Hey! You! Are you interested in markerless motion capture in baseball? Have you played around with other markerless solutions, but felt that you couldn't trust the data? Worried that the data sucks ass? Well, look no further!
I'm proud to announce our new paper: the validation of pitchAITM markerless motion capture using marker-based 3D motion capture - the first single-camera markerless solution to be validated for use in baseball pitching.
Give it a read, and let me know your thoughts!
This study sought to compare and validate baseball pitching mechanics, including joint angles and spatiotemporal parameters, from a single camera markerless motion capture solution with a 3D optical marker-based system. Ten healthy pitchers threw 2–3 maximum effort fastballs while concurrently using marker-based optical capture and pitchAITM (markerless) motion capture. Time-series measures were compared using R-squared (r2), and root mean square error (RMSE). Discrete kinematic measures at foot plant, maximal shoulder external rotation, and ball release, plus four spatiotemporal parameters were evaluated using descriptive statistics, Bland-Altman analyses, Pearson’s correlation coefficients, p-values, r2, and RMSE. For time-series angles, r2 ranged from 0.69 (glove arm shoulder external rotation) to 0.98 (trunk and pelvis rotation), and RMSE ranged from 4.37° (trunk lateral tilt) to 20.78° (glove arm shoulder external rotation). Bias for individual joint angle and spatiotemporal parameters ranged from −11.31 (glove arm shoulder horizontal abduction; MER) to 12.01 (ball visible). RMSE was 3.62 m/s for arm speed, 5.75% height for stride length and 21.75 ms for the ball visible metric. pitchAITM can be recommended as a markerless alternative to marker-based motion capture for quantifying pitching kinematics. A database of pitchAITM ranges should be established for comparison between systems.
https://www.tandfonline.com/doi/full/10.1080/14763141.2022.2137425 (full article available here, or DM me on Twitter)