Machine Learning Golf Club Fitting via Motion Capture
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Solution Overview
Problem
Current golf club fitting methods do not adequately account for the unique swing mechanics and preferences of individual golfers, leading to suboptimal club selection and performance.
Innovation Solution
A method utilizing machine learning analysis of motion capture data from optical, accelerometer, LIDAR, or markerless video systems to recommend personalized golf club profiles, including shaft, club, and build specifications, based on extensive data collection and analysis of golfer swing variables and subjective feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional golf club fitting methods are used, then the process is simple and quick, but the club selection does not adequately account for individual swing mechanics and preferences
Solution Approach 1:
The patent segments the club fitting process into multiple components: motion capture data collection, machine learning analysis, and club recommendation. The motion capture system divides the golfer's swing into discrete measurable parameters (club head speed, attack angle, face angle, etc.), allowing precise analysis of swing mechanics without requiring a monolithic complex system.
Solution Approach 2:
The patent introduces machine learning algorithms as an intermediary between the motion capture data and club selection recommendations. This intermediary processes the complex swing data and translates it into actionable club fitting recommendations, bridging the gap between raw measurement data and practical club selection without requiring direct human expert analysis of each parameter.
2Measurement precision
If motion capture systems with multiple sensors are used, then swing data accuracy improves, but system complexity and cost increase
Solution Approach 1:
The patent merges multiple motion capture technologies (optical tracking, accelerometers, LIDAR, markerless video systems) into a unified club fitting system. By combining these different sensing modalities, the system achieves comprehensive swing measurement capability while managing complexity through integrated data processing and machine learning algorithms that handle the combined data stream.
Solution Approach 2:
The motion capture system is designed with multi-functionality, capable of operating with different sensor types (optical, accelerometer, LIDAR, video) depending on the application requirements. This universal approach allows the system to achieve high measurement precision across various swing conditions and environments without requiring a completely different system for each sensing modality.
3Measurement precision
If extensive swing data collection is performed, then club recommendation accuracy improves, but fitting time increases
Solution Approach 1:
The patent implements preliminary action by pre-processing and analyzing swing data in real-time during the fitting session. The machine learning algorithms continuously process motion capture data as it is collected, providing immediate feedback and recommendations rather than requiring extensive post-session analysis. This allows extensive data collection to occur without proportionally increasing fitting time.
Solution Approach 2:
The system maintains continuous useful action by performing machine learning analysis continuously throughout the data collection process. Rather than collecting all data first and then analyzing, the system analyzes swing mechanics in real-time as each swing is captured, maintaining a continuous feedback loop that provides timely recommendations while utilizing extensive swing data.
Data Source
AI summary
The present disclosure relates to methods and devices for custom fitting golf clubs to golfers using analysis of golf swing mechanics and data obtained from the golfer being fitted in addition to extrinsic data correlations. Methods obtained from any type of motion capture system that includes optical, accelerometer, LIDAR or markerless video based systems are applied to a machine learning analysis to a data set of golf swings.