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Spatiotemporal Gait Parameters of Healthy and Stroke Patients During Overground, Treadmill, and Body Weight Supported Treadmill Walking

Variability in Spatiotemporal Gait Parameters of Stroke Patients Across Overground, Self Paced Treadmill, and Body-Weight Supported Treadmill Walking

Status
Recruiting
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07034105
Enrollment
25
Registered
2025-06-24
Start date
2024-06-12
Completion date
2026-02-11
Last updated
2025-06-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gait Impairment in Stroke Patients

Keywords

Gait Analysis, Spatiotemporal Parameters, Body Weight Support System (BWSS)

Brief summary

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.

Detailed description

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.

Interventions

DIAGNOSTIC_TESTGait Analysis

* 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.

Sponsors

Dhaka Medical College
CollaboratorOTHER
Bangladesh University of Engineering and Technology
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SUPPORTIVE_CARE
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
No

Inclusion criteria

* Participants must be between 18 to 75 years old. * More than 1- month post stroke patient. * Participants must be able to walk with or without assistance. * Patients including both the male and female. * Participants must be able to provide informed consent to participate in the study.

Exclusion criteria

* Severe cognitive or communicative disorders. * Significant joint malposition. * Psychological, cognitive dysfunction, and any other neuromuscular problem. * Pregnant women will be excluded to avoid any potential risks to the mother and fetus. * Unstable cardiovascular disease like congenital heart disease, deep vein thrombosis, coronary heart disease, previous history of heart attack or heart failure.

Design outcomes

Primary

MeasureTime frameDescription
Spatiotemporal Gait Parameter VariabilityBaselineThe 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.

Countries

Bangladesh

Contacts

Primary ContactMuhammad Tarik Arafat, PhD
tarikarafat@bme.buet.ac.bd01911764467
Backup ContactMehedi Hasan Prince, B.Sc.
mhprince.bme@gmail.com+8801745676375

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026