Wearable Electrostatic-Charge Sensing for Swimming Stroke Detection
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Solution Overview
Problem
Existing systems for analyzing swimming activity are costly, complex, and provide delayed feedback, while low-cost wearable sensors struggle with noisy environments and require multiple sensors to compensate for errors, making reliable performance analysis difficult.
Innovation Solution
A wearable system using an electrostatic-charge-variation sensor coupled with a processing unit to detect swimming movements by analyzing electrostatic charge variations, employing auto-correlation and machine learning to identify swimming strokes and styles with reduced computational burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video cameras are used for swimming analysis, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces the mechanical/video-based sensing system with an electrostatic sensing system. The electrostatic sensor detects changes in electrostatic charge caused by swimming movements, eliminating the need for complex video camera setups and post-processing image analysis while providing accurate swimming stroke detection and style classification.
Solution Approach 2:
The patent extracts only the essential measurement function from the complex video system. Instead of using multiple synchronized video cameras and performing complex image processing, the invention uses a single electrostatic sensor to directly detect the physical quantity of interest (electrostatic charge variation during swimming), simplifying the entire measurement system.
2Reliability
If multiple sensors are used to compensate for errors, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent replaces multiple inertial sensors with a single electrostatic sensor. The electrostatic sensing mechanism inherently provides reliable measurements of swimming movements without requiring sensor arrays or complex error compensation algorithms, thus improving reliability while reducing device complexity.
3Measurement precision
If sophisticated algorithms are used for signal processing, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent replaces complex signal processing algorithms with direct electrostatic measurement. The electrostatic sensor naturally produces clean signals that directly represent swimming movements, eliminating the need for sophisticated post-processing algorithms and enabling real-time feedback without computational delays.
4Measurement precision
If inertial sensors are used in noisy environment, then measurement capability is maintained, but measurement precision deteriorates
Solution Approach 1:
The patent replaces inertial sensors that are sensitive to environmental noise with an electrostatic sensor. The electrostatic measurement principle is inherently more robust in the noisy aquatic environment, as it directly measures electrostatic charge variations caused by body movements without being affected by water resistance, bubbles, or other environmental disturbances that plague inertial measurement units.
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
Provides an inexpensive and reliable method for sensing and monitoring swimming parameters, offering real-time feedback and accurate analysis of swimming style and performance metrics.
Implementation Method 1
The sensor is configured to sense a variation of electrostatic charge of the user during execution of the swimming activity and generate a corresponding charge-variation signal
Data Source
AI summary
A system can be used for detecting execution of a swimming activity of a user. The system includes a processing unit, a buffer, and an electrostatic-charge-variation sensor configured to sense a variation of electrostatic charge of the user during execution of the swimming activity and to generate a corresponding charge-variation signal. The processing unit is configured to acquire the charge-variation signal, detect a first sub-portion of signal that identifies a basic movement of the swimming activity in the charge-variation signal, store the first sub-portion of signal in the buffer, compute an auto-correlation between the first sub-portion of signal stored in the buffer and a second sub-portion of signal of the charge-variation signal, and detect the presence of the basic movement in the second sub-portion of signal based on a result of the auto-correlation.


