Wearable Sensor System for Athletic Motion and Trajectory Prediction
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Solution Overview
Problem
Current methods for analyzing and improving athletic performance, such as the 'eye test' and video recording, are inefficient and unable to accurately account for internal physiological factors like muscle fiber activation and heart rate, leading to inconsistent feedback and prolonged training processes.
Innovation Solution
A system using 200 sensors embedded in skin-tight clothing to capture and analyze body movements and physiological conditions, transmitting data to a computer or device for real-time trajectory prediction and biofeedback, allowing for personalized strength training and diet recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If video cameras are used to record user motion for analysis, then motion evaluation capability is improved, but internal physiological factors remain undetected and measurement precision deteriorates
Solution Approach 1:
The patent combines multiple sensing modalities (accelerometers, gyroscopes, magnetometers, electromyography sensors, temperature sensors, humidity sensors) into a single integrated wearable monitoring system. This merging allows simultaneous detection of both external motion parameters and internal physiological factors, resolving the contradiction between motion evaluation capability and physiological factor detection accuracy.
Solution Approach 2:
The patent introduces wearable sensors as intermediary devices that directly contact and monitor the user's body. These sensors act as mediators between the user's internal physiological state and the external analysis system, enabling precise detection of muscle activation, heart rate, temperature, and other physiological parameters that video cameras cannot detect.
2Ease of operation
If coaches use hands-on eye test to analyze performance, then feedback is provided, but time consumption increases and measurement precision deteriorates
Solution Approach 1:
The patent replaces the manual, mechanical eye-test method with an automated electronic sensing and processing system. The wearable sensors continuously collect data, and the processor automatically analyzes motion parameters and physiological factors, eliminating the time-consuming manual observation and analysis process while maintaining or improving feedback quality.
Solution Approach 2:
The patent implements real-time feedback through the wearable monitoring system that continuously tracks performance metrics and provides immediate analysis. This automated feedback loop eliminates delays inherent in manual coaching processes, allowing users to receive instant performance evaluation and adjustment guidance without the time loss associated with traditional methods.
3Measurement precision
If multiple sensors are embedded in clothing to capture comprehensive data, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent designs the wearable monitoring system with multi-functional sensors that can detect multiple types of data simultaneously. For example, the sensor array includes accelerometers, gyroscopes, magnetometers, electromyography sensors, temperature sensors, and humidity sensors integrated into a single wearable unit. This universal approach allows comprehensive data collection while reducing the number of separate devices needed, thereby managing complexity.
Solution Approach 2:
The patent embeds multiple sensing elements within a nested hierarchical structure where sensors are integrated into the clothing fabric itself. The sensing elements are nested within layers of the garment, with processing units and power sources also integrated into the same structure. This nesting approach consolidates multiple functional components into a unified wearable system, reducing overall complexity while maintaining comprehensive measurement capability.
Data Source
AI summary
A method of analyzing data obtained from sensors worn on the body of an athlete. The sensors provide both location and physiological data. The sensors provide data to a computer program that can analyze the movement of the athlete and compare it to prior movement or optimal movements. The computer program can determine better motions to optimize performance based on the motion data from the sensors. The program can also determine physiological changes for the athlete, such as for example increasing leg strength, to optimize the performance. The program can also analyze and predict the trajectory of the sports object based on the data obtained regarding the athlete's movements and capabilities.


