Bed Load Variation Analysis for Fluid Balance Event Prediction
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Solution Overview
Problem
Current fluid balance management in medical facilities is limited by infrequent weight measurements and manual recording, making it difficult to accurately manage and predict fluid balance variations, especially when patients are not in bed.
Innovation Solution
A system that includes a detection device to monitor load variations on a bed, a prediction device to analyze this data and predict events causing fluid balance changes, and a learned model generation device using machine learning to enhance prediction accuracy and automate fluid balance management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If body weight measurement is performed at a frequency of once per day to once per several days, then the measurement process is simple, but the management precision of fluid balance information deteriorates
Solution Approach 1:
The patent replaces manual mechanical weight measurement with an automated load detection system using sensors that continuously monitor bed load variations. This substitution enables automatic detection of patient weight changes without requiring periodic manual measurements, thereby improving measurement precision while maintaining operational simplicity through automation.
Solution Approach 2:
The patent implements continuous load detection on the bed to monitor patient weight variations throughout the day, replacing intermittent manual measurements. This continuous monitoring captures fluid balance changes in real-time, significantly improving measurement precision while the automated system maintains simplicity in data collection and management.
2Device complexity
If manual recording of fluid balance is performed, then the device complexity is low, but the productivity of fluid balance management deteriorates
Solution Approach 1:
The patent implements a self-service system where the load detection device automatically records and processes fluid balance information without requiring manual intervention. The system autonomously detects weight variations, calculates fluid balance changes, and generates management records, thereby improving productivity while keeping the device structure relatively simple.
Solution Approach 2:
The patent replaces manual recording operations with an automated information processing system that detects load variations and automatically generates fluid balance records. This substitution eliminates manual labor in data collection and processing, significantly improving management productivity while the system maintains acceptable complexity through standardized processing algorithms.
3Measurement precision
If automated prediction of fluid balance events is implemented, then the measurement precision of fluid balance improves, but the device complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where load detection data is continuously fed into a prediction device that analyzes weight variations and predicts fluid balance events. The system uses historical data and patterns to improve prediction accuracy over time, achieving high measurement precision through iterative learning while managing device complexity through systematic feedback processing.
Solution Approach 2:
The patent introduces a prediction device as an intermediary between the simple load detection system and the fluid balance management outcome. This intermediary component processes raw load variation data and generates predictive information about fluid intake and excretion events, thereby improving measurement precision while isolating the complexity of prediction algorithms from the basic detection system.
Data Source
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AI summary
A fluid balance management system includes: a detection device configured to output a detection signal corresponding to a load applied to a bed in which a subject is present; a prediction device configured to acquire load variation information indicating a variation over time of the load based on the detection signal, and predict an event that causes variation in fluid balance of the subject from the load variation information; and an output device configured to output prediction information corresponding to a prediction result of the event.