Article

Robot-Assisted Gait Training for Patients with Hemiparesis Due to Stroke

Methodist Neurological Institute, Houston, Texas, USA.
Topics in Stroke Rehabilitation (Impact Factor: 1.45). 05/2011; 18(3):269-76. DOI: 10.1310/tsr1803-269
Source: PubMed
ABSTRACT
Robot-assisted devices are becoming a popular alternative to manual facilitation in stroke rehabilitation. These devices have the potential to reduce therapist burden and treatment costs; however, their effectiveness in terms of functional recovery remains in question. This pilot study compared the outcomes of a stroke rehabilitation program that incorporates robot-assisted gait training (RAGT) with a more traditional therapy program that does not. Twenty hemiparetic stroke patients were recruited at a rehabilitation hospital in Houston, Texas, and were randomly assigned to 2 groups. The control group (n = 10) received 24 1-hour sessions of conventional physical therapy, whereas the RAGT group (n = 10) received 24 1-hour sessions of conventional physical therapy combined with RAGT on a treadmill. Gait function was assessed before and after treatment by an 8-m walk test, a 3-minute walk test, and the Tinetti balance assessment. Both groups showed significant improvement in all 3 outcome measures following treatment (P < .05), but there was no difference between groups. It is concluded that RAGT may provide improvements in balance and gait comparable with conventional physical therapy. A larger multicenter trial is required to investigate the effectiveness of RAGT in hemiparetic stroke.

