Multi-Sensor Motion Capture System for High-Precision Data Fusion
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Solution Overview
Problem
Existing motion capture sensors are limited by accuracy, power usage, and functionality, and lack the ability to utilize motion data for comprehensive analysis and remote monitoring across various applications, including healthcare compliance, gaming, and sports performance, without integrating with multiple equipment types or providing data mining capabilities.
Innovation Solution
A wireless motion capture sensor system that captures orientation, position, velocity, acceleration, proximity, and strain data, with customizable sensor personalities for specific equipment or clothing, enabling advanced calibration, power efficiency, and data mining to analyze and display motion patterns for improved performance and compliance monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single motion capture sensor is used, then device complexity is reduced, but measurement precision and accuracy are limited
Solution Approach 1:
The motion capture system is divided into multiple independent sensor units, each equipped with specific sensors (accelerometers, gyroscopes, magnetometers) to capture different motion parameters. This segmentation allows each sensor to specialize in specific measurements, improving overall measurement precision while distributing system complexity across modular components.
Solution Approach 2:
Multiple sensors including accelerometers, gyroscopes, and magnetometers are merged into a single motion capture unit. This combination enables the system to capture comprehensive motion data (acceleration, orientation, position) simultaneously, achieving high measurement precision without requiring separate systems for each parameter.
2Measurement precision
If high-precision sensors are used, then measurement accuracy is improved, but power usage increases
Solution Approach 1:
The motion capture sensors operate using periodic sampling rather than continuous measurement. The system captures motion data at optimized intervals suitable for the specific application (e.g., golf swing analysis), reducing power consumption while maintaining measurement precision for critical motion events.
Solution Approach 2:
The system dynamically adjusts sampling rates and measurement parameters based on motion intensity and application requirements. During low-activity periods, sampling frequency is reduced to conserve power, while during high-activity events, the system increases precision and sampling rate to capture critical motion data.
3Reliability
If motion capture data is collected continuously, then measurement completeness is improved, but power usage and data processing requirements increase
Solution Approach 1:
The system collects motion data selectively rather than continuously, focusing on capturing partial but critical motion events (e.g., swing initiation, impact moment, follow-through). This partial action approach ensures reliability for key performance metrics while significantly reducing power consumption and data processing requirements.
Solution Approach 2:
The system uses preliminary motion detection algorithms to identify when significant motion events are about to occur, then activates high-precision data collection only during these critical windows. This preliminary detection ensures complete capture of important motion phases without the continuous power consumption of constant high-resolution sampling.
4Adaptability or versatility
If motion capture sensors are integrated into multiple equipment types, then adaptability is improved, but device complexity increases
Solution Approach 1:
The motion capture sensor unit is designed as a universal platform that can be integrated into multiple equipment types (golf clubs, baseball bats, tennis rackets, hockey sticks). The standardized sensor package with accelerometers, gyroscopes, and magnetometers provides multi-functional capability across different sports equipment without requiring equipment-specific customizations.
Solution Approach 2:
The motion capture sensors are nested within existing equipment structures, such as embedding the sensor unit inside the handle or shaft of sporting equipment. This nesting approach allows the sensors to be integrated into multiple equipment types without adding external complexity, as the compact sensor module fits within the existing equipment form factor.
Data Source
AI summary
Motion capture system with a motion capture element that uses two or more sensors to measure a single physical quantity, for example to obtain both wide measurement range and high measurement precision. For example, a system may combine a low-range, high precision accelerometer having a range of −24 g to +24 g with a high-range accelerometer having a range of −400 g to +400 g. Data from the multiple sensors is transmitted to a computer that combines the individual sensor estimates into a single estimate for the physical quantity. Various methods may be used to combine individual estimates into a combined estimate, including for example weighting individual estimates by the inverse of the measurement variance of each sensor. Data may be extrapolated beyond the measurement range of a low-range sensor, using polynomial curves for example, and combined with data from a high-range sensor to form a combined estimate.