Templin Tylan, Riehm Christopher D, Eliason Travis, Hulburt Tessa C, Kwak Samuel T, Medjaouri Omar, Chambers David, Anand Manish, Saylor Kase, Myer Gregory D, Nicolella Daniel P
Southwest Research Institute, San Antonio, TX, United States.
Emory Sports Performance And Research Center (SPARC), Flowery Branch, GA, United States.
Front Bioeng Biotechnol. 2024 Oct 24;12:1426677. doi: 10.3389/fbioe.2024.1426677. eCollection 2024.
3D Markerless motion capture technologies have advanced significantly over the last few decades to overcome limitations of marker-based systems, which require significant cost, time, and specialization. As markerless motion capture technologies develop and mature, there is increasing demand from the biomechanics community to provide kinematic and kinetic data with similar levels of reliability and accuracy as current reference standard marker-based 3D motion capture methods. The purpose of this study was to evaluate how a novel markerless system trained with both hand-labeled and synthetic data compares to lower extremity kinematic and kinetic measurements from a reference marker-based system during the drop vertical jump (DVJ) task.
Synchronized video data from multiple camera views and marker-based data were simultaneously collected from 127 participants performing three repetitions of the DVJ. Lower limb joint angles and joint moments were calculated and compared between the markerless and marker-based systems. Root mean squared error values and Pearson correlation coefficients were used to quantify agreement between the systems.
Root mean squared error values of lower limb joint angles and joint moments were ≤ 9.61 degrees and ≤ 0.23 N×m/kg, respectively. Pearson correlation values between markered and markerless systems were 0.67-0.98 hip, 0.45-0.99 knee and 0.06-0.99 ankle for joint kinematics. Likewise, Pearson correlation values were 0.73-0.90 hip, 0.61-0.95 knee and 0.74-0.95 ankle for joint kinetics.
These results highlight the promising potential of markerless motion capture, particularly for measures of hip, knee and ankle rotations. Further research is needed to evaluate the viability of markerless ankle measures in the frontal plane to determine if differences in joint solvers are inducing unanticipated error.
在过去几十年中,无标记三维运动捕捉技术取得了显著进展,以克服基于标记的系统的局限性,后者需要高昂的成本、时间和专业知识。随着无标记运动捕捉技术的发展和成熟,生物力学界对提供与当前基于标记的三维运动捕捉参考标准具有相似可靠性和准确性水平的运动学和动力学数据的需求日益增加。本研究的目的是评估一种用手工标注数据和合成数据训练的新型无标记系统,与基于标记的参考系统在下落垂直跳(DVJ)任务期间的下肢运动学和动力学测量相比如何。
从127名进行三次DVJ重复的参与者中同时收集多个摄像机视角的同步视频数据和基于标记的数据。计算并比较无标记系统和基于标记的系统之间的下肢关节角度和关节力矩。均方根误差值和皮尔逊相关系数用于量化系统之间的一致性。
下肢关节角度和关节力矩的均方根误差值分别≤9.61度和≤0.23N·m/kg。对于关节运动学,基于标记和无标记系统之间的皮尔逊相关值在髋关节为0.67 - 0.98,膝关节为0.45 - 0.99,踝关节为0.06 - 0.99。同样,对于关节动力学,皮尔逊相关值在髋关节为0.73 - 0.90,膝关节为0.61 - 0.95,踝关节为0.74 - 0.95。
这些结果突出了无标记运动捕捉的潜在前景,特别是对于髋关节、膝关节和踝关节旋转的测量。需要进一步研究来评估无标记踝关节测量在额面的可行性,以确定关节求解器的差异是否会导致意外误差。