When walking over stable, complex terrain, visual information about an upcoming foothold is primarily utilized during the preceding step to organize a nearly ballistic forward movement of the body. However, it is often necessary to respond to changes in the position of an intended foothold that occur around step initiation. Although humans are capable of rapidly adjusting foot trajectory mid-swing in response to a perturbation of target position, such movements may disrupt the efficiency and stability of the gait cycle. In the present study, we consider whether walkers sometimes adopt alternative strategies for responding to perturbations that interfere less with ongoing forward locomotion. Subjects walked along a path of irregularly spaced stepping targets projected onto the ground, while their movements were recorded by a full-body motion-capture system. On a subset of trials, the location of one target was perturbed in either a medial-lateral or anterior-posterior direction. We found that subjects were best able to respond to perturbations that occurred during the latter half of the preceding step and that responses to perturbations that occurred during a step were less successful than previously reported in studies using a single-step paradigm. We also found that, when possible, subjects adjusted the ballistic movement of their center of mass in response to perturbations. We conclude that, during continuous walking, strategies for responding to perturbations that rely on reach-like movements of the foot may be less effective than previously assumed. For perturbations that are detected around step initiation, walkers prefer to adapt by tailoring the global, pendular mechanics of the body.
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http://dx.doi.org/10.1007/s00221-019-05538-7 | DOI Listing |
Digit Biomark
December 2024
VivoSense, Inc., Newport Coast, CA, USA.
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College of Sport and Health Science, Ritsumeikan University, Shiga, Japan.
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View Article and Find Full Text PDFBiomedicines
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Department of Management Information Systems, Keimyung University, Daegu 42601, Republic of Korea.
: Diabetes is a dangerous disease that is accompanied by various complications, including cardiovascular disease. As the global diabetes population continues to increase, it is crucial to identify its causes. Therefore, we predicted diabetes using an AI model and quantitatively examined causal relationships using a causal discovery and inference model.
View Article and Find Full Text PDFHealthcare (Basel)
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Department of Family and Community Medicine, College of Medicine, Qassim University, Buraydah 52571, Saudi Arabia.
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View Article and Find Full Text PDFSci Data
January 2025
Division of Biomechanics and Research Development, Department of Biomechanics, and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, NE, 68182, USA.
The continued effort to study gait kinematics and the increased interest in identifying individuals based on their gait patterns could be strengthened by the inclusion of data from older groups. To address this need and complement our previous database on healthy young adults, we present an addition to the Nonlinear Analysis Core (NONAN) GaitPrint database. We offer full-body inertial measurement data during self-paced overground walking on a 200 m indoor track of 41 older adults (56 + years old; 20 men and 21 women; age: 64.
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