Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
Biomechanics Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
Sci Data. 2023 Mar 30;10(1):180. doi: 10.1038/s41597-023-02077-3.
Human motion capture and analysis could be made easier through the use of wearable devices such as inertial sensors and/or pressure insoles. However, many steps are still needed to reach the performance of optoelectronic systems to compute kinematic parameters. The proposed dataset has been established on 10 asymptomatic adults. Participants were asked to walk at different speeds on a 10-meters walkway in a laboratory and to perform different movements such as squats or knee flexion/extension tasks. Three-dimensional trajectories of 69 reflective markers placed according to a conventional full body markerset, acceleration and angular velocity signals of 8 inertial sensors, pressure signals of 2 insoles, 3D ground reaction forces and moments obtained from 3 force plates were simultaneously recorded. Eight calculated virtual markers related to joint centers were also added to the dataset. This dataset contains a total of 337 trials including static and dynamic tasks for each participant. Its purpose is to enable comparisons between various motion capture systems and stimulate the development of new methods for gait analysis.
通过使用惯性传感器和/或压力鞋垫等可穿戴设备,人体运动捕捉和分析可以变得更加容易。然而,要达到计算运动学参数的光电系统的性能,仍然需要许多步骤。该数据集是在 10 名无症状成年人的基础上建立的。参与者被要求在实验室的 10 米步行道上以不同的速度行走,并进行不同的运动,如深蹲或膝盖屈伸任务。根据传统的全身标记集放置的 69 个反射标记的三维轨迹、8 个惯性传感器的加速度和角速度信号、2 个鞋垫的压力信号、3 个力板获得的三维地面反作用力和力矩被同时记录。还向数据集添加了 8 个与关节中心相关的计算虚拟标记。该数据集共包含 337 次试验,包括每个参与者的静态和动态任务。其目的是能够比较各种运动捕捉系统,并刺激新的步态分析方法的发展。