Gait impairments following a stroke significantly hinder mobility and quality of life, emphasizing the need for precise assessment methods to guide effective rehabilitation strategies. This study evaluates the variability and reliability of spatiotemporal gait parameters across three walking modalities: overground walking, treadmill walking, and body-weight-supported treadmill walking. Using a counterbalanced design, all participants undergo gait analysis in each modality to ensure unbiased and reliable comparisons. The study also incorporates a locally developed, cost-effective Body Weight Support System (BWSS) to address the limitations of accessibility in resource-constrained settings. By identifying how different modalities influence gait variability and reliability, this research aims to optimize rehabilitation outcomes and demonstrate the feasibility of implementing affordable gait analysis tools in clinical practice.
Stroke remains a leading cause of long-term disability, with gait impairments being a prominent challenge that significantly affects functional independence. Accurate and reliable assessment of gait parameters is crucial for tailoring rehabilitation interventions. This study investigates the variability and reliability of spatiotemporal gait parameters, such as stride length, cadence, step time, and gait variability, across three distinct walking modalities: 1. Overground walking 2. Self paced treadmill walking 3. Body weight supported treadmill walking The study employs a counterbalanced design, where each participant performs all three walking modalities, mitigating potential order effects and ensuring robust and reproducible comparisons. Advanced motion analysis systems are utilized to capture high-resolution data, providing insights into the dynamic interplay of gait variability and reliability under each condition. A key innovation of this study is the use of an in-house, cost-effective Body Weight Support System (BWSS). Unlike commercially available systems, which are often prohibitively expensive, the BWSS is designed for accessibility in resource-limited settings, enabling widespread clinical and research applications. This approach aligns with the study's broader goal of improving healthcare equity by developing practical solutions tailored to local needs. By analyzing the impact of different walking modalities on gait, the research aims to: i. To analyze the variability and reliability of spatiotemporal gait parameters in stroke patients across overground, treadmill, and body weight supported treadmill walking (BWST). ii. To identify the walking modality that exhibits the most consistent and stable gait metrics. iii. To assess the clinical relevance of gait parameters from different walking modalities to optimize stroke rehabilitation interventions. This research not only advances the understanding of stroke rehabilitation but also contributes to the global effort to make cutting-edge medical technologies accessible to underserved populations.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
25
* Overground Walking: Stroke patients walk in a natural environment, collecting data on their gait parameters such as stride length, cadence, and gait speed. * Treadmill: Patients walk on a treadmill at their comfortable pace, allowing for more control over their walking speed while measuring the same gait parameters as in overground walking. * Body-Weight Supported Treadmill: Patients walk on a treadmill with a body-weight support system that reduces the load on the legs, enabling patients with more severe impairment to perform walking tasks safely while recording gait parameters.
Bangladesh University of Engineering and Technology
Dhaka, Bangladesh
RECRUITINGSpatiotemporal Gait Parameter Variability
The primary outcome measure will be the variability of spatiotemporal gait parameters, including stride length, cadence, and gait speed, assessed during the three walking modalities (Overground, treadmill, and body weight supported treadmill). The variability will be analyses by calculating the standard deviation and coefficient of variation for each parameter across all walking conditions. These measures will reflect the stability and consistency of the patients' gait performance in different walking settings, which is crucial for understanding their rehabilitation progress and the effect of each walking modality on recovery.
Time frame: Baseline
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