Stroke is a leading cause of long-term disability and is the third most common cause of mortality in developed countries with 15 million people suffering a stroke yearly.1 Different parts of the brain control different bodily functions. If a person survives a stroke, the effects can vary, depending on the location of brain damage, severity and duration of the stroke. Broadly, the effects of stroke can be physical, cognitive or emotional in nature. In terms of the physical effects of stroke, the loss of motor abilities of the limbs presents significant challenges for patients, as their mobility and activities of daily living (ADLs) are affected. The upper or lower limbs can experience weakness (paresis) or paralysis (plegia), with the most common type of limb impairment being hemiparesis, which affects eight out of 10 stroke survivors.2 Other physical effects of stroke are loss of visual fields, vision perception, difficulty swallowing (dysphagia), apraxia of speech, incontinence, joint pain or neuropathic pain (caused by inability of the brain to correctly interpret sensory signals in response to stimuli on the affected limbs). Cognitive effects of stroke are aphasia, memory loss and vascular dementia. Stroke patients can lose the ability to understand speech or the capacity to read, think or reason, and normal mental tasks can present big challenges, affecting their quality of life. The drastic changes in physical and cognitive abilities caused by stroke also lead to emotional effects for stroke patients. Stroke survivors can experience depression when they encounter problems in doing tasks that they can easily do pre-stroke. Along with depression, they can experience a lack of motivation and mental fatigue.
For stroke patients, rehabilitation is the pathway to regaining or managing their impaired functions. There is no definite end to recovery but the most rapid improvement is within the first six months post stroke.3 Before a patient undergoes rehabilitation, an assessment is first done to determine if a patient is medically stable and fit for a rehabilitation program. If the patient is assessed to be suitable, then depending on the level of rehabilitative supervision required, the patient could undergo rehabilitation in various settings – as an in-patient/outpatient (at either a hospital or nursing facility) or at home.3,4 Rehabilitation should be administered by a multi-disciplinary team of physiotherapists, occupational therapist, speech therapist and neuropsychologists, who work together to offer an integrated, holistic rehabilitation therapy.4 Depending on the type of impairment, rehabilitation specialists will assess the appropriate therapies needed and set realistic goals for patients to achieve. Generally, stroke patients should be given a minimum of 45 min for each therapy session over at least five days per week, as long as the patient can tolerate the rehabilitation regimen.3
One of the main goals in stroke rehabilitation is the restoration of motor skills, and this involves patients undergoing repetitive, high-intensity, task-specific exercises that enable them to regain their motor and functional abilities.5,6 It is theorized that the brain is plastic in nature and that repetitive exercises over long periods can enable the brain to adapt and regain the motor functionality that has been repeatedly stimulated.7 This involves the formation of new neuronal interconnections that enable the re-transmission of motor signals.8
Over the years, a number of robotic assistive devices have been used to rehabilitate patients based on high repetitions of task-specific exercises.9 These robotic assistive devices provide consistent and repetitive cycles over long periods and help train the limbs of patients to keep receiving and sending signals from and back to the brain and thereby regain their motor abilities. Such devices are also complex in nature involving interactive automation, sensors and dynamic control logic and are able to function without much intervention from physiotherapists. Several devices have been used for rehabilitation of both upper limb (e.g. ARMin, MIT-MANUS, NeReBot and T-Wrex) and lower limb (e.g. Lokomat, Gait Trainer, G-EO System and Hybrid Assistive Leg).10,11 As an example, for patients who are unable to walk, there are gait-training devices such as the Lokomat that help patients to recover their walking ability. Initially, the physiotherapist will set the patient up with the device and start a software program that cycles through the various stages of walking. The patient's lower limbs will be moved by the device and the physiotherapist is able to set the pace of the simulated walking and the amount of guidance force to assist movement of the legs and extent of body weight support.
