The changes in gait variability after revascularization in patients with peripheral artery disease
Advisor Information
Hafizur Rahman
Location
MBSC Ballroom - Poster #102 - U
Presentation Type
Poster
Start Date
4-3-2022 10:45 AM
End Date
4-3-2022 12:00 PM
Abstract
The changes in gait variability after revascularization in patients with peripheral artery disease
Megan Woods1, Hafizur Rahman1,2, Iraklis Pipinos2,3, Jason Johannning2,3, Sara Myers1,2
1Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE USA
2Department of Surgery and VA Research Service, VA Nebraska-Western Iowa Health Care System, Omaha, NE USA
3Department of Surgery, University of Nebraska Medical Center, Omaha, NE USA
Presentation Preference: Poster only
Peripheral artery disease (PAD) is characterized by limited blood flow to the limbs due to narrowed peripheral arteries. Revascularization surgical treatments to restore blood flow to the legs are common in patients with PAD if conservative approaches are not effective in relieving symptoms. Biomechanical analysis has demonstrated altered gait variability in patients with PAD. Variability is described as the normal fluctuations in motor performance that occur across multiple repetitions of a specific task. The objective of this study is to determine whether gait variability improves following revascularization treatment. Patients underwent revascularization surgery and participated in experimental testing before (baseline) and six-months after revascularization treatment (post-surgery). The position of reflective markers placed on specific anatomical locations of lower limbs were recorded while patients walked on a treadmill at a self-selected speed for three minutes or until the onset of claudication pain, whichever came first. We determined the gait variability using both linear and non-linear analysis. Linear analysis includes the calculation of standard deviation and coefficient of variation. Nonlinear analysis includes the largest Lyapunov exponent and the approximate entropy. We will calculate all four outcomes (standard deviation, coefficient of variation, largest Lyapunov exponent, and approximate entropy) for ankle, knee, and hip range of motions by using custom codes in MATLAB for baseline and post-surgery conditions. This knowledge will be useful for clinicians in interpreting the clinical significance of functional improvements following revascularization surgery.
Scheduling Link
1
The changes in gait variability after revascularization in patients with peripheral artery disease
MBSC Ballroom - Poster #102 - U
The changes in gait variability after revascularization in patients with peripheral artery disease
Megan Woods1, Hafizur Rahman1,2, Iraklis Pipinos2,3, Jason Johannning2,3, Sara Myers1,2
1Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE USA
2Department of Surgery and VA Research Service, VA Nebraska-Western Iowa Health Care System, Omaha, NE USA
3Department of Surgery, University of Nebraska Medical Center, Omaha, NE USA
Presentation Preference: Poster only
Peripheral artery disease (PAD) is characterized by limited blood flow to the limbs due to narrowed peripheral arteries. Revascularization surgical treatments to restore blood flow to the legs are common in patients with PAD if conservative approaches are not effective in relieving symptoms. Biomechanical analysis has demonstrated altered gait variability in patients with PAD. Variability is described as the normal fluctuations in motor performance that occur across multiple repetitions of a specific task. The objective of this study is to determine whether gait variability improves following revascularization treatment. Patients underwent revascularization surgery and participated in experimental testing before (baseline) and six-months after revascularization treatment (post-surgery). The position of reflective markers placed on specific anatomical locations of lower limbs were recorded while patients walked on a treadmill at a self-selected speed for three minutes or until the onset of claudication pain, whichever came first. We determined the gait variability using both linear and non-linear analysis. Linear analysis includes the calculation of standard deviation and coefficient of variation. Nonlinear analysis includes the largest Lyapunov exponent and the approximate entropy. We will calculate all four outcomes (standard deviation, coefficient of variation, largest Lyapunov exponent, and approximate entropy) for ankle, knee, and hip range of motions by using custom codes in MATLAB for baseline and post-surgery conditions. This knowledge will be useful for clinicians in interpreting the clinical significance of functional improvements following revascularization surgery.