Lavikainen Jere, Vartiainen Paavo, Stenroth Lauri, Karjalainen Pasi A, Korhonen Rami K, Liukkonen Mimmi K, Mononen Mika E
Department of Technical Physics, University of Eastern Finland, P.O. Box 1627, Yliopistonranta 8 (Melania building), 70211 Kuopio, Finland.
Diagnostic Imaging Centre, Kuopio University Hospital, Wellbeing Services County of North Savo, Puijonlaaksontie 2, 70210 Kuopio, Finland.
Data Brief. 2024 Aug 14;56:110841. doi: 10.1016/j.dib.2024.110841. eCollection 2024 Oct.
We present a dataset comprising motion capture, inertial measurement unit data, and sagittal-plane video data from walking at three different instructed speeds (slow, comfortable, fast). The dataset contains 51 healthy participants with approximately 60 walking trials from each participant. Each walking trial contains data from motion capture, inertial measurement units, and computer vision. Motion capture data comprises ground reaction forces and moments from floor-embedded force plates and the 3D trajectories of subject-worn motion capture markers. Inertial measurement unit data comprises 3D accelerometer readings and 3D orientations from the lower limbs and pelvis. Computer vision data comprises 2D keypoint trajectories detected using the OpenPose human pose estimation algorithm from sagittal-plane video of the walking trial. Additionally, the dataset contains participant demographic and anthropometric information such as mass, height, sex, age, lower limb dimensions, and knee intercondylar distance measured from magnetic resonance images. The dataset can be used in musculoskeletal modelling and simulation to calculate kinematics and kinetics of motion and to compare data between motion capture, inertial measurement, and video capture.
我们展示了一个数据集，它包含运动捕捉、惯性测量单元数据以及在三种不同指令速度（慢、舒适、快）下行走的矢状面视频数据。该数据集有51名健康参与者，每位参与者大约有60次行走试验。每次行走试验都包含来自运动捕捉、惯性测量单元和计算机视觉的数据。运动捕捉数据包括来自地面嵌入式测力板的地面反作用力和力矩，以及受试者佩戴的运动捕捉标记的三维轨迹。惯性测量单元数据包括来自下肢和骨盆的三维加速度计读数和三维方向。计算机视觉数据包括使用OpenPose人体姿态估计算法从行走试验的矢状面视频中检测到的二维关键点轨迹。此外，该数据集还包含参与者的人口统计学和人体测量学信息，如体重、身高、性别、年龄、下肢尺寸以及从磁共振图像测量的膝关节髁间距离。该数据集可用于肌肉骨骼建模和模拟，以计算运动的运动学和动力学，并比较运动捕捉、惯性测量和视频捕捉之间的数据。
