Mary C Geneau, David L Carey, Paul B Gastin, Sam Robertson, Lachlan P James
{"title":"将力-时间指标分类到下肢力量领域。","authors":"Mary C Geneau, David L Carey, Paul B Gastin, Sam Robertson, Lachlan P James","doi":"10.1519/JSC.0000000000004855","DOIUrl":null,"url":null,"abstract":"<p><strong>Abstract: </strong>Geneau, MC, Carey, DL, Gastin, PB, Robertson, S, and James, LP. Classification of force-time metrics into lower-body strength domains. J Strength Cond Res 38(9): 1561-1567, 2024-The purpose of this study was to classify force-time metrics into distinct lower-body strength domains using a systematic data reduction analysis. A cross-sectional design was used, whereby competitive field sport athletes ( F = 39, M = 96) completed a series of drop jumps, squat jumps, countermovement jumps (CMJs), loaded CMJs, and 2 isometric tasks on portable force platforms, resulting in a total of 285 force-time performance metrics. The metrics were split into 4 test \"families\" and each was entered into a sparse principal component analysis (sPCA) model. A single metric from each component of each family-specific sPCA were selected based on the loading, reliability, and simplicity of the metric and entered into a second sPCA that included metrics across all tests. The final sPCA revealed 7 principal components each containing 2 metrics and explained a total of 53% variance of the dataset. The final principal components were interpreted as 7 lower-body strength domains: (a) dynamic force, (b) dynamic timing, (c) early isometric, (d) maximal isometric, (e) countermovement velocity, (f) reactive output, and (g) reactive timing. The findings demonstrate that a total of 7 metrics from a drop jump, CMJ, and isometric test can be used to represent ∼50% of variance in lower-body strength performance of field sport athletes. These results can help guide and simplify the lower-body strength diagnosis process in field sport athletes.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":" ","pages":"1561-1567"},"PeriodicalIF":4.6000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Classification of Force-Time Metrics Into Lower-Body Strength Domains.\",\"authors\":\"Mary C Geneau, David L Carey, Paul B Gastin, Sam Robertson, Lachlan P James\",\"doi\":\"10.1519/JSC.0000000000004855\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Abstract: </strong>Geneau, MC, Carey, DL, Gastin, PB, Robertson, S, and James, LP. Classification of force-time metrics into lower-body strength domains. J Strength Cond Res 38(9): 1561-1567, 2024-The purpose of this study was to classify force-time metrics into distinct lower-body strength domains using a systematic data reduction analysis. A cross-sectional design was used, whereby competitive field sport athletes ( F = 39, M = 96) completed a series of drop jumps, squat jumps, countermovement jumps (CMJs), loaded CMJs, and 2 isometric tasks on portable force platforms, resulting in a total of 285 force-time performance metrics. The metrics were split into 4 test \\\"families\\\" and each was entered into a sparse principal component analysis (sPCA) model. A single metric from each component of each family-specific sPCA were selected based on the loading, reliability, and simplicity of the metric and entered into a second sPCA that included metrics across all tests. The final sPCA revealed 7 principal components each containing 2 metrics and explained a total of 53% variance of the dataset. The final principal components were interpreted as 7 lower-body strength domains: (a) dynamic force, (b) dynamic timing, (c) early isometric, (d) maximal isometric, (e) countermovement velocity, (f) reactive output, and (g) reactive timing. The findings demonstrate that a total of 7 metrics from a drop jump, CMJ, and isometric test can be used to represent ∼50% of variance in lower-body strength performance of field sport athletes. These results can help guide and simplify the lower-body strength diagnosis process in field sport athletes.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":\" \",\"pages\":\"1561-1567\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1519/JSC.0000000000004855\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/9 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1519/JSC.0000000000004855","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/9 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Classification of Force-Time Metrics Into Lower-Body Strength Domains.
Abstract: Geneau, MC, Carey, DL, Gastin, PB, Robertson, S, and James, LP. Classification of force-time metrics into lower-body strength domains. J Strength Cond Res 38(9): 1561-1567, 2024-The purpose of this study was to classify force-time metrics into distinct lower-body strength domains using a systematic data reduction analysis. A cross-sectional design was used, whereby competitive field sport athletes ( F = 39, M = 96) completed a series of drop jumps, squat jumps, countermovement jumps (CMJs), loaded CMJs, and 2 isometric tasks on portable force platforms, resulting in a total of 285 force-time performance metrics. The metrics were split into 4 test "families" and each was entered into a sparse principal component analysis (sPCA) model. A single metric from each component of each family-specific sPCA were selected based on the loading, reliability, and simplicity of the metric and entered into a second sPCA that included metrics across all tests. The final sPCA revealed 7 principal components each containing 2 metrics and explained a total of 53% variance of the dataset. The final principal components were interpreted as 7 lower-body strength domains: (a) dynamic force, (b) dynamic timing, (c) early isometric, (d) maximal isometric, (e) countermovement velocity, (f) reactive output, and (g) reactive timing. The findings demonstrate that a total of 7 metrics from a drop jump, CMJ, and isometric test can be used to represent ∼50% of variance in lower-body strength performance of field sport athletes. These results can help guide and simplify the lower-body strength diagnosis process in field sport athletes.