Wearable Data‐Driven Transformer Model for Physical Load Assessment in Badminton Training

This study focuses on capturing the physiological state and action characteristics of badminton players in the high‐intensity and fast‐changing sports scene. It proposes a badminton fitness training evaluation system that combines smart wearable devices and deep learning. Through multi‐dimensional data fusion and innovative network architecture, the management from data collection to physical fitness evaluation is realized. First, the monitoring principle of the intelligent exercise bracelet is deeply explored. Through an adaptive filtering algorithm, the heart rate monitoring error for high‐intensity exercise is effectively reduced. Furthermore, the AMste‐Transformer network is innovatively proposed. Based on the time–space mixed attention mechanism, the network addresses the cross‐domain mapping challenge of millimeter‐wave radar data to three‐dimensional (3D) attitude. With adaptive convolution kernel sizes and an Efficient Channel Attention (ECA) feature enhancement module, this study improves estimation accuracy for critical joints including the shoulders, elbows, and wrists. Experiments are conducted on the Human 3.6 M dataset under Protocol 1 and Protocol 2. The model uses 8 attention heads, an embedded feature channel dimension of 512, and a network depth of 4. The experimental results show that the Mean Per Joint Position Error (MPJPE) of AMste‐Transformer in Protocol 1 is 54.3 mm, which is 8.7% lower than that of the second‐best PoseFormer. For badminton‐specific movements, the key joint error is 17.7% lower than that of the baseline Transformer method. The improved smart sports band has achieved high‐precision heart rate monitoring in badminton scenarios with various exercise intensities. Its Pearson correlation coefficient with the medical Holter gold standard reaches up to 0.99. This study provides a scientific tool for badminton training and a technical framework for physical fitness evaluation of other high‐intensity intermittent sports.