In comparison, for conventional rehabilitation of the lower limbs without assistive devices, it would require at least two physiotherapists to train a patient to walk, and the pace and pattern of walking may not be consistent. It is also physically strenuous for the physiotherapists to sustain the exercise over long periods, thus affecting the rehabilitation progress of the patient. The labor-intensive nature of conventional physiotherapy places great strain on physiotherapists. Coupled with the requirements of stroke patients for medical care and intensive rehabilitation exercises (which frequently entail one-to-one manual interaction with therapists), therapist time and organizational budgets, it is not always possible to provide an optimal rehabilitation program for patients.10 Therefore, it is hoped that with robotic assistive devices, better rehabilitation progress can be achieved for patients together with alleviation of time and physical demands on physiotherapists. With the assistance of robots, physiotherapists will be able to concentrate more on functional rehabilitation during individual training sessions and supervision of multiple patients simultaneously during robot-assisted therapy sessions. This approach would maximize the expertise and time of physiotherapists, thus improving the effectiveness of the rehabilitation program.10
There have been clinical studies to determine the effectiveness of robotic assistive devices in the rehabilitation of stroke patients.12 However, these studies presented a mixed picture of the effectiveness of robotic devices. One study on lower limbs reported an improvement in a motor movement scale (Fugl-Meyer Assessment lower extremity score) but not for another motor scale (leg score of Motricity Index) and also stated no improvement on a walking scale (Functional Ambulation Category).13 Others reported that there was no statistically significant difference between robotic assisted therapy and conventional therapy,14,15 while one study that investigated walking speeds and distance found that conventional therapy was more effective than robotic assisted therapy.16 There were also various types of study designs. Some studies examined not just robot-assisted rehabilitation but combinations of robot-assisted rehabilitation and non-conventional physiotherapies (e.g. functional electrical simulation [FES], constraint induced therapy [CIT], transcranial direct current stimulation or motor imagery) versus conventional therapies in three-arm studies.17-19 Other studies involved patients in a randomized controlled crossover trial with or without a washout period.20,21
Typically, in studies, authors used different scales for their primary and secondary outcomes. These scales were used to measure motor movement, motor strength/duration, walking speed or functional activities. With various outcome scales used, it will be a challenge to compare the results of clinical trials,22 and the suitability of certain scales will also depend on the modality of the robotic therapy given. As an example, for arm muscle strength outcome, it will be better if patients have less assistive guidance force provided (or conversely, more resistive guidance force provided) and minimal gravity support during therapy sessions.23 Also, in a trial with multiple outcome measures, testing multiple simultaneous hypotheses at set P values could lead to increased risk of Type I errors.24 To mitigate this, Feise24 recommended that researchers facing multiple outcome measures select a primary outcome measure or use a global assessment measure. As robotic devices are primarily designed to enable movement of a particular limb,10 a suitable measurement scale that reflects the design function of the device is necessary to accurately determine the effectiveness of these devices. In view of this, scales that measure movement abilities of the paretic limbs should be used, such as Fugl-Meyer Scale Assessment (upper extremity) for the upper limbs or Functional Ambulation Category for the lower limbs.
A preliminary search of PubMed, Embase, JBI Database of Systematic Reviews and Implementation Reports and Cochrane Library identified three systematic reviews that have been conducted in this topic area.25-27
These reviews included a variety of outcome measures for motor function, muscle strength, walking capacity and walking velocity. Mehrholz et al.25,26 found that robot-assisted arm training improved ADLs, arm function and muscle strength of the paretic arm, and for the lower limbs walking was improved but not for walking velocity or walking capacity. Prange et al.27 found that arm control improved but not functional ability. The proposed systematic review being undertaken has different aspects to the previous reviews. First is the selection of the outcome measure to examine primarily the motor movement of the paretic limbs in order to have a meaningful comparison across studies.22 Second is the analysis approach toward multiple-arm studies. In the first two reviews,25,26 the results of the arms of robotic intervention groups, some with additional forms of non-conventional treatment, were pooled together for comparison against the control group. In this review, only the arm of robotic intervention group (without other forms of non-conventional treatment, e.g. FES) will be compared to the control group to clarify the effects of the intervention. The current review also seeks to address the question of sustainability of the treatment effects; for example, is the improved motor movement ability measured at the end of intervention period maintained post intervention? If the outcome measure is maintained (or improved) during follow-up measurements after intervention, then the effect of rehabilitation can be considered as being sustainable. From analyzing the intervention sustainability, it is hoped that the optimal duration and frequency of rehabilitation that generate the best sustainability outcome can be identified. This could assist rehabilitation specialists to formulate a suitable proportion of robotic assisted therapy in their treatment protocols. Lastly, there have been new studies28-33 published since these existing systematic reviews were conducted, and this review seeks to incorporate the most recent trial findings.
The diverse range of outcomes and study designs does not provide a clear determination of the effectiveness of robotic assisted rehabilitation, and it is the intent of this review to provide clarity to the discussion and offer useful recommendations for clinical practice. In this review, robotic assisted therapies for both upper and lower limbs will be evaluated to gain a detailed understanding of the effectiveness of robotic devices in these two areas to which a large proportion of rehabilitation efforts is devoted.
