Golf Swing Practice System Using EMG Sensors for Muscle Activation Feedback
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Solution Overview
Problem
Conventional golf training systems are limited in providing direct and intuitive feedback for improving golf swing techniques, as they often require specialized tools and cannot be used during actual golf rounds, and they do not effectively analyze muscle activation patterns for personalized training.
Innovation Solution
A golf swing practice system that includes EMG sensors and a golf swing analysis device for real-time data collection and comparison with professional golfers' data, providing feedback on muscle activation patterns and potential injury risks, allowing for training anywhere, including during actual golf rounds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional golf training systems use specialized tools to adjust golf club trajectory, then training effectiveness is improved, but device complexity and portability are worsened
Solution Approach 1:
The patent replaces mechanical training aids and specialized tools with an electronic sensing system comprising EMG sensors, inertial sensors, and a processing device that analyzes muscle activation patterns and swing mechanics to provide digital feedback, eliminating the need for physical trajectory-adjustment devices
Solution Approach 2:
The system creates a digital model of the golfer's swing by collecting biomechanical data from multiple sensors and comparing it against professional golfer profiles, providing feedback through data analysis rather than physical intervention
2Measurement precision
If conventional training systems provide kinematic and kinetic data feedback, then swing technique improvement is achieved, but muscle activation analysis capability is lost
Solution Approach 1:
The patent combines multiple sensing modalities including EMG sensors for muscle activation detection, inertial sensors for motion tracking, and processing capabilities into an integrated system that simultaneously captures both kinematic/kinetic data and physiological muscle data
Solution Approach 2:
The system serves multiple functions: it monitors muscle activation patterns, tracks swing mechanics, compares performance against professional profiles, and provides comprehensive feedback covering both physical motion and physiological engagement
3Adaptability or versatility
If EMG sensors and data analysis are integrated into the system, then muscle activation analysis capability is improved, but device complexity increases
Solution Approach 1:
The system focuses on measuring and analyzing specific physiological parameters (muscle activation levels, timing patterns) rather than attempting to control all aspects of the swing mechanically, simplifying the approach through targeted parameter monitoring
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 enables personalized golf swing training by providing direct and intuitive feedback, improving athletic ability, reducing injury risks, and allowing for real-time analysis and adjustment of muscle activation patterns, thus enhancing golf performance and safety.
Implementation Method 1
one or more electromyography (EMG) sensors attached to a specific muscle point on a body of a user
Data Source
AI summary
A golf swing practice system is provided. The golf swing practice system includes one or more electromyography (EMG) sensors attached to a specific muscle point on a body of a user and a golf swing analysis device that is connected to the EMG sensor to enable data communication, wherein the golf swing analysis device may include a sensor signal collector configured to receive an EMG signal of the user from the EMG sensor, a data comparison analyzer configured to compare and analyze EMG data of the user and a professional golfer to be compared, and a user interface configured to receive information about a muscle that the user needs to train and display an analysis result of the data comparison analyzer.


