Ross Erin, Milian Anthony, Ferlic Mason, Reed Samuel, Lepley Adam S
School of Kinesiology, University of Michigan, Ann Arbor, Michigan, USA.
Video J Sports Med. 2022 Sep 13;2(5):26350254221102464. doi: 10.1177/26350254221102464. eCollection 2022 Sep-Oct.
Running is an extremely common exercise, both recreationally and competitively. Combined with clinical assessment, technology-driven biomechanical gait analysis can be used to examine markers of performance and injury risk in runners.
The indication is to provide clinicians and sports science researchers a framework for using inertial measurement units (IMU) for data-driven, quantitative gait assessments.
This video details practical application of IMU use in biomechanical gait assessments. Details on participant and equipment setup, in-session protocols, and selection of gait variables are included.
Following collection of demographic and anthropometric outcomes, IMUs should be placed on rigid segments of the lower extremity, sacrum, and trunk. In our model, we place IMUs on the foot, shank, thigh, sacrum, and lower thoracic spine. Following static anatomical calibration, running gait biomechanics are evaluated at multiple speeds using IMUs, 2-dimensional high-speed video cameras, and an instrumented treadmill. The high-speed video and IMU data are analyzed together at various parts of the gait cycle, including foot strike, mid-stance, toe-off, and flight. Many kinematic and kinetic variables (ie, unilateral discrete joint angles, joint excursions, joint moments, spatiotemporal outcomes, etc) can be selected for analysis, ideally via a collaboration between the sports science, athletic, and sports medicine teams. A collaborative approach should also be used to determine how this information will be used to alter training programs or influence injury risk in the running athlete.
DISCUSSION/CONCLUSION: This report details how to use a data-driven approach to evaluate running gait biomechanics using IMU technology. This framework for gait analysis is most applicable, and effective, when the team of researchers works in conjunction with coaches, sport scientists, and athletes. Utilizing this framework, training can be adapted based on the objective and clinical assessment to reduce injury risk and improve performance in the gait assessment.
跑步是一项极为常见的运动，无论是在休闲还是竞技领域。结合临床评估，技术驱动的生物力学步态分析可用于检查跑步者的运动表现指标和受伤风险。
其适应症是为临床医生和运动科学研究人员提供一个使用惯性测量单元（IMU）进行数据驱动的定量步态评估的框架。
本视频详细介绍了IMU在生物力学步态评估中的实际应用。包括参与者和设备设置、 session期间的协议以及步态变量的选择等细节。
在收集人口统计学和人体测量学结果后，应将IMU放置在下肢、骶骨和躯干的刚性节段上。在我们的模型中，我们将IMU放置在足部、小腿、大腿、骶骨和下胸椎上。经过静态解剖校准后，使用IMU、二维高速摄像机和仪器化跑步机在多个速度下评估跑步步态生物力学。在步态周期的各个部分，包括脚着地、支撑中期、脚尖离地和腾空阶段，对高速视频和IMU数据进行综合分析。理想情况下，通过运动科学、体育和运动医学团队之间的合作，可以选择许多运动学和动力学变量（即单侧离散关节角度、关节活动度、关节力矩、时空结果等）进行分析。还应采用合作方法来确定如何利用这些信息来改变训练计划或影响跑步运动员的受伤风险。
讨论/结论：本报告详细介绍了如何使用数据驱动的方法，利用IMU技术评估跑步步态生物力学。当研究团队与教练、运动科学家和运动员合作时，这个步态分析框架最为适用且有效。利用这个框架，可以根据客观和临床评估调整训练，以降低受伤风险并改善步态评估中的表现。
