Source of this article and featured image is Arduino Blog. Description and key fact are generated by Codevision AI system.
This article discusses an innovative electronic paddle designed to enhance table tennis training through data-driven insights. The paddle, developed by Samuel Alexander, uses an Arduino Nano 33 BLE Sense Rev2 board to monitor and analyze strokes. It provides real-time feedback on stroke types and counts, helping players improve their technique. The system also includes a web interface for detailed session analysis, making it a valuable tool for serious players. This tutorial is worth reading because it showcases how machine learning can be applied to sports training. Readers will learn how to build and use a smart paddle that tracks and analyzes different types of strokes.
Key facts
- The electronic paddle uses an Arduino Nano 33 BLE Sense Rev2 board to monitor movement and analyze strokes.
- It can classify different types of strokes, such as backhand drives and forehand smashes, with high accuracy.
- The system includes an OLED screen for real-time feedback and a web interface for detailed session analysis.
- Samuel Alexander designed the paddle to be balanced and functional for real-world training.
- The final accuracy of the stroke classification system reached 88.7%.
