Magnetic Motion Tracking for Natural Human Computer Interaction: A Review | IEEE Journals & Magazine | IEEE Xplore

Magnetic Motion Tracking for Natural Human Computer Interaction: A Review


Abstract:

In the field of multimodal human–computer interaction (HCI), hand (and finger) motion tracking remains a critical challenge because it is the input means of visual reprod...Show More

Abstract:

In the field of multimodal human–computer interaction (HCI), hand (and finger) motion tracking remains a critical challenge because it is the input means of visual reproduction and provides the necessary parameters for real-time modeling of the haptic model. Among motion tracking methods including optical tracking methods, inertial tracking methods, and magnetic motion tracking (MMT) methods, the MMT method has a great development prospect as a marker-based method because of its advantages of no line-of-sight problem, being natural-oriented, and high accuracy. In this article, we first discuss the performance and application scenarios under different configurations of electromagnet-based MMT (EMMT) and permanent-magnet-based MMT (PMMT) systems. And then, the MMT algorithms are reviewed, which can be divided into two broad categories: The model-based algorithms include linear algorithm, nonlinear optimization algorithm, and recursive Bayesian algorithm, and the offline-data-based algorithms include neural network algorithm and lookup table (LUT) algorithm. In addition, a state-of-the-art comparison of MMT algorithms is given. In the end, we have an insightful discussion and give the expected future outlook of MMT.
Published in: IEEE Sensors Journal ( Volume: 22, Issue: 23, 01 December 2022)
Page(s): 22356 - 22367
Date of Publication: 25 October 2022

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