Robotic-assisted gait training (RAGT)

 is a new global physiotherapy technology that applies the high-intensity repetitive principle to improve mobility of patients with stroke or other neurological disorders.


The advantage of RAGT

 may be the reduction of the effort required by therapists compared with treadmill training with partial bodyweight support, as they no longer need to set the paretic limbs or assist in trunk movements. People who receive electromechanical-assisted gait training in combination with physiotherapy after stroke are more likely to achieve independent walking than people who receive gait training without these devices. More specifically, people in the first 3 months after stroke and those who are not able to walk seem to benefit most from this type of intervention. The use of RAGT in stroke patients has positive effects on their balance.


Introduction to RAGT

Stroke is the third most common cause of death and the biggest factor for disability in adults of developing nations, just behind cancer and heart diseases. Approximately 795,000 stroke cases occur every year in the USA with 2-3% in the cerebellum area. The loss of motor skills is one of the most common complaints of stroke survivors as approximately 75% of these patients have some walking disability that could result in high risk of falls.

Impairment in the posterior circulation that involves the cerebellum or brainstem region may lead to damages in several important functions, such as balance, movement coordination, speech, hearing, ocular movement, and swallowing. Ataxia is an important sequela observed and recognized for its presentation as a loss of coordination, dysmetria, dysarthria, hypotonia, rebound phenomenon, and nystagmus Gait ataxia is described by a stumbling walking pattern, an irregular foot placement, an increased step, an enlarged stance, and an abnormal joint torque.

When the depletion of balance ability is associated with decreased joint mobility, muscle tone problems, and loss of proprioception, there is an increase in the difficulty to perform activities of daily living for individuals with stroke injury. Consequently, balance training is crucial for rehabilitation treatment. Conventional gait therapy (CGT), such as the Bobath concept, proprioceptive neuromuscular facilitation, therapist-assisted walking, and the use of braces or other devices are common treatment approache. Furthermore, high severity stroke patients with poor coordination in walking may benefit from treatment with a robotic device that allows task-focused training.

Robot-assisted gait training (RAGT) has been used since 1980 to assist patients with dysfunction in movement caused by neurological disorders. This treatment is based on the body weight-supported treadmill (BWSTT) principle and achieves functional motor relearning through the repetitive practice of all different phases of gait . Training the same movement repetitively enables the nervous system to develop circuits for better communication between the motor center and sensory pathways.

Treatment by RAGT compared with conventional treatment on the treadmill presents advantages, including training duration, more reproducible symmetrical gait patterns, operation by a single therapist, and a reduction in the energy expenditure imposed upon the therapists. Training resulted in a more symmetrical muscle activity pattern in paretic patients compared with conventional treatment.

 Technological innovations are allowing rehabilitation to move toward more integrated processes, with improved efficiency and less long-term impairments. In particular, robot-mediated neurorehabilitation is a rapidly advancing field, which uses robotic systems to define new methods for treating neurological injuries, especially stroke. The use of robots in gait training can enhance rehabilitation, but it needs to be used according to well-defined neuroscientific principles. The field of robot-mediated neurorehabilitation brings challenges to both bioengineering and clinical practice. 


First, it is necessary to clarify the difference between a robot and other electromechanical devices. The Robot Institute of America defines a robot as

a programmable, multi-functional manipulator designed to move material, parts or specialized devices through variable programmed motions for the performance of a variety of tasks

Based on this definition, an incomplete list of commercial robot walk trainers includes the following: Gait Trainer (RehaStim, Berlin, Germany), G-EO (Reha Technology AG, Olten, Switzerland), Lokomat (Hocoma, Volketswil, Switzerland), Bionic Leg (Tibion Bionic Technologies, Moffett Field, CA, USA), eLEGS (University of California Berkeley/Ekso Bionics, Richmond, CA, USA), ReWalk (Argo Medical Technologies, Yokneam, Israel), and REX (Rex Bionics, Auckland, New Zealand). Another list may include prototypes not yet fully commercialized, such as Lopes, Lopes 2 (developed at the University of Twente, Enschede, the Netherlands), Knexo (Vrije University Brussel, Ixelles, Belgium), Alex (University of Delaware, Newark, NJ, USA), Mindwalker (Delft University, Delft, the Netherlands), VanderBilt Exoskeleton (VanderBilt University, Nashville, TN, USA), Hercule (CEA-LIST/RB3D, Paris, France), i-Walker (Universitat Politècnica de Catalunya, Barcelona, Spain), Walkbot (P&S Mechanics Co, Ltd, Seoul, South Korea), Walk Assist Robot (Toyota, Tokyo, Japan), Honda’s walking assist device (Honda, Tokyo, Japan), Anklebot (Massachusetts Institute of Technology, Cambridge, MA, USA), and Indego (Parker Hannifin Corporation, El Segundo, CA, USA).7

