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: Column label Description ID identifier of the participant from 1 to 51 Age age of the participant in years Gender biological sex (M=male, F=female) Leg the participant's dominant leg, identified by asking which foot the participant would use to kick a football (R=right, L=left) Height height of the participant in centimeters Invalid_trials list of invalid trials in the motion capture data, usually classified as such because the participant did not properly step on the middle force plate IAD inter-asis distance in millimeters; measured with a caliper from left to right anterior superior iliac spine Left_knee_width width of the left knee in millimeters; measured with a caliper from medial epicondyle to lateral epicondyle Right_knee_width same as above for the right knee Left_ankle_width width of the left ankle in millimeters; measured with a caliper from medial malleolus to lateral malleolus Right_ankle_width same as above for the right ankle Left_thigh_length length of the left leg in millimeters; measured with a measuring tape from the greater trochanter of of the left femur to the lateral epicondyle of the left femur Right_thigh_length same as above for the right thigh Left_shank_length length of the left shank in millimeters; measured with a measuring tape from the medial epicondyle of the femur to the medial malleolus of the tibia Right_shank_length same as above for the right shank Mass the participant's mass in kilograms; measured on a force plate just before the walking measurements ICD inter-condylar distance of the knee of the dominant leg in millimeters; measured from low-field MRI Left_knee_width_mocap distance between reflective motion capture markers on the medial and lateral epicondyles of the knee in millimeters; measured from a static standing trial; a value of -1 means the data is missing because the participant did not have those markers Right_knee_width_mocap same as above for the right knee 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): Marker name Location Torso1 manubrium of the sternum Torso2 acromion of the right shoulder Torso3 acromion of the left shoulder Torso4 7th cervical vertebra Pelvis1 to Pelvis4 rigid cluster strapped behind the pelvis RFemur1 to RFemur4 rigid cluster strapped laterally to the right thigh RFemur5 medial epicondyle of the knee of the right leg RFemur6 lateral epicondyle of the knee of the right leg RTibia1 to RTibia4 rigid cluster strapped laterally to the right shank RTibia5 medial malleolus of the right ankle RTibia6 lateral malleolus of the right ankle RFoot1 behind the heel RFoot2 1st distal phalanx RFoot3 4th proximal phalanx RFoot4 proximally/posteriorly on IMU on the metatarsals RFoot5 distally/anteriorly on IMU on the metatarsals 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

The collection of this dataset involved research projects that received funding from the Research Council of Finland (grants 324994, 328920, 352666, 332915, 322423, 349469 and 334773 – under the frame of ERA PerMed), the Research Committee of the Kuopio University Hospital Catchment Area for the State Research Funding (grant 5654242), and the Sigrid Juselius Foundation (grants 230123, 230093).

The collection of this dataset was reviewed and approved by the University of Eastern Finland Committee on Research Ethics (statement no. 16/2022).