Wrist-Mounted Arm Fatigue Analysis System for Pitchers
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Solution Overview
Problem
Current athletic monitoring technologies, such as wearable devices, are inadequate in accurately determining a pitcher's arm fatigue levels during baseball pitching, relying on pitch count rather than comprehensive stress analysis, which can lead to inadequate fatigue assessment and potential injury.
Innovation Solution
An arm fatigue analysis system comprising a wrist unit with accelerometers and a computing device that processes x, y, z data to calculate per pitch stress levels and fatigue levels, providing graphical feedback and alarm settings to indicate when a pitcher is fatigued, using a combination of accelerometers on the wrist to track arm orientation and effort levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pitch count is used to monitor pitcher fatigue, then the monitoring system is simple and easy to implement, but the measurement precision of fatigue assessment is insufficient
Solution Approach 1:
The patent combines multiple sensors (accelerometers, gyroscopes, magnetometers) into an integrated monitoring system that collects data from multiple sources simultaneously. This merging of sensing capabilities enables comprehensive fatigue assessment through multi-parameter analysis, resolving the contradiction by achieving high measurement precision through combined sensor data while maintaining system manageability through integrated design.
Solution Approach 2:
The wearable device performs multiple functions including motion tracking, stress analysis, fatigue monitoring, and performance evaluation. By making the system multi-functional, it achieves high measurement precision for fatigue assessment while consolidating various monitoring tasks into a single device, thereby managing complexity through universal design.
2Measurement precision
If comprehensive stress analysis is implemented, then the measurement precision of fatigue levels improves, but the device complexity increases
Solution Approach 1:
The system segments the monitoring function into distinct sensor components (accelerometers for linear motion, gyroscopes for rotational motion, magnetometers for orientation) that work together. This segmentation allows comprehensive stress analysis through multiple specialized sensors while managing complexity by dividing the system into functional modules with clear responsibilities.
Solution Approach 2:
The patent uses a processing unit as an intermediary that receives raw data from multiple sensors, processes and integrates the information, and generates fatigue assessments. This intermediary component coordinates the complex interactions between sensors and output, enabling comprehensive stress analysis while managing system complexity through centralized processing.
3Reliability
If multiple sensors are used to track arm orientation and effort levels, then the reliability of fatigue detection improves, but the weight of the wearable device increases
Solution Approach 1:
The patent employs flexible circuit boards and thin-film sensor technologies that reduce the weight and rigidity of individual sensor components. By using flexible and thin materials for the sensor substrate and housing, the system achieves high reliability through multiple sensors while minimizing the weight penalty through lightweight construction techniques.
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
The system effectively assesses arm fatigue by analyzing arm orientation and effort levels, providing accurate fatigue monitoring and alerting coaches or players when a pitcher is nearing exhaustion, thus preventing overuse injuries and optimizing pitching performance.
Implementation Method 1
a first accelerometer of the pair of accelerometers is disposed at a radius distal area of the wrist and a second accelerometer of the pair of accelerometers is disposed at an ulnar distal area of the wrist
Data Source
AI summary
A method includes collecting, for a pitch, per pitch data that includes a plurality of first arm orientation data points and a plurality of second arm orientation data points. The method further includes analyzing the per pitch data to determine a release point arm orientation and an effort level. The method further includes calculating a per pitch stress level based on the release point arm orientation and the effort level. The method further includes calculating, for a set of pitches, a fatigue level based on the per pitch stress level of each pitch of the set of pitches.