Posture Coaching System Using Sensor Fusion for Weight Training
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Solution Overview
Problem
Current weight training systems face challenges in accurately identifying and correcting abnormal postures without expert assistance, due to high costs, recognition errors, and limited spatial and temporal constraints.
Innovation Solution
A posture coaching system and method that utilizes a sensor module with geomagnetic, gyro, and acceleration sensors to analyze and classify user motion patterns, providing real-time audiovisual feedback for accurate posture correction through machine learning and neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If personal training with experts is used to ensure correct weight training motion, then exercise accuracy and safety are improved, but cost and accessibility deteriorate
Solution Approach 1:
The system enables users to perform self-assessment of their exercise posture using sensors and machine learning algorithms. The automated posture analysis and real-time feedback allow users to independently evaluate and correct their exercise form without requiring expert trainers, making the service accessible to anyone with the device.
Solution Approach 2:
The patent replaces the mechanical system of human expert evaluation with an automated sensor-based detection system. Multiple sensors capture motion data, which is then processed by machine learning models to objectively assess posture accuracy, substituting human judgment with automated computational analysis.
2Measurement precision
If multiple sensors and machine learning algorithms are deployed for accurate posture analysis, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system divides the complex posture analysis task into separate functional modules: sensor data acquisition, coordinate system transformation, pattern recognition, and feedback generation. Each module handles a specific aspect of the analysis, making the overall system more manageable and maintainable despite the complexity of the individual components.
Solution Approach 2:
The patent creates a multi-functional integrated system where a single device performs multiple functions: motion capture, posture analysis, real-time feedback, and exercise guidance. This universal device consolidates what would otherwise require separate systems, reducing overall system complexity while maintaining comprehensive functionality.
3Ease of operation
If real-time feedback is provided without spatial and temporal constraints, then user convenience is improved, but system reliability may deteriorate due to recognition errors
Solution Approach 1:
The system implements real-time feedback loops where sensor data is continuously processed and compared against correct exercise patterns. When deviations are detected, immediate corrective feedback is provided to the user, allowing for continuous adjustment and improvement during the exercise session itself rather than requiring post-exercise analysis.
Solution Approach 2:
The patent pre-loads the system with correct exercise motion patterns and machine learning models before use. This preliminary preparation allows the system to immediately begin accurate recognition and feedback without requiring calibration or setup during the actual exercise, maintaining both reliability and convenience.
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 real-time identification and correction of abnormal postures, improving exercise accuracy without the need for expert guidance or specific spatial and temporal constraints, enhancing user performance and reducing injury risk.
Implementation Method 1
The sensor module may include a geomagnetic sensor, a gyro sensor and an acceleration sensor
Implementation Method 2
The sensor module may include a geomagnetic sensor, a gyro sensor and an acceleration sensor
Implementation Method 3
The sensor module may include a geomagnetic sensor, a gyro sensor and an acceleration sensor
Data Source
AI summary
Disclosed is a posture coaching method for weight training, which includes sensing an exercising motion of a user by a sensor module that is attached to a part of the body of the user or exercise equipment gripped by the user for exercising; calculating an inherent angle of the sensor module and a linear acceleration of each axis of a user-based coordinate system based on the user by using the sensed value; analyzing an exercising posture of the user by detecting and classifying a pattern of the linear acceleration and the inherent angle; and generating exercising posture correction data based on the classified pattern.