Virtual Reality Based Robotic Gait and Balance Trainer

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 Lokomat® 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 Lokomat® 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 Lokomat® 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.

Inclusion criteria

• Having the ICD-10 diagnosis code G.81 Hemiplegia
• At least 3 weeks having passed since the diagnosis (Subacute and cronic periods)
• Being 18 years of age or older
• Having a Berg Balance Score between 21-40 (indicating an acceptable balance)
• Being able to walk with or without support (FAC score of 2 or higher)

Exclusion criteria

• Having a known additional neurological or orthopedic problem that could affect balance
• Inability to adapt to virtual reality applications in Lokomat and Balance Trainer
• Diagnosis being more than 2 years old