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Exploring wearable sensors as an alternative to marker-based motion capture in the pitching delivery

BACKGROUND: Improvements in data processing, increased understanding of the biomechanical background behind kinetics and kinematics, and technological advancements in inertial measurement unit (IMU) sensors have enabled high precision in the measurement of joint angles and acceleration on human subj...

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Autores principales: Boddy, Kyle J., Marsh, Joseph A., Caravan, Alex, Lindley, Kyle E., Scheffey, John O., O’Connell, Michael E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6348088/
https://www.ncbi.nlm.nih.gov/pubmed/30697497
http://dx.doi.org/10.7717/peerj.6365
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author Boddy, Kyle J.
Marsh, Joseph A.
Caravan, Alex
Lindley, Kyle E.
Scheffey, John O.
O’Connell, Michael E.
author_facet Boddy, Kyle J.
Marsh, Joseph A.
Caravan, Alex
Lindley, Kyle E.
Scheffey, John O.
O’Connell, Michael E.
author_sort Boddy, Kyle J.
collection PubMed
description BACKGROUND: Improvements in data processing, increased understanding of the biomechanical background behind kinetics and kinematics, and technological advancements in inertial measurement unit (IMU) sensors have enabled high precision in the measurement of joint angles and acceleration on human subjects. This has resulted in new devices that reportedly measure joint angles, arm speed, and stresses to the pitching arms of baseball players. This study seeks to validate one such sensor, the MotusBASEBALL unit, with a marker-based motion capture laboratory. HYPOTHESIS: We hypothesize that the joint angle measurements (“arm slot” and “shoulder rotation”) of the MotusBASEBALL device will hold a statistically significant level of reliability and accuracy, but that the “arm speed” and “stress” metrics will not be accurate due to limitations in IMU technology. METHODS: A total of 10 healthy subjects threw five to seven fastballs followed by five to seven breaking pitches (slider or curveball) in the motion capture lab. Subjects wore retroreflective markers and the MotusBASEBALL sensor simultaneously. RESULTS: It was found that the arm slot (R = 0.975, P < 0.001), shoulder rotation (R = 0.749, P < 0.001), and stress (R = 0.667, P = 0.001 when compared to elbow torque; R = 0.653, P = 0.002 when compared to shoulder torque) measurements were all significantly correlated with the results from the motion capture lab. Arm speed showed significant correlations to shoulder internal rotation speed (R = 0.668, P = 0.001) and shoulder velocity magnitude (R = 0.659, P = 0.002). For the entire sample, arm slot and shoulder rotation measurements were on a similar scale, or within 5–15% in absolute value, of magnitude to measurements from the motion capture test, averaging eight degrees less (12.9% relative differences) and nine degrees (5.4%) less, respectively. Arm speed had a much larger difference, averaging 3,745 deg/s (80.2%) lower than shoulder internal rotation velocity, and 3,891 deg/s (80.8%) less than the shoulder velocity magnitude. The stress metric was found to be 41 Newton meter (Nm; 38.7%) less when compared to elbow torque, and 42 Nm (39.3%) less when compared to shoulder torque. Despite the differences in magnitude, the correlations were extremely strong, indicating that the MotusBASEBALL sensor had high reliability for casual use. CONCLUSION: This study attempts to validate the use of the MotusBASEBALL for future studies that look at the arm slot, shoulder rotation, arm speed, and stress measurements from the MotusBASEBALL sensor. Excepting elbow extension velocity, all metrics from the MotusBASEBALL unit showed significant correlations to their corresponding metrics from motion capture and while some magnitudes differ substantially and therefore fall short in validity, the link between the metrics is strong enough to indicate reliable casual use. Further research should be done to further investigate the validity and reliability of the arm speed metric.
