Markerless Motion Capture Analysis Using Optical Tracking
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Solution Overview
Problem
Current motion capture technologies rely heavily on marker-based methods, which are subjective, time-consuming, and prone to human error, lacking consistency and reliability in data acquisition and interpretation, especially in assessing complex human movements and balance disorders.
Innovation Solution
A system and method for analyzing motion capture data using markerless technologies that include sensors and a processor to capture and analyze kinematic and kinetic data, generating reports by comparing subject data to comparator waveforms and cohorts, reducing subjectivity and improving accuracy through objective measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If marker-based motion capture methods are used, then measurement precision can be achieved, but device complexity and time consumption increase significantly
Solution Approach 1:
The patent extracts and removes the markers from the motion capture system, transitioning from marker-based to markerless technology. This eliminates the need for physical markers while maintaining measurement capability through direct optical tracking of anatomical landmarks, thereby reducing device complexity and setup time while preserving measurement precision.
Solution Approach 2:
The patent replaces the mechanical marker attachment system with an optical-based markerless tracking system. Instead of using physical markers that require mechanical attachment to the body, the system uses computer vision and optical sensors to detect and track anatomical landmarks directly, substituting a mechanical approach with an optical field-based approach.
2Ease of operation
If manual motion assessment methods are used, then ease of operation is maintained, but reliability and consistency deteriorate due to human error
Solution Approach 1:
The system enables self-service by allowing the motion capture process to occur without human intervention in data collection. The automated optical tracking system independently captures, processes, and analyzes motion data, eliminating the need for manual measurement and assessment by practitioners, thereby ensuring consistent and reliable results while maintaining operational simplicity.
Solution Approach 2:
The patent implements automated feedback mechanisms where the system continuously captures motion data, compares it against normative databases, and provides real-time analysis and recommendations. This closed-loop feedback system ensures reliability by objectively measuring and analyzing motion patterns without human error, while the automated nature maintains ease of operation.
3Measurement precision
If comprehensive motion analysis is performed, then diagnostic accuracy is improved, but loss of time increases due to fastidious measurement procedures
Solution Approach 1:
The patent implements continuous motion capture and analysis throughout the entire assessment process. The system continuously tracks motion data in real-time without interruption, eliminating the need for repeated setup and measurement phases. This continuous action allows comprehensive diagnostic analysis to be performed efficiently, maintaining high diagnostic accuracy while reducing total analysis time.
Solution Approach 2:
The system performs preliminary actions by pre-processing and normalizing motion data in real-time as it is captured. The automated system immediately processes raw data, compares it against pre-established normative databases, and prepares analysis results without requiring subsequent manual processing steps. This preliminary automated processing maintains diagnostic accuracy while significantly reducing the time required for comprehensive analysis.
Data Source
AI summary
A system for analyzing data from motion capture measurements has a sensor to measure motion capture measurements, a module configured to receive sensor data from the sensors, and a processor configured to analyze to the sensor data received from the sensors and create a report of such analysis. A computer-implemented method of analyzing data from motion capture measurements includes performing motion capture measurements on a subject, receiving motion capture data from the motion capture measurements, processing the motion capture data and the background data on a computer using an algorithm, including comparing the motion capture data and background data to one or more comparator waveforms, generating a report based on the processing analysis, and communicating the results of the report.