使用无标记运动捕捉系统进行运动分析评估的生物学可靠性。

IF 2.3 Q2 SPORT SCIENCES Frontiers in Sports and Active Living Pub Date : 2024-08-27 eCollection Date: 2024-01-01 DOI:10.3389/fspor.2024.1417965
Nicolas M Philipp, Andrew C Fry, Eric M Mosier, Dimitrije Cabarkapa, Justin X Nicoll, Stephanie A Sontag
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引用次数: 0

摘要

介绍:运动捕捉技术的进步包括无标记系统,以促进有效的数据收集。最近,有报道称这种技术在人体运动评估中的技术可靠性。为了进一步了解潜在误差的来源,还必须确定生物可靠性。本研究旨在确定三维无标记运动捕捉(MMC)系统量化 4 项运动分析综合评分和 81 个运动学变量的日常可靠性:22 名健康男性(n = 11;X ¯ ± SD;年龄 = 23.0 ± 2.6 岁,身高 = 180.4.8 厘米,体重 = 80.4 ± 7.3 千克)和女性(n = 11;年龄 = 20.8 ± 1.1 岁,身高 = 172.2 ± 7.4 厘米,体重 = 68.0 ± 7.3 千克)参加了此次研究。所有受试者分别在 4 天内进行了 4 组标准化测试,包括 14 个不同的动作。三维 MMC 系统(DARI Motion 公司,Lenexa, KS)使用围绕测试区域的 8 个摄像头来量化动作特征。使用 1 × 4 RMANOVAs 来确定综合运动分析得分在不同测试日之间的显著差异,使用 RM-MANOVAs 来确定运动学数据在不同测试日之间的差异(p 结果:没有观察到任何综合得分(即运动能力、爆发力、质量、准备状态)或 81 个运动学变量存在差异。此外,在 85 个测量变量中,有 84 个变量的 ICC 值为良好至优秀(0.61-0.99)。与之前报告的技术变异性数据相比,62.3%的项目变异性是由生物变异性引起的,85个变量中有66个变量的主要误差来源是生物变异性(即总变异性>50%):这些研究结果有效地补充了大量文献,表明 MMC 解决方案在捕捉人体运动的运动学特征方面具有足够的可靠性。
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Biological reliability of a movement analysis assessment using a markerless motion capture system.

Introduction: Advances in motion capture technology include markerless systems to facilitate valid data collection. Recently, the technological reliability of this technology has been reported for human movement assessments. To further understand sources of potential error, biological reliability must also be determined. The aim of this study was to determine the day-to-day reliability for a three-dimensional markerless motion capture (MMC) system to quantify 4 movement analysis composite scores, and 81 kinematic variables.

Methods: Twenty-two healthy men (n = 11; X ¯ ± SD ; age = 23.0 ± 2.6 years, height = 180.4.8 cm, weight = 80.4 ± 7.3 kg) and women (n = 11; age = 20.8 ± 1.1 years, height = 172.2 ± 7.4 cm, weight = 68.0 ± 7.3 kg) participated in this study. All subjects performed 4 standardized test batteries consisting of 14 different movements on four separate days. A three-dimensional MMC system (DARI Motion, Lenexa, KS) using 8 cameras surrounding the testing area was used to quantify movement characteristics. 1 × 4 RMANOVAs were used to determine significant differences across days for the composite movement analysis scores, and RM-MANOVAs were used to determine test day differences for the kinematic data (p < 0.05). Intraclass correlation coefficients (ICCs) were reported for all variables to determine test reliability. To determine biological variability, mean absolute differences from previously reported technological variability data were subtracted from the total variability data from the present study.

Results: No differences were observed for any composite score (i.e., athleticism, explosiveness, quality, readiness; or any of the 81 kinematic variables. Furthermore, 84 of 85 measured variables exhibited good to excellent ICCs (0.61-0.99). When compared to previously reported technological variability data, 62.3% of item variability was due to biological variability, with 66 of 85 variables exhibiting biological variability as the primary source of error (i.e., >50% total variability).

Discussion: Combined, these findings effectively add to the body of literature suggesting sufficient reliability for MMC solutions in capturing kinematic features of human movement.

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CiteScore
2.60
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7.40%
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459
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15 weeks
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