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269
Top Stroke Rehabil 2011;18(3):269–276
© 2011 Thomas Land Publishers, Inc.
www.thomasland.com
doi: 10.1310/tsr1803-269
Robot-Assisted Gait Training for Patients
with Hemiparesis Due to Stroke
Stanley Fisher, MD,
1,2
Leah Lucas,
2
and T. Adam Thrasher, PhD
3
1
Methodist Neurological Institute, Houston, Texas;
2
HealthSouth Rehabilitation Hospital, Humble, Texas;
3
University of Houston, Center for Neuromotor and Biomechanics Research, Houston, Texas
Robot-assisted devices are becoming a popular alternative to manual facilitation in stroke rehabilitation. These devices have
the potential to reduce therapist burden and treatment costs; however, their effectiveness in terms of functional recovery
remains in question. This pilot study compared the outcomes of a stroke rehabilitation program that incorporates robot-
assisted gait training (RAGT) with a more traditional therapy program that does not. Twenty hemiparetic stroke patients
were recruited at a rehabilitation hospital in Houston, Texas, and were randomly assigned to 2 groups. The control group
(n = 10) received 24 1-hour sessions of conventional physical therapy, whereas the RAGT group (n = 10) received 24
1-hour sessions of conventional physical therapy combined with RAGT on a treadmill. Gait function was assessed before
and after treatment by an 8-m walk test, a 3-minute walk test, and the Tinetti balance assessment. Both groups showed
signifi cant improvement in all 3 outcome measures following treatment (P < .05), but there was no difference between
groups. It is concluded that RAGT may provide improvements in balance and gait comparable with conventional physical
therapy. A larger multicenter trial is required to investigate the effectiveness of RAGT in hemiparetic stroke. Key words:
gait, hemiparesis, robot-assisted training, stroke, treadmill training
A
large proportion of strokes result in
hemiparesis and gait impairments. Recovery
of balance and walking function are key
goals for many stroke patients, and signifi cant
improvements are possible through rehabilitation.
The current evidence indicates that intensive,
task-specifi c therapy produces the highest level of
recovery of motor function, even in cases of severe
impairment.
1
Locomotor training is the process
of retraining gait through the repetitive execution
of assisted walking movements. The traditional
approach to locomotor training involves manual
assistance from therapists as patients walk on a
treadmill or overground.
2
When applied at a high
enough intensity and for a suffi cient duration,
locomotor training has the potential to produce
significant, long-lasting improvements in gait
function.
3
In recent years, there has been a lot of
attention focused on the development of advanced
therapeutic interventions involving technologies
such as functional electrical stimulation
4
(FES)
and robotics.
5
These interventions are designed
to facilitate walking and enable patients to engage
in gait retraining at the earliest point in their
rehabilitation program.
Currently, there are many treatment options
available for gait rehabilitation after stroke.
6
Many
of these have proved to be effective in clinical
studies; however, it is not clear that any particular
approach is superior for improving gait speed or
quality.
3
The use of partial body weight support
to facilitate locomotor training became popular
in the mid-1990s. Many severely impaired stroke
patients have diffi culty bearing their total body
weight on the affected leg during the swing phase
of gait. This problem can be addressed by partially
relieving the patient’s body weight using an
overhead harness, thus compensating for weakness
of the weight-bearing muscles and allowing the
patient to focus on motor control during walking.
In stroke rehabilitation, body weight–supported
treadmill training (BWSTT) typically involves 1
or 2 therapists who provide manual assistance
to facilitate correct movement. Compared with
traditional locomotor training approaches, BWSTT
enables patients to walk longer and to take more
steps, thus signifi cantly increasing the number of
repetitions and functional gains.
7
BWSTT has been
shown to be effective in improving gait function in
Grand Rounds
Elliot J. Roth, MD, Editor
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    • "Over the years, various gait rehabilitation robotic devices have been developed based on different concepts [6,7]. However, most of existing robotic gait training systems, such as Lokomat [4], ReoAmbulator [8], LOPES [9], ALEX [10] and Auckland University's system [11], integrate treadmills and fixed platforms [12]. They are meant for acute patients at big rehabilitation centers or hospitals; and rehabilitation progress of which is inferior to overground gait training [13,14]. "
    [Show abstract] [Hide abstract] ABSTRACT: This paper presents the mechanical design and evaluation of a knee–ankle–foot robot, which is compact, modular and portable for stroke patients to carry out overground gait training at outpatient and home settings. A novel compact series elastic actuator (SEA) is developed for safe human–robot interactions. As a solution to the limitation of conventional SEA designs, one low-stiffness translational spring and a high-stiffness torsion spring are placed in series for force transmission. The springs are selected based on gait biomechanics to maintain a high intrinsic compliance for most period of a gait cycle, while retaining the capacity to provide the peak force. To achieve portability, the robotic joint mechanism is optimized based on gait biomechanics, and the mechanical structure is built with lightweight materials. This robot demonstrates stable and accurate force control in experiments conducted on healthy subjects with overground walking. The activation level of the major leg muscles of subjects is reduced as indicated by the EMG signals and the normal gait pattern is maintained during the test, which demonstrates that the robot can provide effective assistive force to the subjects during overground walking.
    Full-text · Article · Sep 2016 · Mechanism and Machine Theory
    • "Motivated by the idea that a better understanding of the effects of human–robot misalignment can drive the design of future improved exoskeletons , this study analyzed the effects of knee misalignments on a user's gait in terms of kinematics, kinetics, and gait timing. To date, most treadmill-based rehabilitation exoskeletons feature a simple hinge joint at the robotic knee: Lokomat [1], LOPES [33], ALEX I, II, and III [18], [34], [35] , and Au- toAmbulator [36]. Each device provides several adjustments to fit the subject's legs into the robot and reduce macromisalignments . "
    [Show abstract] [Hide abstract] ABSTRACT: Due to the complexity of the human musculoskeletal system and intra/intersubjects variability, powered exoskeletons are prone to human-robot misalignments. These induce undesired interaction forces that may jeopardize safe operation. Uncompensated inertia of the robotic links also generates spurious interaction forces. Current design approaches to compensate for misalignments rely on the use of auxiliary passive degrees of freedom that unavoidably increase robot inertia, which potentially affects their effectiveness in reducing undesired interaction forces. Assessing the relative impact of misalignment and robot inertia on the wearer can, therefore, provide useful insights on how to improve the effectiveness of such approaches, especially in those situations where the dynamics of the movement are quasi-periodic and, therefore, predictable such as in gait. In this paper, we studied the effects of knee joint misalignments on the wearer's gait, by using a treadmill-based exoskeleton developed by our group, the ALEX II. Knee joint misalignments were purposely introduced by adjusting the mismatch between the length of the robot thigh and that of the human thigh. The amount of robot inertia reflected to the user was adjusted through control. Results evidenced that knee misalignment significantly changes human-robot interaction forces, especially at the thigh interface, and this effect can be attenuated by actively compensating for robot inertia. Misalignments caused by an excessively long robot thigh are less critical than misalignments of equal magnitude deriving from an excessively short robot thigh.
    No preview · Article · Aug 2015 · IEEE Transactions on Robotics
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    • "Most of the clinical trials indicated that robotic gait training alone or the combination of robotic gait training and conventional therapy is superior to conventional therapy alone in terms of gait function recovery [90,94,96,101,102]. Some trials reported improvement but no difference in gait function recovery , which is the primary assessing scale of those trials, between experimental and controlled groups [97,100] . Another trial however reported that conventional therapy was superior to robotic gait rehabilitation in terms of gait speed and endurance [95]. "
    [Show abstract] [Hide abstract] ABSTRACT: A large number of gait rehabilitation robots, together with a variety of control strategies, have been developed and evaluated during the last decade. Initially, control strategies applied to rehabilitation robots were adapted from those applied to traditional industrial robots. However, these strategies cannot optimise effectiveness of gait rehabilitation. As a result, researchers have been investigating control strategies tailored for the needs of rehabilitation. Among these control strategies, assisted-as-needed (AAN) control is one of the most popular research topics in this field. AAN training strategies have gained the theoretical and practical evidence based backup from motor learning principles and clinical studies. Various approaches to AAN training have been proposed and investigated by research groups all around the world. This article presents a review on control algorithms of gait rehabilitation robots to summarise related knowledge and investigate potential trends of development. There are existing review papers on control strategies of rehabilitation robots. The review by Marchal-Crespo and Reinkensmeyer (2009) had a broad cover of control strategies of all kinds of rehabilitation robots. Hussain et al. (2011) had specifically focused on treadmill gait training robots and covered a limited number of control implementations on them. This review article encompasses more detailed information on control strategies for robot assisted gait rehabilitation, but is not limited to treadmill based training. It also investigates the potential to further develop assist-as-needed gait training based on assessments of patients’ ability. In this paper, control strategies are generally divided into the trajectory tracking control and AAN control. The review covers these two basic categories, as well as other control algorithm and technologies derived from them, such as biofeedback control. Assessments on human gait ability are also included to investigate how to further develop implementations based on assist-as-needed concept. For the consideration of effectiveness, clinical studies on robotic gait rehabilitation are reviewed and analysed from the viewpoint of control algorithm.
    Full-text · Article · Sep 2014 · Medical Engineering & Physics
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