Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT06164197 |
| Other study ID # |
RAGT03 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
August 23, 2023 |
| Est. completion date |
June 1, 2025 |
Study information
| Verified date |
December 2023 |
| Source |
Ankara Yildirim Beyazit University |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
The aim of research is to examine and compare the effectiveness of virtual reality-based
balance training and robot-assisted walking approaches on balance and gait in individuals
post-stroke. Through the study, Investigators intend to reach conclusions regarding whether
the focus should be on balance or walking training based on the Berg Balance Scale and
Functional Ambulation Classification levels of stroke survivors. Subgroups will be formed in
both groups based on Functional Ambulation and Berg Balance Scale scores. The balance and
gait developments within these subgroups will be compared, aiming to determine at which
levels balance or walking improvement is more pronounced. These findings are crucial for
making the right choices in setting rehabilitation goals for individual patients.
Description:
Stroke is one of the leading causes of death in adults and results in severe disability.
Within the first 3 months after a stroke, 20% of patients use a wheelchair, and 70%
experience walking problems. Balance problems are among the most common issues after a
stroke, impacting a patient's ability to sit, stand, transfer, and walk, thereby creating a
risk of falls. Additionally, balance and walking quality are vital components, with
abnormalities potentially leading to abnormal walking patterns, reduced walking speed, and
spatiotemporal asymmetries. Therefore, improving balance and walking is a fundamental goal in
stroke rehabilitation and holds priority for many patients and their families.
Robot-assisted gait training (RAGT) is an emerging and promising technological approach in
stroke rehabilitation. RAGT provides safe, high-intensity, and task-oriented walking training
with ample repetitions. Repetitive tasks can enhance neuroplasticity and motor learning,
resulting in improved balance and walking speed.
Robotic systems come in two types: end-effector and exoskeleton. The LokomatĀ® FreeD (Hocoma
AG, Switzerland) is an exoskeleton-type robot. Unlike the conventional Lokomat, the FreeD
module allows pelvic translation to the right and left, along with rotation. These
coordinated pelvic movements are mechanically facilitated by the device during walking. It is
known that these movements are crucial for human walking and balance, and with the FreeD
module, these pelvic movements have become part of robot-assisted gait training.
In a systematic review comparing Lokomat with conventional physiotherapy, it was reported
that Lokomat is equally effective in terms of balance. Another review found that patients
undergoing robot-assisted gait training showed better improvement in balance compared to
those not receiving this treatment. The literature supports Lokomat's positive effects on
both balance and walking.
In this research, virtual reality applications on LokomatĀ® will be integrated as part of the
exercises in the Lokomat group and virtual reality-based balance training using the Balance
Trainer will be employed for the Balance-Trainer group.
Patients will be allocated to the Lokomat and Balance-Trainer groups based on the treatment
they receive. Both systems are actively used in the hospital, which research conduct, for the
purpose of actively treating patients who meet the research criteria for improving balance
and walking in stroke survivors. Participants will engage in exercises with LokomatĀ® or
Balance Trainer for three weeks, five sessions per week, each session lasting 30 minutes,
totaling 15 sessions, in addition to their current rehabilitation program.