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

NCT ID: NCT07034105

Last Updated: 2025-06-24

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 25 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-06-12
• Study Completion Date: 2026-02-11

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.

Conditions

Gait Impairment in Stroke Patients

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: SUPPORTIVE_CARE
• Blinding Strategy: NONE

Study Groups

Experimental Group - Walking Modalities Comparison

This arm will involve stroke patients who undergo all three walking modalities (Overground Walking, Self-Paced Treadmill, and Body-Weight Supported Treadmill) in a counterbalanced order. Each patient will perform all modalities, and the spatiotemporal gait parameters such as stride length, cadence, and gait speed will be measured for analysis. The primary goal is to compare gait parameter variability and reliability across different walking conditions, assessing the effect of each modality on stroke rehabilitation.

Group Type: EXPERIMENTAL

Gait Analysis

Intervention Type: DIAGNOSTIC_TEST

• 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.

Interventions

Gait 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.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

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.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 75 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Dhaka Medical College

OTHER

Sponsor Role: collaborator

Bangladesh University of Engineering and Technology

OTHER

Sponsor Role: lead

Responsible Party

Muhammad Tarik Arafat

Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Muhammad Tarik Arafat, PhD

Role: PRINCIPAL_INVESTIGATOR

Department of Biomedical Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka - 1205.

Locations

Bangladesh University of Engineering and Technology

Dhaka, , Bangladesh

Site Status: RECRUITING

Countries

Bangladesh

Central Contacts

Muhammad Tarik Arafat, PhD

Role: CONTACT

tarikarafat@bme.buet.ac.bd

01911764467

Mehedi Hasan Prince, B.Sc.

Role: CONTACT

mhprince.bme@gmail.com

+8801745676375

Facility Contacts

Muhammad Tarik Arafat, PhD

Role: primary

tarikarafat@bme.buet.ac.bd

+88 01911764467

Provided Documents

Document Type: Study Protocol and Informed Consent Form

View Document

Other Identifiers

BUET/ERC/2024/02

Identifier Type: -

Identifier Source: org_study_id