Research on multi-node gait information acquisition system and time synchronization based on BLE

Gait information is critical in various domains. However, achieving accurate time synchronization across multiple sensor nodes in wireless systems remains a challenge, particularly in gait information acquisition, where precise data alignment is essential. Current solutions are limited by high power consumption, system complexity, and transmission instability. This study proposes a multi-node gait information acquisition system incorporating a six-axis inertial sensor and a plantar pressure sensor, with the ESP32 serving as the core processing unit. The system utilizes the low-power Bluetooth protocol for real-time data transmission. To address the issue of time desynchronization, we introduce an average error-based time synchronization algorithm. The algorithm was tested in an experimental setup using a signal generator, two gait systems, and a mobile device. The results demonstrate that the average error method effectively estimates and corrects frequency drift, significantly reducing time synchronization errors. The system offers a low-power, high-precision solution for multi-node gait information acquisition, advancing the accuracy of gait data fusion and analysis.