A Breathable Soft Sensor for Tracking Racket Swings in Sports

Accurately counting racket swings is critical in badminton training, as it provides essential feedback for athletes to monitor training volume, optimize techniques, and prevent overtraining. To address the lack of accessible and precise motion monitoring tools, we designed a soft, moisture-permeable IMU-based sensor capable of real-time motion capture and analysis. By applying the Madgwick filter, Butterworth low-pass filter, and Short-Time Fourier Transform (STFT) to the collected data, the system can accurately identify motion postures and calculate the frequency of characteristic movements. We validated the system through experiments involving six participants, including both professional and amateur badminton players. The results showed that the system achieved an accuracy of 96.87% in detecting and counting high-clear shots when compared to video recordings. This sensor provides a practical, non-invasive tool for athletes to independently monitor their training, offering new possibilities for unsupervised data collection and advancing the application of wearable sensors in sports science.