Pressure-Sensing Bedsore Risk Evaluation With Posture Estimation
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Solution Overview
Problem
Existing methods for preventing bedsores require manual intervention and are time-consuming, costly, and lack the ability to accurately assess individual risk based on personal conditions, making it difficult to manage pressure application and evaluate bedsore risk effectively.
Innovation Solution
A system and method that estimates posture and body portions using pressure data, detects key points, evaluates bedsore risk through coordinate data, and generates 3-D data for intuitive risk assessment, incorporating statistical and learning data to provide personalized risk evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used to identify and change patient posture, then bedsore prevention can be achieved, but time consumption and cost increase significantly
Solution Approach 1:
The system enables automatic self-monitoring and self-evaluation of bedsore risk through pressure sensors and computational algorithms. The pressure sensing mat automatically detects pressure distribution, the posture estimation unit automatically determines body posture, and the risk evaluation unit automatically assesses bedsore risk without requiring manual intervention from care workers.
Solution Approach 2:
The patent replaces the mechanical manual inspection and posture adjustment system with an automated sensor-based system. Pressure sensors detect pressure distribution, computational algorithms estimate posture and evaluate risk, and the system automatically generates guidance information, eliminating the need for manual physical inspection and intervention.
2Reliability
If manual posture changing is performed to solve pressure, then bedsore risk reduces, but operational complexity and cost increase
Solution Approach 1:
The system automatically performs the complex tasks of pressure detection, posture estimation, and risk evaluation without requiring skilled manual intervention. The pressure sensing mat continuously monitors pressure distribution, the posture estimation unit automatically calculates body posture from pressure data, and the risk evaluation unit automatically assesses bedsore risk, making the system self-sufficient.
Solution Approach 2:
The patent introduces computational algorithms and software units as intermediaries between the pressure sensors and the final risk assessment. The posture estimation unit acts as an intermediary that translates pressure data into posture information, and the risk evaluation unit acts as an intermediary that combines pressure distribution and posture data to generate risk assessments, simplifying the overall system operation.
3Measurement precision
If continuous manual monitoring is performed, then bedsore risk can be evaluated accurately, but sustained human effort and cost increase
Solution Approach 1:
The pressure sensing mat continuously monitors pressure distribution without interruption, and the system continuously processes this data through the posture estimation and risk evaluation units. This continuous automated monitoring maintains constant surveillance of bedsore risk without requiring periodic manual checks, ensuring uninterrupted and accurate risk assessment.
Solution Approach 2:
The system performs continuous self-monitoring and self-evaluation through automated algorithms that process pressure data in real-time. The computational units continuously calculate posture and evaluate risk without human intervention, maintaining sustained monitoring capacity that would be impossible for manual systems.
4Measurement precision
If individualized pressure assessment is performed for each subject, then bedsore risk evaluation becomes more accurate, but time required for assessment increases
Solution Approach 1:
The system automatically adjusts assessment parameters based on individual subject characteristics such as weight, height, sex, and age. The posture estimation unit calculates posture specific to each individual, and the risk evaluation unit tailors risk assessment parameters to match the subject's personal characteristics, enabling accurate individualized assessment without manual adjustment of parameters for each person.
Data Source
AI summary
A system for evaluating a bedsore risk includes a pressure data reception unit that receives pressure data from a plurality of pressure sensors, a posture and body portion estimation unit that detects the coordinates of key points that are feature points of a body and estimate a posture based on pressure data, to output coordinate data of a pressure region of interest (PROI), that is, an interested pressure region, based on the coordinates of the key points and the posture, and that estimates a body portion, a by-portion risk evaluation unit that evaluates a degree of risk for each body portion based on the coordinate data of the PROI, statistical data, and learning data and to generate by-portion risk evaluation data, and a by-portion risk evaluation data output unit that outputs the by-portion risk evaluation data by dividing the by-portion risk evaluation data into grades according to bedsore occurrence risks.