Integral-Free Spatial Orientation Estimation Method and Wearable Rotation Measurement Device for Robot-Assisted Catheter Intervention

Abstract

The spatial orientation of rotating objects is typically measured by utilizing inertial measurement units and requires temporal integration of angular velocities. The integration of the angular velocities accumulates the measurement noise and results in erroneous orientation estimation, thus, necessitates real-time error compensation. In this article, an integral-free 3-D orientation estimation framework based on stereo-accelerometry and sensor fusion is proposed and validated. Afterward, a wearable device, MiCarp for robot-assisted interventional surgery was designed, prototyped, and investigated for the accuracy and real-time performance. To achieve the real-time performance, an artificial neural network was trained and implemented in the wearable device. The comparison of the results of the proposed method with a representative complementary filtering method showed the superior performance. The proposed method had a mean-absolute-error of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$1.7^\circ \pm 2.4^\circ$</tex-math></inline-formula> , a measurement range of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm 180^\circ$</tex-math></inline-formula> , and a real-time sample rate of up to 117 Hz. In the end, the feasibility of integrating the proposed device with a representative robotic intervention system was investigated. The proposed wearable device showed the capability of robust capturing of multiple successive rotations for an arterial cannulation task on a vascular model.