Automatic detection of pitching and throwing events in baseball with inertial measurement sensors
Journal article
Murray, Nick B., Black, Georgia M., Whiteley, Rod J., Gahan, Peter, Cole, Michael H., Utting, Andy and Gabbett, Tim J.. (2017). Automatic detection of pitching and throwing events in baseball with inertial measurement sensors. International Journal of Sports Physiology and Performance. 12(4), pp. 533-537. https://doi.org/10.1123/ijspp.2016-0212
Authors | Murray, Nick B., Black, Georgia M., Whiteley, Rod J., Gahan, Peter, Cole, Michael H., Utting, Andy and Gabbett, Tim J. |
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Abstract | Purpose: Throwing loads are known to be closely related to injury risk. However, for logistic reasons, typically only pitchers have their throws counted, and then only during innings. Accordingly, all other throws made are not counted, so estimates of throws made by players may be inaccurately recorded and underreported. A potential solution to this is the use of wearable microtechnology to automatically detect, quantify, and report pitch counts in baseball. This study investigated the accuracy of detection of baseball pitching and throwing in both practice and competition using a commercially available wearable microtechnology unit. Methods: Seventeen elite youth baseball players (mean ± SD age 16.5 ± 0.8 y, height 184.1 ± 5.5 cm, mass 78.3 ± 7.7 kg) participated in this study. Participants performed pitching, fielding, and throwing during practice and competition while wearing a microtechnology unit. Sensitivity and specificity of a pitching and throwing algorithm were determined by comparing automatic measures (ie, microtechnology unit) with direct measures (ie, manually recorded pitching counts). Results: The pitching and throwing algorithm was sensitive during both practice (100%) and competition (100%). Specificity was poorer during both practice (79.8%) and competition (74.4%). Conclusions: These findings demonstrate that the microtechnology unit is sensitive to detect pitching and throwing events, but further development of the pitching algorithm is required to accurately and consistently quantify throwing loads using microtechnology. |
Keywords | GPS; training; competition; workload monitoring |
Year | 2017 |
Journal | International Journal of Sports Physiology and Performance |
Journal citation | 12 (4), pp. 533-537 |
Publisher | Human Kinetics, Inc. |
ISSN | 1555-0265 |
Digital Object Identifier (DOI) | https://doi.org/10.1123/ijspp.2016-0212 |
Scopus EID | 2-s2.0-85023605442 |
Open access | Published as green open access |
Page range | 533-537 |
Research Group | Sports Performance, Recovery, Injury and New Technologies (SPRINT) Research Centre |
Author's accepted manuscript | License All rights reserved File Access Level Open |
Publisher's version | License All rights reserved File Access Level Controlled |
Output status | Published |
Publication dates | |
Online | 2017 |
https://acuresearchbank.acu.edu.au/item/8991w/automatic-detection-of-pitching-and-throwing-events-in-baseball-with-inertial-measurement-sensors
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Author's accepted manuscript
AM_Murray_2017_Automatic_detection_of_pitching_and_throwing.pdf | |
License: All rights reserved | |
File access level: Open |
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