Design and evaluation of an FBG sensor-based glove to simultaneously monitor flexure of ten finger joints

Abstract

This paper demonstrates a fiber Bragg grating sensor-based instrumented glove that simultaneously measures the range of motion of the ten finger joints (five metacarpophalangeal, four proximal interphalangeal and one interphalangeal joint) with very high angular resolution (0.1�). The accuracy and repeatability of all the ten sensors of the glove are compared with a pre-calibrated inertial measurement unit (IMU) sensor. The glove outperforms many earlier reported sensing gloves with a mean error of 0.80�. The standard deviation (1.01�) and range (2.60�) obtained in the reliability test performed on five healthy subjects are also smaller compared to many other gloves. The feasibility of using the glove in real-world applications has been shown by demonstrating a virtual reality (VR) platform that uses a Raspberry Pi-based module to interface the glove with custom VR games running on an Android tablet or a VR headset. VR-based gaming platforms have become popular in the rehabilitation of the upper limb in stroke patients in recent years. The high accuracy and reliability of this glove will enable accurate tracking of the movement quality and recovery progress of stroke patients during the virtual rehabilitation therapy.