Wearable Foot Sensor Risk Scoring for Diabetic Ulcer Alerts
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Solution Overview
Problem
Current methods fail to effectively assess and predict the risk of diabetic foot ulcers, which are a significant complication for diabetic patients, by integrating comprehensive sensor data analysis to generate personalized risk scores.
Innovation Solution
A system and method utilizing temperature sensors in footwear to monitor temperature differences across plantar locations, combined with additional sensors for activity and pressure data, to generate vascular assessment alerts and step count goals, and ultimately calculate a personalized risk score for diabetic foot ulcers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive sensor data analysis is integrated to generate personalized risk scores, then the accuracy and reliability of diabetic foot ulcer risk assessment is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The system divides the risk assessment into multiple independent sensor modules (temperature sensors for vascular assessment, pressure sensors for biomechanical assessment, activity sensors for lifestyle assessment). Each sensor type collects specific data independently, and the processor integrates these segmented data streams to generate comprehensive risk scores, reducing overall system complexity while maintaining assessment accuracy
Solution Approach 2:
The input device is designed as a multi-functional platform that simultaneously performs vascular assessment, biomechanical assessment, and lifestyle monitoring using integrated sensors. This universal device consolidates multiple assessment functions into a single system, reducing the need for separate devices and simplifying data integration while improving comprehensive risk evaluation
2Reliability
If temperature sensors monitor temperature differences across plantar locations to detect vascular issues, then early detection of diabetic foot ulcer risk is improved, but the measurement precision requirements increase
Solution Approach 1:
The system employs multiple temperature sensors positioned at specific plantar locations (heel, midfoot, forefoot) to detect localized temperature variations. Each sensor monitors its specific region independently, and the processor compares temperature differences between locations to identify abnormal heat patterns associated with ulcer risk, achieving early detection without requiring extreme measurement precision
Solution Approach 2:
The system continuously monitors temperature differences and provides feedback by generating vascular assessment alerts when thresholds are exceeded. This ongoing monitoring with immediate feedback enables early detection of vascular issues, allowing intervention before ulcer development while using practical measurement precision levels
3Adaptability or versatility
If multiple sensors collect activity data and pressure readings to generate comprehensive risk scores, then the comprehensiveness of patient assessment is improved, but the data processing complexity increases
Solution Approach 1:
The system merges data from multiple sensor types (temperature, pressure, activity) into a unified risk assessment framework. The processor integrates these diverse data streams by normalizing them to common scales and combining them through weighted algorithms to generate comprehensive risk scores, achieving versatile patient assessment while managing data processing complexity through standardized integration protocols
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides timely alerts and personalized risk scores, helping to prevent diabetic foot ulcers by identifying potential issues early and recommending interventions, thereby improving patient care and reducing complications.
Implementation Method 1
collecting a plurality of temperature readings over a time period by an input device... determining a first temperature difference for the first time by comparing a first temperature reading at a first plantar location to a first temperature reading at a second plantar location
Data Source
AI summary
A method for generating a risk score includes: for each user in a plurality of users, collecting a plurality of sensor readings over a time period using an input device worn by the user, the input device configured to collect the plurality of sensor readings; calculating one or more comparison metrics based on the plurality of sensor readings; determining whether the one or more comparison metrics satisfies one or more threshold requirements; generating a plurality of information alerts if the one or more comparison metrics does not satisfy the one or more threshold requirements in the time period, each information alert corresponding to an information alert type; generating a risk factor for each information alert based on the information alert type; generating one or more alert totals for the time period based on the plurality of information alerts; generating a risk score for the user based on each of the risk factors and the one or more alert totals; and ordering the plurality of users in a list according to the risk score for each user.