Department of Computer and Information Sciences, Northumbria University, Newcastle-upon-Tyne NE1 8ST, UK.
Department of Health and Life Sciences, Northumbria University, Newcastle-upon-Tyne NE1 8ST, UK.
Sensors (Basel). 2023 Jan 7;23(2):696. doi: 10.3390/s23020696.
Running gait assessment is essential for the development of technical optimization strategies as well as to inform injury prevention and rehabilitation. Currently, running gait assessment relies on (i) visual assessment, exhibiting subjectivity and limited reliability, or (ii) use of instrumented approaches, which often carry high costs and can be intrusive due to the attachment of equipment to the body. Here, the use of an IoT-enabled markerless computer vision smartphone application based upon Google’s pose estimation model BlazePose was evaluated for running gait assessment for use in low-resource settings. That human pose estimation architecture was used to extract contact time, swing time, step time, knee flexion angle, and foot strike location from a large cohort of runners. The gold-standard Vicon 3D motion capture system was used as a reference. The proposed approach performs robustly, demonstrating good (ICC(2,1) > 0.75) to excellent (ICC(2,1) > 0.90) agreement in all running gait outcomes. Additionally, temporal outcomes exhibit low mean error (0.01−0.014 s) in left foot outcomes. However, there are some discrepancies in right foot outcomes, due to occlusion. This study demonstrates that the proposed low-cost and markerless system provides accurate running gait assessment outcomes. The approach may help routine running gait assessment in low-resource environments.
跑步步态评估对于制定技术优化策略以及为预防和康复损伤提供信息至关重要。目前，跑步步态评估依赖于（i）视觉评估，具有主观性和有限的可靠性，或（ii）使用仪器化方法，这些方法通常成本高昂，并且由于设备附在身体上而具有侵入性。在这里，评估了一种基于 Google 的姿态估计模型 BlazePose 的物联网支持的无标记计算机视觉智能手机应用程序，用于在资源有限的环境中进行跑步步态评估。该人体姿态估计架构用于从大量跑步者中提取接触时间、摆动时间、步幅时间、膝关节弯曲角度和脚着地位置。黄金标准的 Vicon 3D 运动捕捉系统被用作参考。所提出的方法表现稳健，在所有跑步步态结果中均表现出良好（ICC(2,1) > 0.75）到优秀（ICC(2,1) > 0.90）的一致性。此外，在左脚结果中，时间结果的平均误差较低（0.01-0.014 s）。然而，右脚结果存在一些差异，这是由于遮挡造成的。本研究表明，所提出的低成本无标记系统提供了准确的跑步步态评估结果。该方法可能有助于在资源有限的环境中进行常规跑步步态评估。
