Patient Posture Evaluation with 3D Mesh for Reproducible Measurements
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Solution Overview
Problem
Existing methods for diagnosing and treating physiological conditions such as skeletal misalignment and poor posture are inconsistent, prone to human error, and lack standardized, reproducible measurements, leading to variable treatment outcomes and difficulty in quantifying efficacy.
Innovation Solution
A system and method for evaluating patient data using a geometric mesh representation of the body, determining landmarks, and comparing them to reference geometry to assess postural deviations, which includes a graphical user interface for visualization and exercise prescription tailored to individual needs, utilizing machine learning for predictive analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual methods are used for diagnosing and treating physiological conditions, then treatment can be provided, but the diagnosis and treatment are inconsistent and prone to human error
Solution Approach 1:
The patent replaces manual visual assessment and physical measurement methods with an automated computer vision system that uses imaging devices and algorithms to detect anatomical landmarks, measure body composition, and evaluate postural deviations. This substitution of mechanical/manual processes with automated optical and computational systems eliminates human error and ensures consistent, reproducible measurements across different patients and practitioners.
Solution Approach 2:
The system enables automated self-assessment capabilities where the computer vision technology automatically detects landmarks, calculates measurements, and generates evaluation reports without requiring manual intervention. The algorithm independently processes images to determine body fat percentage, muscle mass, and postural alignment, providing consistent results without human variability.
2Measurement precision
If standardized measurements are implemented to improve consistency, then measurement precision improves, but the complexity of the evaluation system increases
Solution Approach 1:
The patent segments the body into distinct anatomical regions by detecting specific landmarks (such as acromion, iliac crest, knee joint) and creating a geometric mesh representation. This segmentation allows for precise measurement of postural deviations in specific body segments while using standardized protocols for landmark identification and measurement calculation, achieving high precision through systematic division of the assessment task.
Solution Approach 2:
The system transforms raw image data into standardized geometric parameters by detecting anatomical landmarks and calculating their spatial relationships. The measurement precision is improved by converting visual assessments into quantifiable parameters (coordinates, distances, angles) that can be consistently measured and compared, while the complexity is managed through automated parameter extraction algorithms.
3Reliability
If personalized exercise prescriptions are provided based on individual postural deviations, then treatment efficacy improves, but the complexity of treatment planning increases
Solution Approach 1:
The system provides personalized exercise prescriptions based on feedback from the postural deviation analysis. The computer vision system detects specific deviations (such as anterior pelvic tilt, rounded shoulders), and the treatment planning module automatically generates targeted exercise recommendations that address the identified deviations. This feedback loop ensures that each patient receives a customized treatment plan based on their specific anatomical measurements and postural characteristics.
Solution Approach 2:
The system performs preliminary analysis of postural deviations and automatically generates exercise prescription templates before final treatment planning. By pre-processing the anatomical data and identifying key deviation patterns, the system prepares personalized treatment frameworks that guide the selection and customization of exercises, reducing the complexity of final treatment planning while maintaining high efficacy.
Data Source
AI summary
A method of extracting and displaying postural measurements from patient data includes retrieving, by a processor of a computing device, the patient data from memory. The patient data includes a geometric mesh representation of a patient, including a plurality of data points corresponding to spatial coordinates of a plurality of vertices in three dimensions. The method also includes determining, by the processor, a reference geometry along the geometric mesh representation in a fixed position with respect to the spatial coordinates; determining, by the processor, a landmark corresponding to one of skeletal or soft tissue anatomy for the patient; and determining, by the processor, a postural deviation of a body portion of the patient by comparing the reference geometry and the landmark. The method further includes displaying, by a display of the computing device, a graphical user interface indicating a characteristic related to the postural deviation.