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spelling pubmed-63480882019-01-29 Exploring wearable sensors as an alternative to marker-based motion capture in the pitching delivery Boddy, Kyle J. Marsh, Joseph A. Caravan, Alex Lindley, Kyle E. Scheffey, John O. O’Connell, Michael E. PeerJ Anatomy and Physiology BACKGROUND: Improvements in data processing, increased understanding of the biomechanical background behind kinetics and kinematics, and technological advancements in inertial measurement unit (IMU) sensors have enabled high precision in the measurement of joint angles and acceleration on human subjects. This has resulted in new devices that reportedly measure joint angles, arm speed, and stresses to the pitching arms of baseball players. This study seeks to validate one such sensor, the MotusBASEBALL unit, with a marker-based motion capture laboratory. HYPOTHESIS: We hypothesize that the joint angle measurements (“arm slot” and “shoulder rotation”) of the MotusBASEBALL device will hold a statistically significant level of reliability and accuracy, but that the “arm speed” and “stress” metrics will not be accurate due to limitations in IMU technology. METHODS: A total of 10 healthy subjects threw five to seven fastballs followed by five to seven breaking pitches (slider or curveball) in the motion capture lab. Subjects wore retroreflective markers and the MotusBASEBALL sensor simultaneously. RESULTS: It was found that the arm slot (R = 0.975, P < 0.001), shoulder rotation (R = 0.749, P < 0.001), and stress (R = 0.667, P = 0.001 when compared to elbow torque; R = 0.653, P = 0.002 when compared to shoulder torque) measurements were all significantly correlated with the results from the motion capture lab. Arm speed showed significant correlations to shoulder internal rotation speed (R = 0.668, P = 0.001) and shoulder velocity magnitude (R = 0.659, P = 0.002). For the entire sample, arm slot and shoulder rotation measurements were on a similar scale, or within 5–15% in absolute value, of magnitude to measurements from the motion capture test, averaging eight degrees less (12.9% relative differences) and nine degrees (5.4%) less, respectively. Arm speed had a much larger difference, averaging 3,745 deg/s (80.2%) lower than shoulder internal rotation velocity, and 3,891 deg/s (80.8%) less than the shoulder velocity magnitude. The stress metric was found to be 41 Newton meter (Nm; 38.7%) less when compared to elbow torque, and 42 Nm (39.3%) less when compared to shoulder torque. Despite the differences in magnitude, the correlations were extremely strong, indicating that the MotusBASEBALL sensor had high reliability for casual use. CONCLUSION: This study attempts to validate the use of the MotusBASEBALL for future studies that look at the arm slot, shoulder rotation, arm speed, and stress measurements from the MotusBASEBALL sensor. Excepting elbow extension velocity, all metrics from the MotusBASEBALL unit showed significant correlations to their corresponding metrics from motion capture and while some magnitudes differ substantially and therefore fall short in validity, the link between the metrics is strong enough to indicate reliable casual use. Further research should be done to further investigate the validity and reliability of the arm speed metric. PeerJ Inc. 2019-01-24 /pmc/articles/PMC6348088/ /pubmed/30697497 http://dx.doi.org/10.7717/peerj.6365 Text en © 2019 Boddy et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Anatomy and Physiology
Boddy, Kyle J.
Marsh, Joseph A.
Caravan, Alex
Lindley, Kyle E.
Scheffey, John O.
O’Connell, Michael E.
Exploring wearable sensors as an alternative to marker-based motion capture in the pitching delivery
title Exploring wearable sensors as an alternative to marker-based motion capture in the pitching delivery
title_full Exploring wearable sensors as an alternative to marker-based motion capture in the pitching delivery
title_fullStr Exploring wearable sensors as an alternative to marker-based motion capture in the pitching delivery
title_full_unstemmed Exploring wearable sensors as an alternative to marker-based motion capture in the pitching delivery
title_short Exploring wearable sensors as an alternative to marker-based motion capture in the pitching delivery
title_sort exploring wearable sensors as an alternative to marker-based motion capture in the pitching delivery
topic Anatomy and Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6348088/
https://www.ncbi.nlm.nih.gov/pubmed/30697497
http://dx.doi.org/10.7717/peerj.6365
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