遇见数据集

Bipedal Gait Dataset with Motion Capture and IMU Data in Circular Walking Paths

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Zenodo2025-07-14 更新2026-05-26 收录
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Dataset Description This dataset comprises gait recordings collected in a controlled laboratory environment using dual motion capture technology: an optical system and inertial sensors. The main goal of the study was to evaluate spatial gait parameters and support the development and validation of algorithms for biomechanical analysis. Motion Capture Systems Optical System: Move Human MoCap The optical motion capture system used was the Move Human (MH) Sensors MoCap, developed by the IDERGO research group. It includes: 15 custom 3D-printed rigid bodies (RBs) with reflective markers 12 OptiTrack Flex 13 cameras, managed via Motive software Each RB has a unique geometry that enables automatic identification. The system captures marker positions at a frequency of 120 Hz, allowing for full-body kinematics reconstruction during walking. The data are stored in .csv format, with headers containing over 100 variables, including: Orientations: Rx, Ry, Rz Positions: X, Y, Z Internal and relative rotations: Ri, Ra Segmented body structures: Pelvis, spine, shoulders, arms, hips, knees, and feet (left and right sides) Inertial System: SmartInsole IMUs The inertial dataset contains recordings from six-axis IMUs, combining triaxial accelerometers and gyroscopes, embedded in portable devices worn on the outer side of each shoe. Each file is sampled at 50 Hz and includes: timestamp: Sample time sensor_id: Sensor identifier foot: Foot side (left/right) seq: Acquisition sequence number acx, acy, acz: Acceleration values along each axis gyrx, gyry, gyrz: Angular velocity values roll, pitch, yaw: Calculated angular orientations p_...: Plantar pressure data (note: not used due to reliability issues) Each row in the CSV contains 21 float32 numerical columns. Experimental Protocol Participants walked continuously in a circular path in the laboratory, a design that avoids stops and sharp turns, allowing for uninterrupted, stable recordings by both systems. The protocol consisted of four trials, varying in walking speed and trajectory direction, to capture intra-subject variability and test algorithm robustness: Trial 1 – Fast walking, counterclockwise Trial 2 – Fast walking, clockwise Trial 3 – Slow walking, counterclockwise Trial 4 – Slow walking, clockwise This configuration allows for analysis of the effects of rhythm and directionality on gait and supports stability validation of gait parameter estimation. Each session includes at least 25 strides per participant and per trial, exceeding commonly accepted thresholds for statistical reliability in gait analysis. All participants wore the same flat, comfortable shoes to minimize variability from footwear. Participants The study included 26 adult participants, recruited through internal calls and the research team’s network. Inclusion criteria were: No musculoskeletal or neurological conditions Ability to walk independently without assistance Signed informed consent in accordance with ethics committee protocols Data Organization and File Structure The data generated in this project are organized hierarchically and consistently, following a folder structure that reflects the type of sensor, the type of test, and the walking conditions. There are two main branches: IDERGO data Subdivided into four folders according to the corresponding trial, e.g., Trial 1 – Fast walking – Counterclockwise direction. Each file is named with the date and time of capture, the participant ID, and the suffix _Motion.csv. Example: 2022-04-05_10.29_HW001o_Motion.csv SmartInsole data Also organized by trial (e.g., Trial 1 – Fast walking – Counterclockwise direction) The files are shorter but still identifiable by participant code: Example: HW_01.csv

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Zenodo
创建时间:
2025-07-09
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