Motion Analysis System for Human Capability Rating
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Solution Overview
Problem
Current technologies face challenges in efficiently and reliably analyzing large quantities of human motion data to quantify physical capabilities, often requiring expert interpretation and being costly, which limits their routine application in healthcare and other fields.
Innovation Solution
Development of methods and systems that use data mining techniques and protocols to transform motion data into objective, quantified ratings and classifications, allowing for semi-automatic analysis and application by modestly trained individuals, incorporating kinematic, kinetic, and other data to create executable protocols for assessing physical capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion data collection devices are used to measure human movements, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments the complex motion analysis task into distinct components: data collection by sensors, data transmission to processing system, and separate analysis phases (linear and non-linear). This segmentation allows each component to be optimized independently, maintaining measurement precision while reducing overall system complexity.
Solution Approach 2:
A computer processing system acts as an intermediary between the motion data collection devices and the end-user interpretation. This intermediary automatically processes the complex data, transforming raw measurements into meaningful results, thereby reducing the complexity burden on both the measurement devices and the users.
2Measurement precision
If expert interpretation is used to analyze motion data, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary automated processing of motion data through linear and non-linear analysis before expert interpretation is needed. This preliminary action prepares the data in advance, reducing the time required for expert analysis while maintaining interpretation accuracy by preserving detailed information for expert review.
Solution Approach 2:
The system implements a feedback mechanism where automated analysis results are provided to experts, who can then review and refine interpretations. This feedback loop maintains high measurement precision by combining automated efficiency with expert judgment, while reducing total analysis time compared to purely expert-based interpretation.
3Measurement precision
If comprehensive motion analysis is performed, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The computer processing system serves multiple functions: collecting data from various sensors, performing linear analysis, conducting non-linear analysis, and generating comprehensive results. This multi-functionality consolidates complexity into a single universal system rather than requiring separate complex devices for each analysis function.
Solution Approach 2:
The system replaces manual expert analysis mechanics with automated computational mechanics. Complex algorithms for linear and non-linear analysis are executed automatically by computer processing, achieving comprehensive analysis without the complexity of manual procedures while maintaining or improving measurement precision.
4Loss of time
If automated analysis is implemented, then loss of time is reduced, but measurement precision deteriorates
Solution Approach 1:
The system merges multiple analysis approaches (linear analysis and non-linear analysis) into a unified automated processing framework. This combination allows the system to leverage the speed of automated computation while incorporating diverse analytical methods that maintain measurement precision, achieving both time efficiency and accuracy.
Data Source
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AI summary
Motion Analysis is used to classify or rate human capability in a physical domain via a minimized movement and data collection protocol producing a discreet, overall figure of merit of the selected physical capability. The minimal protocol is determined by data mining of a more extensive movement and data collection. Protocols are relevant in medical, sports and occupational applications. Kinematic, kinetic, body type, Electromyography (EMG), Ground Reactive Force (GRF), demographic, and psychological data are encompassed. Resulting protocols are capable of transforming raw data representing specific human motions into an objective rating of a skill or capability related to those motions.