Soft Tissue Stress Modeling for Shoulder Injury Risk Limits
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Solution Overview
Problem
Current ergonomic guidelines for preventing shoulder injuries are inadequate as they rely on oversimplified characterizations and self-reported pain, failing to account for the interaction of posture, force, repetition, and duration, leading to unknown risk levels and limited effectiveness in occupational ergonomics.
Innovation Solution
A method and system using ultrasound devices to measure physical parameters like shear modulus and Young's modulus, combined with finite element modeling, to create a soft tissue damage model that predicts injury risk and provides guidelines for reducing cumulative damage by setting exposure limits and work/rest cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If existing ergonomic analysis relies on theoretical constructs and psychophysical estimates, then the analysis can be performed with simple methods, but the measurement precision and reliability of injury risk assessment deteriorates
Solution Approach 1:
The patent replaces traditional mechanical ergonomic analysis methods with a computational model that uses finite element analysis and musculoskeletal modeling. This substitution allows for more precise calculation of soft tissue stress distributions while maintaining ease of application through automated computing processes, resolving the contradiction between simplicity and precision.
Solution Approach 2:
The patent changes the parameters used in ergonomic analysis from psychophysical estimates to biomechanical parameters including muscle activation levels, tendon force, joint moments, and soft tissue stress distributions. This parameter transformation enables both precise injury risk assessment and practical application through standardized computational protocols.
2Device complexity
If existing approaches use generalized body area characterization, then the analysis is simpler, but the reliability of injury prediction for specific soft tissues deteriorates
Solution Approach 1:
The patent segments the shoulder complex into distinct soft tissue structures including supraspinatus tendon, infraspinatus tendon, deltoid muscle, and rotator cuff muscles. Each segment is modeled with its own biomechanical properties and stress characteristics, enabling reliable injury prediction for specific tissues while maintaining manageable analysis complexity through systematic modular modeling.
Solution Approach 2:
The patent applies local quality analysis by characterizing each soft tissue structure with its specific material properties, geometric configuration, and stress distribution patterns. This localized approach allows for accurate injury prediction for individual tissues such as the supraspinatus tendon while using a unified computational framework that maintains overall analysis simplicity.
3Difficulty of detecting and measuring
If injury detection focuses on self-reported injury after occurrence, then the detection method is simpler, but the loss of time for prevention deteriorates
Solution Approach 1:
The patent implements preliminary action by calculating cumulative damage and injury risk before actual injury occurs. The model continuously accumulates stress history and predicts future injury risk based on current and past loading conditions, enabling intervention before the injury event. This transforms injury detection from reactive to proactive, eliminating time loss while maintaining detection accuracy through computational modeling.
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
Enables the prediction and prevention of musculoskeletal injuries by providing evidence-based guidelines that reduce stress on soft tissues, such as tendons, by accounting for posture, force, and repetition, thereby improving workplace safety and reducing injury risk.
Implementation Method 1
measuring at least one parameter of the soft tissue using an ultrasound device
Implementation Method 2
obtaining physical parameters characterizing the soft tissue of the individual under each of a plurality of loading conditions
Data Source
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AI summary
Techniques for obtaining materials science properties of soft tissue for use in a damage model for ameliorating injuries in an individual performing a process are presented. The techniques can include obtaining physical parameters characterizing the soft tissue of the individual under each of a plurality of loading conditions, fitting a soft tissue damage model based on the parameters, and ameliorating injury in performing the process by implementing guidelines based on the soft tissue damage model.