Research on Rehabilitation Glove System Based on UKF Information Fusion

Inhalt:
This article mainly introduces the hand movement disorder caused by stroke or accident. Because the evaluation of hand rehabilitation is relatively vague, most of them rely on the subjective evaluation of rehabilitation physicians, which makes it difficult for patients to obtain rehabilitation advice conveniently and accurately. In this paper, a hand rehabilitation glove system based on unscented Kalman filter (UKF) information fusion for hand rehabilitation is proposed. The system uses STM32F407VET6 as the processor, and uses the six-position calibration method and ellipsoid fitting method to analyze the acceleration and magnetic force. Then, the pose estimation method of UKF information fusion is used for data fusion, and the processed data drives the hand model in the Unity scene for real-time restoration. Experiments show that the use of pose estimation by unscented Kalman filtering provides the possibility for low-cost hand rehabilitation training.