Biomechanical Feedback System Using Cross-Platform Physics Engine
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Solution Overview
Problem
Current systems for delivering biomechanical feedback to human and object motions are often expensive, lack consistency across platforms, and fail to provide actionable insights for improving performance and reducing injury risk, with wearable technology being limited in precision and accuracy.
Innovation Solution
A system utilizing multiple hardware data capture devices, a cross-platform compatible physics engine, and interactive platforms to collect and process kinematic and kinetic data, providing prescriptive feedback through a user-friendly interface that correlates biomechanical data with idealized motion models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sophisticated motion capture systems are used to deliver biomechanical feedback, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The system segments the complex biomechanical analysis into multiple components: optical motion capture for kinematic data, force plates for kinetic data, and separate processing modules for different types of biomechanical calculations. This segmentation allows each component to be optimized independently while maintaining overall system precision.
Solution Approach 2:
The patent introduces an intermediary processing system that bridges the gap between simple wearable sensors and complex motion capture laboratories. This intermediary layer includes automated processing algorithms and standardized feedback formats that translate raw sensor data into actionable biomechanical insights without requiring full laboratory infrastructure.
2Measurement precision
If proprietary software and processing algorithms are developed to extract biomechanical metrics, then measurement precision is improved, but device complexity and ease of operation worsen
Solution Approach 1:
The system implements automated feedback mechanisms that process biomechanical data through proprietary algorithms and deliver actionable insights to users in real-time. The feedback includes specific performance metrics, comparison to normative data, and automated recommendations, eliminating the need for users to manually interpret complex biomechanical measurements.
Solution Approach 2:
The patent enables self-service functionality where the system automatically performs biomechanical analysis, generates performance reports, and provides corrective recommendations without requiring expert intervention. Users can independently access and interpret their biomechanical data through standardized, user-friendly interfaces.
3Measurement precision
If comprehensive motion detection is implemented to provide prescriptive feedback, then measurement precision is improved, but loss of information and processing requirements increase
Solution Approach 1:
The system extracts only the most relevant biomechanical parameters from comprehensive motion detection data for feedback delivery. Rather than presenting all available data, the system identifies and extracts key performance indicators and risk factors that are most actionable for users, reducing information overload while maintaining measurement precision.
Solution Approach 2:
The patent transforms comprehensive motion detection data into standardized biomechanical parameters that are easier to process and interpret. This includes converting raw sensor data into normalized kinematic and kinetic measures, and further transforming these into clinically relevant metrics that maintain precision while reducing data complexity.
4Adaptability or versatility
If multiple hardware platforms are integrated to deliver consistent feedback, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system implements a universal data processing framework that can accommodate multiple hardware platforms including optical motion capture systems, inertial measurement units, and force plates. This universal framework uses standardized processing algorithms and common feedback formats that work across different sensor types and platforms, enabling cross-platform compatibility without requiring separate processing systems for each hardware type.
Data Source
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AI summary
A method and system to deliver biomechanical feedback utilizes three major elements: (1) multiple hardware data capture devices, including optical motion capture, inertial measurement units, infrared scanning devices, and two-dimensional RGB consecutive image capture devices, (2) a cross-platform compatible physics engine compatible with optical motion capture, inertial measurement units, infrared scanning devices, and two-dimensional RGB consecutive image capture devices, and (3) interactive platforms and user-interfaces to deliver real-time feedback to motions of human subjects and any objects in their possession and proximity.