Precise 6-DOF Motion Tracking of Fine Motor Skills of Fingers Based on Wearable Magnetic Induction Sensors

The development of telecommunication technologies has increased the relevance of remote-control tasks, including the use of methods of increased accuracy for critical areas. Depending on the application field, remote control or monitoring devices can be equipped with various types of sensors, including inertial measurement units (IMUs). By combining the mobility, autonomy, and accuracy of the IMUs, a tracking system can be created, allowing an objective assessment of the fine motor skills of fingers according to readings of sensors. Here, a description of the mathematical model of IMU movement in an external magnetic field based on readings of sensors such as an accelerometer, gyroscope, and magnetometer is presented. The possibility of estimating the orientation of the inertial sensor using quaternions calculated by the gradient descent method with the Madgwick filter and the applicability of this approach for complex types of motion are shown. The usage of both inertial and magnetic tracking methods separately and an attempt to combine the motion moduli using the Kalman filter are evaluated. We demonstrate that the hardware solutions and methods for determining the position of the sensors, in conjunction with the inverse kinematics method, work quickly and allow one to register the fine motor skills of users with the restoration of the position of hand segments. The developed prototype of the tracking system controller with six degrees of freedom (6-DOF) allows for an accurate assessment of the position and orientation of the IMU sensor array, making it possible for usage in various fields, including entertainment, industry, and medicine.