A Hand Motion Recognition System Combining Wearable Sensing Gloves and Template Matching Algorithm
Dapeng Wang, Yupeng Fu, Bo Yang, Teng Liu, Chuizhou Meng, Shijie Guo · 2024
Hand motion recognition systems, especially those these using wearable electronic glove, have received growing attention in the field of human-computer interaction and medical rehabilitation. However, two problems still exist: (1) the sensors are usually single, which fails to acquire the multi-sensor information; and (2) Pattern recognition based on deep learning algorithms tend to require a large number of samples to ensure pattern recognition accuracy, whereas obtaining a large amount of hand movement information from a patient is difficult. To address the above problems, this study develops a hand motion recognition system through combining a wearable sensing glove and a new template matching algorithm. The wearable sensing glove employs five Flex sensors and one Inertial Measurement Unit (IMU) to obtain the gesture information, followed by realization of the human-computer interaction through the Unity3D software. Meanwhile, a simple template matching algorithm is constructed for the hand gesture recognition, which can recognize 10 numbers and 20 letters in American Sign Language (ASL) with an accuracy of 90.11% and 87.13%, respectively. The proposed hand motion recognition system can basically meet the needs of patients for hand movement recognition.