A-22 A study on the estimation method of baseball bat trajectory in practice swing motion using the extended Kalman filter

Shibata, Shohei; Hirose, Kiyoshi; Naruo, Takeshi; Shimizu, Yuichi

doi:10.1299/jsmeshd.2015._a-22-1_

Cited by 1 publication

(2 citation statements)

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“…Shibata et al 8 developed an algorithm to analyze the baseball swing trajectory. This algorithm involved determining the initial attitude, estimating the 3D posture using an extended Kalman filter (EKF), compensating for the error in the azimuth angle, and estimating the bat trajectory.…”

Section: Methodsmentioning

confidence: 99%

“…To this end, the authors previously developed an algorithm that could compensate for the integration error and estimate the baseball bat trajectory during practice swing motion. 8 However, in that study, the analysis period was from the swing beginning to the instant of maximum swing velocity. Thus, baseball bat trajectory to the follow-through phase was not estimated.…”

Section: Introductionmentioning

confidence: 91%

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Estimation of baseball bat trajectory during a practice swing using a Kalman filter for velocity compensation

Shibata¹,

Hirose²,

Naruo³

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part P:

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This study aimed to (a) develop an algorithm that could estimate a baseball bat trajectory from the beginning of the swing to the follow-through phase during a practice swing without a ball and (b) evaluate the accuracy of the proposed method using a three-dimensional motion capture system. The sensor fusion using the adaptive Kalman filter for compensating velocity decreased the error of acceleration integration during the follow-through phase. Further, the three-dimensional bat trajectory in a global coordinate was estimated by combining the sensor fusion and compensation by motion characteristics. The three-dimensional bat trajectory from the swing beginning to the follow-through phase estimated by the proposed method was compared with the three-dimensional bat trajectory obtained by the three-dimensional motion capture system. The proposed method achieved a root mean square of the error of 7.72 km/h for velocity, which was less than the root mean square of the error (8.91 km/h) obtained by simple time integration of forward direction. These results indicate that the error by acceleration integration during the follow-through phase is compensated. The proposed method is, thus, deemed effective and can be used to evaluate baseball swing, including the follow-through phase, with high accuracy.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 91%