strategy based on actual communication link conditions. The processor-controlled selection algorithm adjusts which data elements are transmitted based on available link duration, signal quality, and data priority. This dynamic adaptation ensures reliable transmission of critical information even under varying automatic link conditions without requiring user monitoring.
Solution Approach 2:
The system implements feedback mechanisms where transmission results and link conditions are analyzed to adjust future transmission strategies. The processor learns from past transmission outcomes and optimizes data selection algorithms accordingly, ensuring reliable automatic transmission without user intervention by continuously improving its ability to transmit critical data within available link windows.
4Productivity
If selective data transmission algorithm is implemented, then transmission efficiency improves, but device complexity increases
Solution Approach 1:
The selection algorithm applies different quality criteria to different data elements based on their clinical importance. Critical measurements, alarms, and status changes receive higher priority and are selected for transmission first, while routine data receives lower priority. This local quality differentiation approach improves transmission efficiency without requiring overly complex algorithms, as the prioritization rules are based on clear clinical relevance criteria.
Data Source
AI summary
A diabetes care system for detection of an analyte and method for selective data transmission are disclosed. The diabetes care system has a mobile component and a base station, wherein a data transmission occurring between the mobile component and the base station within a time interval in which a wireless communication link exists, wherein is selectively performed in such a manner that within the time interval, a first partial set of the data is transmitted from the mobile component to the base station. The first partial set is selected using a processor-controlled selection algorithm in such a manner that the data transmitted in the time interval is representative of the entirety of the data stored in the mobile component.