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

2019 ◽  
pp. 175433711987143
Author(s):  
Shohei Shibata ◽  
Kiyoshi Hirose ◽  
Takeshi Naruo ◽  
Yuichi Shimizu
Keyword(s):  
Kalman Filter ◽  
Root Mean Square ◽  
Sensor Fusion ◽  
Motion Capture ◽  
Time Integration ◽  
Three Dimensional ◽  
Forward Direction ◽  
Mean Square ◽  
Motion Capture System ◽  
Motion Characteristics

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.

A Low-Dimensional Dissimilarity Analysis of Unilateral and Bilateral Stroke-Impacted Hand Trajectories

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Jay Ryan U. Roldan ◽  
Dejan Milutinović ◽  
Zhi Li ◽  
Jacob Rosen
Keyword(s):  
Multidimensional Scaling ◽  
Healthy Subject ◽  
Motion Capture ◽  
Early Phase ◽  
Three Dimensional ◽  
High Rate ◽  
Motion Capture System ◽  
Trajectory Data ◽  
The Difference ◽  
Low Dimensional

In this paper, we propose a quantitative approach based on identifying hand trajectory dissimilarities through the use of a multidimensional scaling (MDS) analysis. A high-rate motion capture system is used to gather three-dimensional (3D) trajectory data of healthy and stroke-impacted hemiparetic subjects. The mutual dissimilarity between any two trajectories is measured by the area between them. This area is used as a dissimilarity variable to create an MDS map. The map reveals a structure for measuring the difference and variability of individual trajectories and their groups. The results suggest that the recovery of hemiparetic subjects can be quantified by comparing the difference and variability of their individual MDS map points to the points from the cluster of healthy subject trajectories. Within the MDS map, we can identify fully recovered patients, those who are only functionally recovered, and those who are either in an early phase of, or are nonresponsive to the therapy.

A Mobile Motion Capture System Based on Inertial Sensors and Smart Shoes

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Pyeong-Gook Jung ◽  
Sehoon Oh ◽  
Gukchan Lim ◽  
Kyoungchul Kong
Keyword(s):  
Motion Capture ◽  
Inertial Sensors ◽  
Kinematic Model ◽  
Three Dimensional ◽  
Health Condition ◽  
Body Motion ◽  
Whole Body ◽  
Motion Capture System ◽  
Outdoor Sports ◽  
Motion Capture Systems

Motion capture systems play an important role in health-care and sport-training systems. In particular, there exists a great demand on a mobile motion capture system that enables people to monitor their health condition and to practice sport postures anywhere at any time. The motion capture systems with infrared or vision cameras, however, require a special setting, which hinders their application to a mobile system. In this paper, a mobile three-dimensional motion capture system is developed based on inertial sensors and smart shoes. Sensor signals are measured and processed by a mobile computer; thus, the proposed system enables the analysis and diagnosis of postures during outdoor sports, as well as indoor activities. The measured signals are transformed into quaternion to avoid the Gimbal lock effect. In order to improve the precision of the proposed motion capture system in an open and outdoor space, a frequency-adaptive sensor fusion method and a kinematic model are utilized to construct the whole body motion in real-time. The reference point is continuously updated by smart shoes that measure the ground reaction forces.

The Study on Three-Dimensional Roughness of Machined Surface in High Speed Milling of SiCp/Al Composites

2011 ◽  
Vol 188 ◽  
pp. 179-183 ◽  
Author(s):  
Yang Jun Wang ◽  
M. Zhou ◽  
Y.H. Zhao
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
High Speed ◽  
Three Dimensional ◽  
Roughness Parameter ◽  
Cutting Parameters ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Machined Surface ◽  
High Speed Milling

For the purpose of investigating the effect on surface micro-topography of cutting parameters in high speed milling of SiCp/Al Composites, the high speed milling experiments were performed .The machined surface was measured by Taylor Hobson roughness tester and OLS3000 Confocal Laser Scanning Microscope. The acquired surface data was dealt with the three-dimensional roughness method. The three-dimensional root-mean-square deviation of the surface Sq and two-dimensional root-mean-square deviation Rq were compared. The effects of cutting parameters on three-dimensional roughness parameter were also investigated. The results showed that both feed rate and depth of cut have a little effect on the value of three-dimensional roughness parameter，and the cutting speed is the main affecting factor.

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