Characterization of Human Gait by Means of the Trajectory of the Instantaneous Centers of Rotation of Lower Limb Segments in the Sagittal Plane

• Published in: IEEE access Vol. 13; pp. 27438 - 27448
• Main Authors: Iwaniec, Marek, Arias, Ludwin Molina, Iwaniec, Joanna
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Asymptotic methods; Asymptotic properties; Biomechanical engineering; Biomechanics; Cameras; Data acquisition; Diseases; Gait; Gait analysis; Gait recognition; Human motion; Image processing; instantaneous center of rotation; Kinematics; Knee; Legged locomotion; Limbs; motion analysis; Motion capture; Motion segmentation; Pattern analysis; Position measurement; Rotation; Segments; Software; Structural analysis; time-series analysis; Trajectory; Video
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2025.3539452

Gait analysis in the clinical context is essential for identifying structural and functional limitations in individuals. By examining the spatial and temporal characteristics of a subject's gait and comparing them to reference values, clinicians can gather valuable insights that aid in diagnosing diseases, developing treatment plans, and evaluating their efficacy. While much of the existing research on kinematic gait-related data has focused primarily on joint motion, other measures, such as the trajectories of the instantaneous center of rotation (ICR), remain underexplored. This paper investigates the potential of ICR trajectories of the lower limb segments as a biomechanical measure for assessing human gait. To achieve this, gait trials were conducted with subjects walking both overground and on a treadmill using a wearable inertial motion capture system, while sports cameras recorded motion in the sagittal plane. Kinematic data were acquired through video processing with the open-source tool Kinovea and directly via Xsens Analyze software. The positions of the ICRs of the lower limb segments in the sagittal plane were calculated for each time sample, and the determined trajectories were analyzed in time, frequency, and state space. The results indicate that the ICR trajectories of the shank exhibit a characteristic pattern, suggesting their potential use in gait analysis. Despite challenges posed by the asymptotic behavior of the studied signals and numerical errors related to the methods used, this study highlights the considerable potential of using ICR trajectories to enhance our understanding of human gait.