Bed Load Sensor Center-of-Gravity Variation Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional bed monitoring techniques fail to accurately detect the waking or body movement state of patients, particularly those with dementia or postoperative patients, due to false positives from disturbance factors and inability to differentiate between user movements and external influences, leading to inadequate monitoring of patients in intensive care or remote locations.
Innovation Solution
A bed device equipped with load measurement sensors and computational units that analyze load and center-of-gravity variations, using threshold values and weighting coefficients to filter out disturbance effects, totals significant movements over time periods to determine the user's waking or sleeping state with high precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional bed monitoring techniques use center of gravity information to detect user movement, then it is possible to detect user position changes, but false positives occur when disturbance factors (objects placed on bed, persons leaning on bed) cause center of gravity variations that are indistinguishable from user arising actions
Solution Approach 1:
The patent segments the monitoring function into multiple independent detection units: load variation detection, center of gravity variation detection, and their combined analysis. Each unit processes specific aspects of bed load changes, allowing the system to cross-validate results and distinguish genuine user movements from disturbance factors by comparing patterns across different detection dimensions
Solution Approach 2:
The patent introduces load variation information as an intermediary parameter that mediates between raw center of gravity data and final waking state determination. By analyzing the relationship and temporal correlation between load variation and center of gravity variation, the system can filter out false positives caused by disturbance factors that affect only one parameter without causing corresponding changes in the other
2Measurement precision
If the amount of time for determining center of gravity movement is increased to detect slow arising with high precision, then detection accuracy improves, but the system cannot detect situations where users lie down quickly after being up for a long time
Solution Approach 1:
The patent implements dynamic adjustment of detection parameters and time windows based on current monitoring context. The system adapts its analysis timeframe and threshold sensitivity according to detected movement patterns, allowing it to switch between detailed analysis for slow movements and rapid detection mode for quick actions, thereby resolving the contradiction between precision and speed
Solution Approach 2:
The patent employs periodic sampling and analysis of bed load information at multiple time scales. By conducting both frequent rapid checks and periodic detailed analysis, the system can capture both quick transient movements and slower sustained movements, ensuring neither type of action is missed due to fixed time window constraints
3Device complexity
If only center of gravity information is monitored to detect user movement, then the system is simple to implement, but it cannot distinguish between user movements and external influences such as objects placed on the bed or persons leaning on the bed
Solution Approach 1:
The patent segments the monitoring function into multiple independent detection units: load variation detection, center of gravity variation detection, and their combined analysis. Each unit processes specific aspects of bed load changes, allowing the system to cross-validate results and distinguish genuine user movements from disturbance factors by comparing patterns across different detection dimensions
Solution Approach 2:
The patent creates a multi-functional monitoring system that simultaneously performs multiple detection tasks using the same hardware infrastructure. The bed load sensors serve both to measure total load variations and to calculate center of gravity position, extracting multiple types of information from a single measurement source to maintain simplicity while enhancing discrimination capability
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The bed device has load measurement means for generating a load signal; first computation means for computing a center-of-gravity variation or load variation on the basis of the load signal; first determination means for determining whether the computation result for the center-of-gravity variation or load variation is equal to or greater than a first threshold value; totaling means for totaling the number of times that the computation result is determine to be equal to or greater than the first threshold value; second computation means for multiplying the totaling results by coefficients for each time period and adding the results; and second determination means for determining a waking or sleeping state or determining a body movement or rest state of a user on the basis of whether a computation result of the second computation means is equal to or greater than a second threshold value. Movement of a user can thereby be monitored by using load information of a bed unit, and the waking state or body movement state of the bed user can be detected with high precision.