Stroke is the second leading cause of mortality, comprising 11.8% of all deaths worldwide, and the third most common cause of combined disability and death worldwide.(1) Locomotor disability is one of the significant barriers to community ambulation in stroke survivors and may manifest as reduced gait speed and endurance, recurrent falls, poor balance, and difficulty to perform activities of daily living.(2) Hence, recovery of gait is considered a top priority in rehabilitation of individuals with stroke.
In the acute phase of recovery, frequent, intensive, repetitive and task-specific training with active patient participation has been proposed to enhance neuroplasticity that facilitates gait and functional recovery.(3, 4) In recent years, stroke rehabilitation programs have incorporated use of several robotic devices, which provide more intensive and repetitive training compared to conventional approaches. A common characteristic of gait training robot is to partially support the body weight and aid in locomotion. Robotic devices can facilitate early mobilization of non-ambulatory patients and improve outcomes in the sub-acute phase of stroke.(5) The other advantages of robotic devices are their ability to deliver high repetitions of intensive gait training with reduced effort of the therapist, less energy-consumption, and greater cardiorespiratory efficiency of the patient. Treadmill-based robotics includes both end-effector devices and exoskeleton systems, which executes gait training on a treadmill with body weight support. In end-effector devices (e.g., G-EO- Reha-Technology, Switzerland), moveable footplates attached to the patient's feet simulate gait pattern. The exoskeleton treadmill system (e.g., Lokomat, Walkbot) moves joints, such as the hip, knee, and ankle, in a controlled manner during the gait training.(6)
A systematic review suggested that patients who receive robotic-assisted treadmill gait training and physiotherapy after stroke might attain more independent walking than patients who receive only conventional training.(5) However, there was no difference in gait speed and endurance between robotic and conventional gait training with equal intensity and duration.(5, 7, 8)
Despite the effectiveness of robot-assisted treadmill training, overground gait training is required to transfer the acquired skills to practical use in patients, improving the gait speed and endurance. Robotic Treadmill training does not permit the patient to experience real-world gait obstacles, such as walking on uneven terrain, stepping over objects, and stair climbing. Moreover, on treadmill robotics, patients walk with a pre-set speed and body weight support, creating an atmosphere where the patient might have less control in initiating each step and lack of alteration in visuospatial flow. These elements challenge optimum overground walking.(9) Therefore, stroke patients need to put more active effort into generating steps to walk and maintaining balance with the help or supervision during overground gait training. Traditionally, overground walking training is conducted using lower limb orthosis, walking aids such as cane/walker/hemiwalker etc, and therapists' assistance.(10) However, due to increased need of stroke patients and dearth of human resources including physical therapists, providing intensive and task-specific repetitive gait training is challenging.(11) Over-ground robotic-assisted gait training allows the patient to walk in a real-world setting, facilitates upright posture and balance control, and demands the patient's active participation while ensuring proper task performance.(12) Therefore, a robotic device using body weight support for overground walking could be a valuable tool for the gait rehabilitation of patients with stroke.
Overground robotic devices incorporate wearable powered exoskeletons (e.g. Ekso). Patients with severe deficits, including dense hemiplegia, might be benefited with exoskeleton robotic training.(12) The disadvantage is carrying the power source's heavy weight on the patient's back. Moreover patients with poor trunk control find it difficult to perform overground walking.
The Mobility Assisted Robotic System-MARS used in the present trial is an overground gait training-assist robot, developed by Bionic Yantra, an Indian start up based in Bengaluru, India. The system can sense the movement of the patient through the harness system, which is integrated with the sensor feedback system, allowing the patient to practice gait training safely and independently. There is a paucity of literature on robotic overground gait training in stroke patients. This pre-post study was aimed to explore the clinical effects of overground walking training with Mobility Assisted Robotic System (MARS) on gait parameters in stroke patients.