Motion Analysis System Using Intermediary Visualization
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Solution Overview
Problem
Current motion analysis systems for athletic motions, such as golf swings, lack the ability to capture and present comprehensive data in a way that optimizes user understanding and assimilation, failing to provide effective visualization and prescription of exercises tailored to individual performance levels and deficiencies.
Innovation Solution
A global, knowledge-based system that uses state-of-the-art technology to instrument users with sensors, capture motion data, and provide an information-rich, graphic display of results, allowing for real-time biofeedback and prescription of user-specific training regimes based on performance data, including video, color-coded animations, and synchronized data/time graphs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional motion analysis systems are used to capture positional data of isolated body parts, then measurement precision is improved, but ease of operation deteriorates due to lack of visual aid and complex data interpretation
Solution Approach 1:
The patent introduces an intermediary visualization system that translates complex motion capture data into intuitive graphical representations. The system uses virtual representations of body segments and joints that visually display motion patterns, making the data interpretable without requiring expert analysis. This intermediary layer bridges the gap between precise measurement and easy understanding.
Solution Approach 2:
The system creates visual copies or representations of the actual body motion through graphical interfaces. Instead of presenting raw numerical data, the system generates visual models that replicate the motion patterns, allowing users to intuitively understand their movement patterns without directly interpreting complex positional data.
2Measurement precision
If multiple sensors are used to capture comprehensive motion data, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent implements a multi-functional sensor system where each sensor serves multiple purposes. The sensors not only capture positional data but also contribute to generating visual representations, providing feedback, and analyzing motion patterns. This universal approach allows comprehensive motion capture without proportionally increasing system complexity.
Solution Approach 2:
The system merges multiple sensor functions and data streams into a unified processing and visualization framework. Instead of treating each sensor independently, the patent combines their outputs into integrated visual representations that show the complete motion picture, reducing the apparent complexity for the user.
3Loss of information
If detailed motion analysis data is provided to users, then information completeness is improved, but loss of information increases due to user inability to assimilate and understand the data
Solution Approach 1:
The patent applies local quality by providing different levels and types of information representation tailored to specific user needs and contexts. Rather than presenting all possible data uniformly, the system offers localized visualizations that highlight relevant aspects of motion for different users or situations, making information more assimilable while maintaining completeness.
Solution Approach 2:
The system transforms one-dimensional numerical data into two-dimensional or three-dimensional visual representations. By adding spatial and graphical dimensions to the data presentation, the patent enables users to comprehend complex motion patterns more easily, effectively reducing information loss while maintaining data completeness.
Data Source
AI summary
A system and method for analyzing and improving the performance of a body motion, which requires receiving, by a CPU, sensor data from sensors worn by a user; storing the transmitted sensor data in a data buffer; recognizing that a motion gesture occurred based on a signature of acceleration data in the buffered sensor data, extracting from the data buffer sensor data from a predetermined time window around the moment when the motion gesture occurred; automatically generating a regime file customized for the user based on the extracted sensor data, and generating in real-time a user interface displaying a representation corresponding to the motion indicated by the sensor data, wherein the CPU determines the signature of acceleration data by matching the buffered sensor data with stored motion signatures, wherein the regime file is automatically generated based on diagnostic parameters obtained from the sensor data associated with a motion activity category.