These devices can be classified according to the motion they apply to the patient’s body. For instance, “exoskeletons” move joints, such as hip, knee, and ankle, controlled during the gait phases, whereas “end-effector robots” move only the feet, often placed on a support (footplate), which imposes specific trajectories, simulating the stance and swing phases during gait training.Another possible classification is between devices in which the patient is moved in a fixed place and those moving the patient around the environment. We could define these devices as static and dynamic ones, respectively


Theoretical and practical robotic support for gait rehabilitation

A common feature of gait training robots is the possibility to support (partially or totally) the body weight and the movement of patients. Body weight support seems to be the condition sine qua non for facilitating gait recovery with robotic devices. To restore gait, clinicians prefer a task-specific repetitive approach and, in recent years, better outcomes have been achieved with higher intensities of walking practice programs.Another role of robotic devices is to facilitate the administration, to nonambulatory patients, of intensive and highly repetitive training of complex gait cycles, something a single therapist cannot easily do alone. With respect to treadmill training with partial body weight support, yet another advantage of these robotic devices may be the reduced effort for therapists: they no longer need to set the paretic limbs or assist trunk movements.A secondary but important feature related to body weight support and to robotic rehabilitation in general is the possibility of favoring the restoration of an adequate level of cardiorespiratory efficiency. Despite this aspect being rarely taken into account in evaluating robotic efficiency, previous results have shown that robotic gait training reduces energy consumption and cardiorespiratory load. In fact, for severely impaired neurological patients, robotic walk training allows an early verticalization without the risk of increasing spasticity on antigravitational muscles, hence avoiding deconditioning, which would worsen cardiologic comorbidities. This is a very important feature, if one considers that cardiovascular disease is the leading prospective cause of death in people with chronic stroke.32 It is well known that persons with stroke suffer an extremely poor cardiovascular fitness, with a reduction of the mobility and a consequent reduction of the quality of life.

Energy consumption and cardiorespiratory load during walking with robot assistance seems to depend not only on body weight support but also on factors such as robot type, walking speed, and amount of effort. These parameters could be adjusted during robotic rehabilitation to make it either more or less energy consuming and stressful for the cardiorespiratory system.


Robotic rehabilitation “versus” or “together” with physiotherapy?

he use of robots should not replace the neurorehabilitation therapy performed by a physiotherapist. Robots, as all technological devices, must be considered as tools in the hands of the physiotherapist and never rehabilitative per se.In fact, the robot can alleviate all labor-intensive phases of physical rehabilitation, hence allowing the physiotherapist to focus on functional rehabilitation during individual training and to supervise several patients at the same time during robot-assisted therapy sessions. With this approach, the expertise and time of physiotherapists is optimized, increasing the rehabilitation program’s efficacy and efficiency at the same time.

With respect to conventional therapy alone, the addition of robotic intervention brings another important advantage: it allows an online and offline instrumented, quantitative (hence, objective) evaluation of several parameters related to patient performance. These include range of motion, velocity, smoothness of movements, amount of forces, and so on. Thus, robotic systems may be used not only to produce simple and repetitive stereotyped movement patterns, as in the case of most of the existing devices, but also to generate a more complex, controlled multisensory stimulation of the patient. This includes, but is not limited to, the assessment of the patient’s performance with a biofeedback or with a report.

An aspect rarely taken into account in robotic rehabilitation is the psychology of the patient, who often needs not only to be cured, but also to be cared. It is well known that patients’ engagement and participation in conventional exercises is considered a key factor to increase rehabilitation performances and thereby boost plasticity. During robot-assisted therapy, this can be achieved via extrinsic feedback of serious game scenarios, where the scores obtained assess the patients’ performance. The acceptance of robotic technology by patients and physiotherapists may be an issue per se, although there is no evidence of this for the devices developed to date. Nevertheless, not all patients, especially the elderly, accept to be treated with a robot, and Bragoni et  they have shown that anxiety may reduce the efficacy of robotic walking training. In the future, the cultural gap among technology providers, rehabilitation professionals, and end users should be filled by improving the dissemination of technological knowledge and the diffusion of increasingly user-friendly and safer technology.


