CST Framework: A Robust and Portable Finger Motion Tracking Framework

Abstract

Finger motion tracking is a significant challenge in the field of motion capture. However, existing technology for finger motion tracking often requires the wearing of a heavy device and a laborious calibration process to track the bending angle of each joint; this can be challenging, particularly because the motion of each finger has a high coupling characteristic. To address this issue, in this work, we have proposed a compressed sensing-based tracking (CST) framework that enables the estimation of the bending angle of all hand joints using sensors smaller than the number of hand joints. Our framework also integrates a real-time calibration function, which significantly simplifies the calibration process. We developed a glove with multiple liquid metal sensors and an inertial measurement unit to evaluate the effectiveness of our CST framework. The experimental results show that our CST framework can achieve high-speed and accurate hand arbitrary motion capture with only 12 sensors. The motion-tracking gloves developed on this basis are user-friendly and particularly suitable for human–computer interaction applications in robot control, the metaverse and other fields.