IEEE Trans Biomed Eng. 2018 Jan;65(1):52-63. doi: 10.1109/TBME.2017.2688919. Epub 2017 Apr 12.
Tongue tracking, which helps researchers gain valuable insights into speech mechanism, has many applications in speech therapy and language learning. The wireless localization technique, which involves tracking a small magnetic tracer within the 3-D oral space, provides a low cost and convenient approach to capture tongue kinematics. In practice, this technique requires accurate calibration of three-axial magnetic sensors used in the tracking system. The data-driven calibration depends on the trajectories of magnetic tracer and the ambient noise, which may change across time and space.
In this paper, we model the kinematics of tracer movement and the noisy magnetic measurements in a Bayesian framework, then present a joint calibration and localization (JCL) algorithm based on expectation maximization (EM), where the unscented Rauch-Tung-Striebel smoother is employed for tracer localization and the curvilinear search algorithm is applied for sensor calibration.
Based on measurements conducted on our tongue tracking system with a small magnetic tracer (diameter: 6.05 mm, thickness: 1.25 mm, residual induction: 14 800 G), the JCL algorithm achieves averaged root mean square error of 0.45 mm for tracer position estimation and for tracer orientation estimation, which are significantly lower than those of the separate calibration and localization algorithms.
These results show that JCL can help improve the localization accuracy of this system.
A potentially high precision tongue tracking method is demonstrated.
舌位追踪技术可以帮助研究人员深入了解言语机制，在言语治疗和语言学习中具有广泛的应用。无线定位技术通过追踪 3D 口腔空间内的小磁示踪剂，提供了一种低成本、便捷的方法来获取舌部运动学信息。在实际应用中，该技术需要对跟踪系统中使用的三轴磁传感器进行精确校准。数据驱动的校准依赖于磁示踪剂的轨迹和环境噪声，这些因素可能会随时间和空间而变化。
在本文中，我们在贝叶斯框架下对示踪剂运动的运动学和噪声磁测量进行建模，然后提出了一种基于期望最大化（EM）的联合校准和定位（JCL）算法，其中使用无迹 Rao-Tung-Striebel 平滑器进行示踪剂定位，采用曲线搜索算法进行传感器校准。
基于我们的舌位跟踪系统（带有直径为 6.05mm、厚度为 1.25mm、剩磁感应为 14800G 的小磁示踪剂）进行的测量，JCL 算法在示踪剂位置估计和示踪剂方向估计方面的平均均方根误差分别为 0.45mm，明显低于单独的校准和定位算法。
这些结果表明，JCL 可以帮助提高该系统的定位精度。
展示了一种潜在高精度的舌位跟踪方法。
