Monitoring Data Source Selection to Minimize Unnecessary Switching
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Solution Overview
Problem
Existing monitoring systems face challenges in selecting a reliable data source for a monitoring parameter due to inconsistencies among different data sources, leading to potential confusion and misinterpretation for healthcare professionals.
Innovation Solution
A method and system for selecting a data source among multiple sources based on fitness scores, biased towards maintaining the current primary source unless a clear benefit or convenience is found in switching to a secondary source, with criteria such as fitness variance and value variance thresholds to ensure minimal unnecessary switching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system switches to a secondary data source when its fitness score is slightly higher than the primary data source, then the measurement precision may be improved, but the system stability deteriorates due to unnecessary switching between data sources
Solution Approach 1:
The patent combines multiple data sources to provide a monitoring parameter value, using a selection mechanism that evaluates fitness scores of different data sources. The system merges the capabilities of multiple sensors and data sources while maintaining a single stable output through intelligent selection rather than arbitrary switching.
Solution Approach 2:
The system changes the selection parameter from simple fitness score comparison to a more robust evaluation that considers both fitness scores and switching criteria. This parameter change prevents unnecessary switching by requiring significant fitness improvements before changing data sources, thereby stabilizing the system while maintaining precision.
2Reliability
If the system frequently switches between data sources to maintain the highest fitness score, then the reliability of the monitoring parameter may be improved, but the complexity of the selection mechanism increases
Solution Approach 1:
The patent segments the data source selection process into distinct evaluation components: fitness score calculation and switching criterion assessment. This segmentation allows the system to evaluate multiple data sources independently and select the most appropriate one without requiring complex real-time switching logic, thereby maintaining reliability while managing complexity.
Solution Approach 2:
The system introduces an intermediary selection mechanism that mediates between multiple data sources and the final monitoring parameter output. This intermediary layer evaluates fitness scores and applies switching criteria to determine when to switch data sources, simplifying the overall system architecture while ensuring reliable parameter delivery.
3Adaptability or versatility
If the system uses multiple data sources with different algorithms to derive monitoring parameters, then the adaptability of the monitoring system is improved, but the consistency of the monitoring parameter values deteriorates
Solution Approach 1:
The patent implements a universal selection mechanism that can evaluate and select from multiple different data sources and algorithms. This multi-functional approach allows the system to adapt to different monitoring scenarios and data source types while maintaining consistent output through a standardized selection process based on fitness scores and switching criteria.
Data Source
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AI summary
The disclosed method and system select a data source from multiple data sources, each configured to generate data for determining a value of the same monitoring parameter of a subject. The selection process involves determining a fitness score for each data source and selecting an updated primary data source based on these scores. The selection is biased towards maintaining the current primary data source. Accordingly, the invention provides a selection process that is designed to minimize unnecessary switching between data sources, thereby reducing potential confusion for healthcare professionals and enhancing the reliability of the monitoring parameter values.