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

VSEngineering 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

Engineering Contradiction:
Improveease of ergonomic analysisVSAvoidinjury risk assessment precision
Core Design Contradiction:
Ease of manufactureVSMeasurement precision

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.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

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.

Inventive Principle:
Principle #35Parameter changes

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

Engineering Contradiction:
Improveanalysis complexityVSAvoidinjury prediction reliability
Core Design Contradiction:
Device complexityVSReliability

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.

Inventive Principle:
Principle #1Segmentation

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.

Inventive Principle:
Principle #3Local quality

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

Engineering Contradiction:
Improveinjury detection simplicityVSAvoidprevention time
Core Design Contradiction:
Difficulty of detecting and measuringVSLoss of time

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.

Inventive Principle:
Principle #10Preliminary action

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

Methodology Applied
Scientific EffectShear wave propagation: Surface Acoustic Wave

Implementation Method 2

obtaining physical parameters characterizing the soft tissue of the individual under each of a plurality of loading conditions

Methodology Applied
Scientific EffectElasticity: Elasticity

Data Source

PatentEP4032478B1Characterizing soft tissue stress for ameliorating injury in performing a process
Publication Date: 2026.02.18 THE BOEING CO
  • EP4032478B1 patent drawingFigure 1
  • EP4032478B1 patent drawingFigure 2
  • EP4032478B1 patent drawingFigure 3

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.