Forearm Trajectory Measurement during Pitching Motion using an Elbow-mounted Sensor

Abstract

This paper describes a measurement method of three-dimensional (3D) forearm movement during pitching motion using an elbow-mounted sensor (3D sensor). The 3D sensor comprises accelerometers of two kinds with dynamic range of 4 [G] and 100 [G], and two kinds of gyroscopes with dynamic range of 300 [deg/s] and 4000 [deg/s], respectively, because the sensors used in measurement of sports activities require a wide dynamic range. The 3D sensor, attached on the forearm, measures 3D acceleration and angular velocity. The 3D trajectory of the forearm is estimated through double integration of the measured acceleration, which is transformed from the acceleration based on the system of moving coordinate on the forearm to that on the fixed system of coordinates. Because the estimated trajectory of the forearm is affected by the numerical integration of the measured data including errors, the 3D trajectory error is reduced by determining the position and posture of the forearm at the end of the pitching motion. Results of the pitching experiment show that the 3D trajectory and angle of the forearm estimated by the 3D sensor agree with those measured from a video camera image with an error margin of around 10 %.

Evaluation of wearable gyroscope and accelerometer sensor (PocketIMU2) during walking and sit-to-stand motions

“…Coefficient of correlation and root mean square error were calculated to evaluate the accuracy of the sensor. Different from previous study [5] [6], our sensor did not use any filters or make assumption about their posture during motion. Therefore it does not depend on a specific motion, or well organized environment.…”

“…Related to a gyroscope sensor, Sagawa, K. et al successfully recorded human pitching motion with modification of the recorded data by assuming the fixed start and end postures [5]. They could record very quick motion, but their assumption cannot be applicable to continuous daily motions.…”

Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review

“…Error can even become negligible when CoM global trajectories are used solely to support the interpretation of other estimated variables, as is done for external force estimates during ski racing [ 75 ]. Six possible approaches have been proposed to derive known reference positions: subtracting the linear trend line over the analysed time period from the Euler angles [ 41 ] assuming that the mean value is constant for cyclic events, to derive vertical CoM excursion from peak to peak values within each cycle (while running on a track [ 295 ] or on a treadmill [ 155 ]) defining a body model and measuring body segment orientation with respect to a reference to obtain vertical and horizontal CoM displacements (with respect to the skis at take-off during ski jumping [ 88 ], with respect to the ground during a golf swing [ 238 ] and with respect to a Global Navigation Satellite System (GNSS) antenna placed over the head during alpine skiing [ 122 ]) starting and ending the movement in known positions, to obtain shoulder, elbow and wrist [ 185 ], and solely elbow trajectories [ 267 ] during baseball pitching through data fusion with GPS based position estimates, which simultaneously compensates for short-term GPS outages (during outdoor activities such as snowboarding [ 333 ]) fusing the velocity of a root point (integral of a pelvic sensor acceleration) with the velocity estimated from the lower limb kinematics at ground contact [ 40 , 335 ]. …”

2D trajectory estimation during free walking using a tiptoe-mounted inertial sensor

“…where R( 1 ω, θ) is an equivalent rotation matrix that rotates E n by the angle θ around angular velocity vector 1 ω (Sagawa et al, 2009). …”