Permanent Magnet Tracking Method Resistant to Background Magnetic Field for Assessing Jaw Movement in Wearable Devices
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https://figshare.com/articles/dataset/Permanent_Magnet_Tracking_Method_Resistant_to_Background_Magnetic_Field_for_Assessing_Jaw_Movement_in_Wearable_Devices/17430482/1
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Abstract. There is a large gap between primitive bruxism detectors and sophisticated clinical machines for jaw kinematics evaluation. Large, expensive clinical appliances can precisely record jaw motion, but completely restrain the patient for the duration of the test. Wearable bruxism detectors allow to continuously count and record bites but provide no information about jaw movement trajectories. Previously, we have developed a permanent magnet and 3-axial magnetometer-based method for wearable, intra-oral continuous jaw position registration. In this work, we present an effective solution to the two main drawbacks of the method. Firstly, two-adjacent-magnetometer approach is able compensate for background magnetic fields with no reference sensor outside of the systems magnetic field. Secondly, jaw rotational angles were included into position calculations, by applying trigonometric equations that links translation of the jaw to its rotation. This way we were able to use 3-DOF (degree-of-freedom) magnetic position determination method to track positions of 5-DOF human masticatory system. To validate the method, finite element modeling and 6-DOF robotic arm (0.01 mm, 0.01 deg) was used, which showed 65% increase in precision to average RMSE = 0.17 mm. The method potentially can be utilized in small scale, low-power, wearable intra-oral device for continuous jaw motion recording.<br>One dataset consists of magnetic field values of main and the reference sensor and their calibration values - data needed for position estimation presented in the publication.<br>There are separate datasets for finite element model test, static positioning test and dynamic test. <br>B field values in dataset are arranged in the following order:[Bx By Bz Brefx Brefy Brefz].<br><br>Data is in -32768 to 32768 format, representing -4900 to 4900 uT.<br>
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figshare
创建时间:
2021-12-23



