Model-based Tracking of Magnetic Sensor Gloves in Real Time
While mechanical tracking is commonly seen in robot-assisted surgery, contactless gesture control leads to a more intuitive approach. Magnetic localization systems might be able to provide an untethered access to the necessary hand movement data. A model-based system exploiting a priori knowledge to improve the accuracy and robustness can be benefi cial in this context. We present a proof of concept, in which the index fi nger of a digital twin of a hand is tracked with three simulated sensors. Based on the physiological composition, the fi nger is modeled as a kinematic chain with rotational degrees of freedom between the segments according to the corresponding fi nger joints. We applied an extended Kalman filter using this description to enhance position and rotation estimates for the sensors on the fi nger segments. We achieved mean absolute errors < 1 cm for the positions and < 10 ∘
for the local rotations with fi rst simulations of a bending motion.
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