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      Concurrent validity of barbell force measured from video-based barbell kinematics during the snatch in male elite weightlifters

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      PLoS ONE
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          Abstract

          This study examined the concurrent validity of an inverse dynamic (force computed from barbell acceleration [reference method]) and a work-energy (force computed from work at the barbell [alternative method]) approach to measure the mean vertical barbell force during the snatch using kinematic data from video analysis. For this purpose, the acceleration phase of the snatch was analyzed in thirty male medal winners of the 2018 weightlifting World Championships (age: 25.2±3.1 years; body mass: 88.9±28.6 kg). Vertical barbell kinematics were measured using a custom-made 2D real-time video analysis software. Agreement between the two computational approaches was assessed using Bland-Altman analysis, Deming regression, and Pearson product-moment correlation. Further, principal component analysis in conjunction with multiple linear regression was used to assess whether individual differences related to the two approaches are due to the waveforms of the acceleration time-series data. Results indicated no mean difference ( p > 0.05; d = −0.04) and an extremely large correlation ( r = 0.99) between the two approaches. Despite the high agreement, the total error of individual differences was 8.2% (163.0 N). The individual differences can be explained by a multiple linear regression model (R 2 adj = 0.86) on principal component scores from the principal component analysis of vertical barbell acceleration time-series waveforms. Findings from this study indicate that the individual errors of force measures can be associated with the inverse dynamic approach. This approach uses vertical barbell acceleration data from video analysis that is prone to error. Therefore, it is recommended to use the work-energy approach to compute mean vertical barbell force as this approach did not rely on vertical barbell acceleration.

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          Progressive statistics for studies in sports medicine and exercise science.

          Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.
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            Spreadsheets for analysis of validity and reliability

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              A simple method for measuring force, velocity and power output during squat jump.

              Our aim was to clarify the relationship between power output and the different mechanical parameters influencing it during squat jumps, and to further use this relationship in a new computation method to evaluate power output in field conditions. Based on fundamental laws of mechanics, computations were developed to express force, velocity and power generated during one squat jump. This computation method was validated on eleven physically active men performing two maximal squat jumps. During each trial, mean force, velocity and power were calculated during push-off from both force plate measurements and the proposed computations. Differences between the two methods were not significant and lower than 3% for force, velocity and power. The validity of the computation method was also highlighted by Bland and Altman analyses and linear regressions close to the identity line (P<0.001). The low coefficients of variation between two trials demonstrated the acceptable reliability of the proposed method. The proposed computations confirmed, from a biomechanical analysis, the positive relationship between power output, body mass and jump height, hitherto only shown by means of regression-based equations. Further, these computations pointed out that power also depends on push-off vertical distance. The accuracy and reliability of the proposed theoretical computations were in line with those observed when using laboratory ergometers such as force plates. Consequently, the proposed method, solely based on three simple parameters (body mass, jump height and push-off distance), allows to accurately evaluate force, velocity and power developed by lower limbs extensor muscles during squat jumps in field conditions.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: MethodologyRole: ValidationRole: Writing – review & editing
                Role: MethodologyRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                19 July 2021
                2021
                : 16
                : 7
                Affiliations
                [1 ] Research Group Weightlifting, Institute for Applied Training Science, Leipzig, Germany
                [2 ] Division of Training and Movement Sciences, Research Focus Cognition Sciences, University of Potsdam, Potsdam, Germany
                Universita degli Studi di Milano, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Article
                PONE-D-21-03839
                10.1371/journal.pone.0254705
                8289080
                34280222
                003bed03-842b-4874-8a45-7e070b881606
                © 2021 Sandau et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 2, Tables: 2, Pages: 11
                Product
                Funding
                Funded by: german federal ministry of the interior, building and community
                Award Recipient :
                This study is part of the research project KT 1-17 at the Institute for Applied Training Science, Leipzig, Germany and was funded by the German Federal Ministry of the Interior, Building and Community. We acknowledge the support of the Deutsche Forschungsgemeinschaft and Open Access Publishing Fund of University of Potsdam.
                Categories
                Research Article
                Physical Sciences
                Physics
                Classical Mechanics
                Acceleration
                Physical Sciences
                Physics
                Classical Mechanics
                Motion
                Velocity
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Physical Sciences
                Physics
                Classical Mechanics
                Kinematics
                Physical Sciences
                Physics
                Classical Mechanics
                Motion
                Research and Analysis Methods
                Microscopy
                Electron Microscopy
                Scanning Electron Microscopy
                Computer and Information Sciences
                Software Engineering
                Computer Software
                Engineering and Technology
                Software Engineering
                Computer Software
                Custom metadata
                All relevant data are within the manuscript and its S1 and S2 Tables.

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