Research On Sensing Technology Of Handheld Instrument To Cancel Physiological Tremor

Humans have intrinsic limitations in manual positioning accuracy. These limitations areconsequences of small involuntary movements that are inherent in normal hand motion.Theinherent，involuntary，roughly sinusoidal movement is called physiological tremor.Duringmicrosurgery or cell manipulation bio-tech industry，the most familiar type of erroneousmovement affecting operators is physiological tremor. Not only that it complicates manyprecise micromanipulation procedures，it also makes certain types of intervention impossible.Based on the characteristics of the physiological tremor and requirements the handheldinstrument，a high accuracy measurement system for physiological tremor of the handheldtool is adopted. Motion of the instrument is sensed by a new magnetometer-aidedall-accelerometer inertial measurement unit (IMU). The sensing system consists of threedual-axis miniature accelerometers and a three-axis magnetometer. On the one side，theangular motion information derived from the differential sensing kinematics algorithm hasvery high sensing resolution but suffers from integration drift; on the other hand， theorientation obtained from the gravity and magnetic North vectors is noisy but non-drifting.These two complementary sensing sources are fused via an augmented state quaternion-basedKalman filter to yield high quality sensing. A complementary quaternion-based Kalman filteris researched and the accelerometer and magnetometer sensor information are fused by thealgorithm to improve the precision.In this paper，the measurement unit for tracking the handheld tool is designed anddemonstrates the superiority of this design by comparing the error variance to that of aconventional IMU design; Then analyze the error sources of the IMU and obtain the errormodel for the accelerometer and magnetometer measurement error and installation error，study sensor calibration method for deterministic errors and correct it. Compute the bodyangular velocity from the accelerometer outputs，reference the methods in the inertialmeasurement for attitude matrix updating and retrieve the complete six degrees of freedommotion information of the instrument. The gravity is combined with the non-driftingNorth-seeking information via TRIAD algorithms to provide the direction cosine matrixirelated to the measurement vector.Based on the body angular velocity vector and the direction cosine matrix，design an augmented state quaternion-based Kalman filter to fusethem and botain an orientation estimate. Finaly，the acceleration information is fused andintegrated twice to obtain the position of the body frame and the tool-tip position is calculatedby simple motion kinematics. Finally，WFLC is used to get the physiological tremor of thehand-held the tool-tip position and the estimation tremor.