Types of participants
The current review will consider studies that include adult stroke patients (18 years and older) of all genders, regardless if stroke is due to ischemic or hemorrhagic causes. Patients with pre-existing impairments that are not caused by stroke, such as disabilities due to spinal cord injuries, Parkinson's disease, multiple sclerosis and traumatic brain injuries (caused by accidents, falls, infections, tumors or chemical toxins), will be excluded. Study participants may be new stroke patients or repeat stroke patients at acute, sub-acute or chronic stages of their stroke, so long as they have been accepted into a formal rehabilitation program. Only trials where the rehabilitation setting is either in-patient or outpatient will be included. Home rehabilitation patients will be excluded due to potential confounding of treatment adherence. The rehabilitation program can be conducted at hospitals, nursing facilities or across multi-centers, and only physical impairments related to upper and lower limbs will be considered.
Types of intervention(s)
The current review will consider studies that evaluate rehabilitation of stroke patients using interactive, automated electromechanical equipment (i.e. assistive robotics). The types of robotic assistive devices can be varied (e.g. either robotic exoskeletons or end-effectors for gait training), as long as interventions involve electromechanical assistive devices with automation, sensors and dynamic control logic that help patients regain their motor abilities. Interventions involving the devices below are not considered as robotic rehabilitation devices as they do not exhibit assistive automation that robotic devices have:
- Non-interactive devices that deliver passive motion such as treadmills, static body-weight-assisted treadmills, bicycles, static walking aids, static orthoses (such as ankle-foot orthoses addressing foot drop) or pure mechanical trainers (e.g. Reha-Slide, Reha-Slide duo).
- Standalone video games controlled solely by patient without automated assistive feature, such as Nintendo Wii.
- Rehabilitation programs using non-conventional therapies such as acupuncture, FES, transcranial direct current stimulation, motor imagery, biofeedback and CIT.
The intervention group can have or not have an added conventional physiotherapy component. If the intervention group has an added conventional physiotherapy component, this can involve non-interactive static devices.
The intervention should not contain other types of non-conventional therapy (e.g. FES, transcranial direct current stimulation, motor imagery or CIT). For multiple-arm studies, only results of the intervention arm with robotic assisted rehabilitation will be compared to the control arm. The intervention arm with a combination of robotic assistive devices and non-conventional therapy will be excluded from analysis.
As control groups, patients do not receive robotic assisted rehabilitation but receive only conventional physiotherapy or no physiotherapy treatment at all. The conventional physiotherapy treatment, however, may include non-interactive static devices (e.g. bicycles, treadmills and acupuncture).
The amount of therapy treatment in both intervention and control groups should be the same in terms of frequency and duration, that is, dose-matched. For example, if patients in the intervention group undergo 60 min of therapy using a robotic assistive device on top of a conventional physiotherapy component, then in the control group the patients should also undergo additional 60 min of conventional physiotherapy. Therefore, the total amount of therapy planned for patients (in terms of frequency per week, duration of a therapy session and overall rehabilitation period) should be the same for both groups. This does not apply if, in the control group, patients do not receive conventional physiotherapy.
For robotic assisted rehabilitation, the duration of therapy will consist of time for the patient to be set up with and be taken out of the robotic device, thus limiting the time for exercising the paretic limb (e.g. for Lokomat, a robotic exoskeleton device, actual exercise time can range from 35 to 40 min in a 60-min therapy session).34 Although the actual exercise duration can be less than the allocated duration of therapy, it can still be considered as being equivalent to the duration of a conventional physiotherapy session, as during a conventional therapy session not the full duration will be used for exercising. There will also be time for patients to prepare or rest in between exercises. In addition, some trials do not provide a breakdown of actual exercise duration but only the duration of a therapy session.
The current review will consider studies that include the outcome measure of the amount of motor movement demonstrated by the paretic limbs. To have an accurate point of reference across studies, only studies that have used scales that measure motor movement will be considered for the review.
For outcome measure of upper limbs, the Fugl-Meyer Assessment35 (upper extremity score) is the preferred scale. If a study does not use this scale, then an alternative measurement scale that quantifies upper limb motor movement (e.g. upper limb Motricity Index36) will be considered.
