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  • Title: Investigation of intersegmental coordination patterns in human walking.
    Author: Varma V, Trkov M.
    Journal: Gait Posture; 2024 Jul; 112():88-94. PubMed ID: 38749294.
    Abstract:
    BACKGROUND: Intersegmental coordination between thigh, shank, and foot plays a crucial role in human gait, facilitating stable and efficient human walking. Limb elevation angles during the gait cycle form a planar manifold describes the by the planar covariation law, a recognized fundamental aspect of human locomotion. RESEARCH QUESTION: How does the walking speed, age, BMI, and height, affect the size and orientation of the intersegmental coordination manifold and covariation plane? METHODS: This study introduces novel metrics for quantifying intersegmental coordination, including the mean radius of the manifold, rotation of the manifold about the origin, and the orientation of the plane with respect to the coordinate planes. A statistical investigation is conducted on a publicly available human walking dataset for subjects aged 19-67 years, walking at speeds between 0.18 and 2.3 m s-1 to determine correlations of the proposed quantities. We used two sample t-test and ANOVA to find statistical significance of changes in the metrics with respect to gender and walking speed, respectively. Regression analysis was used to establish relationships between the introduced metrics and walking speed. RESULTS: High correlations are observed between walking speed and the computed metrics, highlighting the sensitivity of these metrics to gait characteristics. Conversely, negligible correlations are found for demographic parameters like age, body mass index (BMI), and height. Male and female groups exhibit no practically significant differences in any of the considered metrics. Additionally, metrics tend to increase in magnitude as walking speed increases. SIGNIFICANCE: This study contributes numerical metrics to characterize ISC of lower limbs with respect to walking speed along with regression models to estimate these metrics and related kinematic quantities. These findings hold significance for enhancing clinical gait analysis, generating optimal walking trajectories for assistive devices, prosthetics, or rehabilitation, aiming to replicate natural gaits and improve the functionality of biomechanical devices.
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