Athletic Motion Sensor System for Non-Intrusive Performance Analysis
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Solution Overview
Problem
Current data capture and analysis devices for athletes are intrusive, interfering with their performance and often not allowed in competitive events, necessitating a non-intrusive system for gathering and analyzing motion data.
Innovation Solution
A system utilizing sensors such as accelerometers and gyroscopes integrated into athletic equipment, transmitting data to a processor for real-time analysis and qualitative assessment, allowing for the identification of specific motions and outcomes without hindering the athlete's mobility or violating sport rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data capture devices are integrated into athletic equipment, then measurement precision is improved, but device complexity increases and may interfere with athlete performance
Solution Approach 1:
The system divides the data capture functionality into separate modular sensor units (accelerometers, gyroscopes, magnetometers) that can be independently integrated into different pieces of athletic equipment. Each sensor package operates as an independent module, allowing for precise motion tracking without requiring a complex integrated system.
Solution Approach 2:
A wireless communication intermediary (transceiver system) is introduced to bridge the sensor units and the processing system. This allows data to be transmitted without physical connections, reducing mechanical complexity while maintaining measurement precision. The wireless intermediary handles data transmission without requiring direct coupling between sensors and processing equipment.
2Measurement precision
If multiple sensors are integrated into athletic equipment, then measurement precision is improved, but the equipment may impede athlete mobility and performance
Solution Approach 1:
Sensors are strategically positioned at specific locations on athletic equipment where they can capture the most relevant motion data with minimal impact on performance. For example, accelerometers are placed in boxing gloves to capture punch dynamics, while gyroscopes are positioned in footwear to track foot orientation, ensuring local optimization of measurement quality without overall system interference.
Solution Approach 2:
The sensor packages are enclosed in flexible, lightweight housings that conform to the contours of athletic equipment without adding rigid structures. This allows the sensors to be integrated into gear like boxing gloves and footwear while maintaining the flexibility and comfort required for optimal athletic performance.
3Productivity
If real-time data analysis is performed, then productivity is improved, but use of energy increases
Solution Approach 1:
The system performs data analysis at periodic intervals rather than continuously, processing sensor data at key moments in the athletic activity (e.g., at the completion of a punch, jump, or sprint interval). This periodic processing provides real-time performance feedback while significantly reducing overall energy consumption compared to continuous analysis.
Solution Approach 2:
The system processes only the most critical motion parameters in real-time while deferring analysis of less critical data. This partial processing approach provides sufficient performance feedback for immediate athletic adjustments without the full computational burden of analyzing every sensor parameter continuously.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables effective, non-intrusive data capture and analysis, providing qualitative assessments of athletic performance in real-time, enhancing training and competition monitoring while adhering to sport regulations.
Implementation Method 1
a first three-axis accelerometer coupled to the first processor
Implementation Method 2
a first gyroscope coupled to the first processor
Data Source
AI summary
The systems and methods described herein attempt to provide data capture and analysis in a non-intrusive fashion. The captured data can be analyzed for qualitative conclusions regarding an object's actions. For example, a system for analyzing activity of an athlete to permit qualitative assessments of that activity comprises a first processor to receive activity-related data from sensors on the athlete. A first database stores the activity-related data. A second database contains pre-identified motion rules. A second processor compares the received activity-related data to the pre-identified motion rules, wherein the second processor identifies a pre-identified motion from the pre-identified motion rules that corresponds to the received activity-related data. A memory stores the identified pre-selected motion.