Kuopio gait dataset: motion capture, inertial measurement and video-based sagittal-plane keypoint data from walking trials

This dataset contains motion capture (3D marker trajectories, ground reaction forces and moments), inertial measurement unit (wearable Movella Xsens MTw Awinda sensors on the pelvis, both thighs, both shanks, and both feet), and sagittal-plane video (anatomical keypoints identified with the OpenPose human pose estimation algorithm) data.
The data is from 51 willing participants and collected in the HUMEA laboratory in the University of Eastern Finland, Kuopio, Finland, between 2022 and 2023. All trials were conducted barefoot.

The file structure contains an Excel file containing information of the participants, data folders under each subject (numbered 01 to 51), and a MATLAB script.

The Excel file has the following data for the participants:

The folders under each subject (folders numbered 01 to 51) are as follows:

• imu: "Raw" inertial measurement unit (IMU) data files that can be read with Xsens Device API (included in Xsens MT Manager 4.6, which may be unavailable these days, not sure). You won't need this if you use the data in the imu_extracted folder.
• imu_extracted: IMU data extracted from those data files using the Xsens Device API, so you don't have to.
  • The data is saved as MATLAB structs where the fields are named as a sensor ID (e.g., "B42D48"). The sensor IDs and their corresponding IMU locations are as follows:
    • pelvis IMU: B42DA3
    • right femur IMU: B42DA2
    • left femur IMU: B42D4D
    • right tibia IMU: B42DAE
    • left tibia IMU: B42D53
    • right foot IMU: B42D48
    • left foot IMU: B42D51 (except for subjects 01 and 02, where left foot IMU has the ID B42D4E)
  • Some of the data are just zeros as they couldn't be read from these sensors, but under each sensor, the fields "calibratedAcceleration", "freeAcceleration", "time", "rotationMatrix", and "quaternion" contain usable data.
    • time: Contains time stamps of the measurement at each frame recorded at 100 Hz, so if you remove the first value from all values in the time vector and divide the result by 100, you will get the time in seconds from the beginning of the walking trial.
    • calibratedAcceleration and freeAcceleration: Contain triaxial acceleration data from the accelerometers of the IMU. freeAcceleration is just calibratedAcceleration without the effect of Earth's gravitational acceleration.
    • rotationMatrix: Orientations of the IMU as rotation matrices.
    • quaternion: Orientations of the IMU as quaternions.
• openpose: Trajectories of the keypoints identified from sagittal plane video frames, saved as json files.
  • The keypoints are from the BODY_25 model of OpenPose (https://cmu-perceptual-computing-lab.github.io/openpose/web/html/doc/md_doc_02_output.html).
  • Each frame in the video has its own json file.
  • You can use the function in the script "OpenPose_to_keypoint_table.m" in the root folder to read the keypoint trajectories and confidences of all frames in a walking trial into MATLAB tables. The function takes as argument the path to the folder containing the json files of the walking trial.
• mocap: Motion capture data (marker trajectories and force plate recordings) in C3D and Vicon Nexus compatible formats.
• Note that some subjects (11, 14, 37, 49) do not have keypoint and IMU data.

The folders under each subject are divided into three ZIP archives with 17 subjects each.

The script "OpenPose_to_keypoint_table.m" is a MATLAB script for extracting keypoint trajectories and confidences from JSON files into tables in MATLAB.

The marker trajectories of the motion capture data include the following markers (see notes below the table):

Notes:

• In the table above, only right leg markers are described; the left leg markers start with "L" instead of "R" and were placed symmetrically.
• During walking trials, medial knee markers (RFemur5 and LFemur5) were removed if they physically collided.
• Participant 1 wore an incomplete marker set.
• Participant 2 only had torso markers on the manubrium of the sternum and on the 7th cervical vertebra.
• The pelvis and thigh clusters were 3D printed, which allowed placing an IMU on the cluster and placing markers rigidly several centimeters away from the skin surface (see figure 6.5 of this dissertation).
• In some participants, the Torso4 marker was on the acromion of the left shoulder and the Torso3 marker on on the 7th cervical vertebra, instead of the other way around.
• In some participants, the second foot marker (e.g., RFoot2) was on the 4th proximal phalanx and the third foot marker (e.g., RFoot3) was on the 1st distal phalanx instead of the other way around.
• Automatic marker labeling may have misplaced other markers in some of the trials, so manual verification is recommended.

Publication in Data in Brief: https://doi.org/10.1016/j.dib.2024.110841

This data was also used in this paper and described in section 6.3 of this dissertation.

Contact: Jere Lavikainen, jere.lavikainen@uef.fi