The COMPWALK-ACL: A Dataset of Multi-pace IMU Gait Kinematics in Adolescents, Adults, and ACL Injured Patients

Gait analysis provides objective, quantitative parameters essential for assessing mobility, identifying movement impairments, and monitoring the progress of rehabilitation. While traditional lab-based systems offer high accuracy, wearable Inertial Measurement Units (IMUs) enable portable, cost-effective gait assessments outside the laboratory environment. However, the reliability and applicability of IMU-derived data across diverse populations and walking conditions require robust datasets. This paper presents a lower limb kinematic dataset acquired with the Xsens Awinda IMU system. Data were collected from 92 unique participants: healthy adults (n = 25), healthy adolescents (n = 27), and individuals with ACL injuries assessed before surgery (n = 40), with 27 completing a follow-up three months post-reconstruction. Participants walked overground at self-selected slow, normal, and fast speeds. The dataset contains spatiotemporal parameters, as well as lower limb joint kinematics. It enables research on normative gait across age groups, the effects of ACL injury and early recovery on movement patterns, and the development of IMU-based gait analysis methods under different walking speeds and clinical conditions.