Low Latency Basketball Action Recognition and Game Technology Analysis Based on Spiking Neural Network Under SAGIN Environment

Basketball action recognition based on wearable devices and deep learning has been widely applied in the field of behavior analysis. However, there is an urgent need for real‐time recognition of athlete movements, precise technical analysis, and data privacy protection in modern basketball training and competitions. To this end, this article proposes a low‐latency basketball action recognition and game technology analysis framework based on multimodal spiking neural networks (SNNs) under the space air ground‐integrated network (SAGIN) environment. This study utilizes multiple wearable sensors to synchronously collect high‐frequency multimodal time series signals. To effectively process these sensing data with high spatiotemporal complexity, we design an effective feature extraction backbone based on SNNs which can capture temporal information of time series data with low computational complexity and low latency. In addition, to improve the recognition accuracy and robustness of complex basketball actions, we exploit the joint learning module to enhance multimodal information fusion. At last, to address the issue of data silos and ensure user data privacy, we adopt a personalized federated learning paradigm, allowing all parties involved to collaboratively optimize the global model without sharing local raw data. Our proposed method has been evaluated on various public datasets, including OPPORTUNITY, PAMAP2, SKODA, and our self‐built basketball action dataset. The extensive experimental results demonstrate that our approach achieves significant performance and is more robust to noise compared to other deep models. Our proposed framework can achieve high‐precision real‐time action classification and fine‐grained technical statistical analysis while ensuring low communication and computing overhead, providing an effective technical solution for the intelligent and personalized development of basketball sports in the context of integrated aerospace networks.