From “efficacy for all” to “all for efficacy”

Most studies aim at answering the question “are robotic devices effective for all kinds of poststroke patients?”. However, Morone et al have highlighted the need for changing this question into “for whom are robotic devices the most effective?” The goal should not be to test the efficacy for all patients but to dispose of all the possibilities, for improving efficacy. For instance, the least-affected patients would rather benefit from device-free conventional overground training than use artificial interventions that may alter recovery of their physiological patterns.

A key point for the diffusion and correct use of new technologies is to know the group of patients for whom and the rehabilitation phase during which each type of technology is more beneficial. Following this principle, it was  found that patients with more severe motor leg impairments are those who benefit the most from robot-assisted therapy in combination with conventional therapy. This finding probably results from the augmented intensity of robotic therapy, as compared to conventional therapy (especially for the most impaired patients). Conversely, patients with greater voluntary motor function in the affected limb can perform intensive training during conventional therapy also. A large rehabilitation study (Locomotor Experience Applied Post-Stroke [LEAPS]) showed that more expensive high-tech therapy was not superior to intensive home strength and balance training (the so-called kitchen sink exercises), but both were better than lower-intensity physical therapy. These results may support the idea that the great advantage of robots designed for walking therapy is only related to the warranty of a more intensive therapy. Consequently, after 20 years of investigation on robotic devices, including body weight support systems, efficacy is still uncertain, and most of the robotic use is still confined to research-controlled trial instead of in clinical practice. This skepticism has led to put into question the clinical usability of robots in neurorehabilitation: Hidler and Lum questioned the possibility that these devices will become commonplace in every hospital and rehabilitation clinic or whether they will become things of the past like so many other promising prototypes. In addition, after having asked “Where are the robots promised by scientific literature able to restore motor functions after stroke?”,  it was noted that despite surgical robots being introduced at around the same time as rehabilitation robots, only the benefit of the formers has been well established.

On the other hand, from a theoretical point of view, many researchers agree that patients may benefit from machines providing external support, until they recover the capacity of walking over ground, unsupported. Robots can favour this recovery, allowing a progressive decrease of external support matching the patients’ level of gait dependency. Probably, the question needs to be changed from “Are robotic devices effective for rehabilitation?” to “Who may benefit the most from robotic rehabilitation”?


Current perspective and open problems

According to the current literature, it is not yet clear how different rehabilitation approaches contribute to restorative processes of the central nervous systems after stroke. In this scenario, the efficacy of robotic gait training seems to be strictly related to a good identification of the best candidates among patients of those who could benefit more from a robotic training. This choice is strictly related to both physical and psychological features with respect to the available devices.

There are also some other points deserving attention. Despite most studies claiming that robots would increase rehabilitation intensity, repetition of tasks alone is not sufficient to guide neural plasticity. Furthermore, most robots replicate physiological patterns, not always reachievable by patients. The approach is analogous to training footballers only to play many matches, without focusing the training on specific aspects and exercises that need to be improved separately. In fact, optimal schemes of robot assistance to facilitate motor skill learning are debated. Thus, a robot is not a substitute for physical therapists but should be considered a tool in the hands of therapists to train different determinants of a multisystem rehabilitation and for improving patients’ skills. This leads to the need for a robot of active onboard control algorithms combined with functional motor learning tasks, to improve participation, required assistance, and reinforcement learning



Finally, most of the robots commercialized nowadays are based on the a prior idea that walking is an automatic subcortical ability. However, this aspect was recently reconsidered from the following perspectives: 1) from a biomechanical point of view, by reviewing the role of the trunk from a passive to an active actor; 2) from a neurological point of view, in which the conventional bottom-up approach has been integrated in a top-down approach; 3) from a neuromechanical point of view, in which structures and functions are strictly connected around specific harmonic points of equilibrium that maximize the efficiency of walking.

At this step, the role of the clinical researcher is to investigate whether the available robot is effective or not for the level of severity in patients with stroke admitted to his/her rehabilitation hospital. The role of bioengineers should be to match the most recent neurological findings with the specifics of the robots developed for gait training, not only simulating physiological patterns and emulating the therapist, but favoring and widening the determinants of gait recovery. Finally, both clinicians and bioengineers should collaborate for defining new paradigms and protocols for increasing robotic effectiveness and diffusion within the rehabilitation teams.

For further reading please refer to 

National Center for Biotechnology Information, U.S. National Library of Medicine