Optimized Optical Fiber Sensors for Forearm Muscle Deformation Monitoring and Hand Motion Recognition

Abstract

Hand motion monitoring plays a crucial role in fields such as human-machine interaction and rehabilitation training. Currently, electronic sensors are commonly used for hand motion monitoring. However, they are confronted with issues such as susceptibility to electromagnetic interference and sweat stains. Fiber Bragg Grating (FBG) sensors are small in size, highly sensitive, and possess good biocompatibility. In this paper, a flexible distributed Fiber Bragg Grating sensor is introduced. Emphasis is laid on the optimization and fabrication of the sensor, and performance tests are carried out on the fabricated sensor. To verify the potential of the sensor in hand motion monitoring, experiments are conducted. In the gesture recognition experiment, the Vision Transformer (ViT) model is utilized to classify eight types of gestures, and the final accuracy reaches 96.5%. In the wrist joint angle measurement experiment, the Pearson correlation coefficient between the physical angle and the measured angle is 0.985. In the grasping experiment, individual differences are reflected by the standard deviation during the grasping process. The experiments have demonstrated that the proposed sensor has the potential for monitoring hand motions.