For outcome measure of lower limbs, the Functional Ambulation Category37 is the preferred scale. If a study does not use this scale, then an alternative measurement scale that quantifies walking will be considered, for example Barthel Index38 (ambulation item) or Functional Independence Measure39 (walking item).
Another aspect that will be examined is the level of ADLs attained after the intervention. For outcome measure of ADLs, Functional Independence Measure is the preferred scale. If a study does not use this scale, then an alternative measurement scale that quantifies the level of ADLs will be considered, for example, the Barthel Index. As ADLs involve usage of both upper and lower limbs, a global ADL measurement combining both subgroups of upper and lower limbs will be considered.
In clinical trials, patient outcomes at different stages of the rehabilitation process are measured. Usually measures are taken at pre-, mid- and post-intervention stages but some studies will continue to take follow-up measurements in the months after the end of the intervention therapy. For this review, measurements taken at pre- and post-intervention therapy will be included for analysis. Follow-up measurements taken after the intervention has ended will also be compared to measurements taken at the end of the intervention to examine the sustainability of the treatment effect.
Types of studies
The current review will consider experimental study designs of randomized controlled trials. For studies with crossover design, only the first study period will be considered for inclusion, as it is not clear if carry-over effects will have diminished sufficiently during the washout period. Also, given the context of rehabilitation where it is likely and desired for patients to retain the effects of rehabilitative training, the two different phases will have a dependence on each other.16 Thus, it will be confounding if both the first and second study periods of crossover trials are used to assess the effectiveness of robotic assistive devices.
The search strategy aims to find published and unpublished studies. A three-step search strategy will be utilized in this review. An initial limited search of PubMed will be undertaken followed by analysis of the text words contained in the title and abstract, and of the index terms used to describe the article. A second search using all identified keywords and index terms will then be undertaken across all included databases. Third, the reference list of all identified reports and articles will be searched for additional studies. Studies published in English will be considered for inclusion in this review and a date limit starting from 2000 will be set, as automated robotic devices have been increasingly used since 2000, together with an associated increase in the number of studies undertaken.
The databases to be searched include:
PubMed, Embase, CINAHL, Cochrane Central Register of Controlled Trials (CENTRAL) and PEDro (Physiotherapy Evidence Database).
The search for unpublished studies will include:
Mednar, ProQuest Dissertations & Theses, ClinicalTrials.gov, Google Scholar
Initial search terms to be used will be:
Robotics[mh] OR Robot*[tw] OR Exoskeleton Device[mh] OR Exoskeleton*[tw] OR Gait Trainer[tw] OR Lokomat[tw] AND Rehabilitation[mh] OR Rehabilitation[tw] OR Habilitation[tw] AND Stroke[mh] OR Stroke*[tw] OR “Cerebrovascular Accident” OR Cerebral[tw] OR “Cerebral Stroke” OR “Cerebrovascular Stroke” OR “Acute Stroke” OR “Sub-acute Stroke” OR “Subacute Stroke”
Assessment of methodological quality
Papers selected for retrieval will be assessed by two independent reviewers for methodological validity prior to inclusion in the review using standardized critical appraisal instruments from the Joanna Briggs Institute Meta Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) (Appendix I). Any disagreements that arise between the reviewers will be resolved through discussion or with a third reviewer.
Data will be extracted from papers included in the review using the standardized data extraction tool from JBI-MAStARI (Appendix II). The data extracted will include specific details about the interventions, populations, study methods and outcomes of significance to the review question and specific objectives. In the event of specific data of interest being absent from published articles, corresponding authors will be contacted to request access to the relevant data.
Quantitative data will, where possible, be pooled in statistical meta-analysis using JBI-MAStARI. All results will be subject to double data entry. Effect sizes expressed as odds ratio (for categorical data) and weighted/standardized mean differences (for continuous data) and their 95% confidence intervals will be calculated for analysis. Heterogeneity will be assessed statistically using I2 and the standard chi-square. Where statistical pooling is not possible, the findings will be presented in narrative form including tables and figures to aid in data presentation where appropriate. Sub-groups that may be considered for analysis include upper limb interventions, lower limb interventions, acute patients (i.e. less than three months post stroke), sub-acute/chronic patients, duration and frequency of intervention.
The current systematic review contributes toward the degree of Master of Clinical Science for the first author, through the Joanna Briggs Institute, The University of Adelaide.
Appendix I: Appraisal instruments
MAStARI appraisal instrument
Appendix II: Data extraction instruments
MAStARI data extraction instrument
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