A Comparative Study of Conventional Physiotherapy Versus Robotic Training Combined with Physiotherapy in Patients with Stroke U. Dundar, H. Toktas, O. Solak, A.M. Ulasli, and S. Eroglu Department of Physical Medicine and Rehabilitation, Faculty of Medicine, Afyon Kocatepe University, Afyon, Turkey Background: There has been a growing interest in the use of robotic therapy to improve walking ability in individuals following stroke. Objectives: The aim of this retrospective study was to compare conventional physiotherapy (CP) with robotic training (RT) combined with CP and to measure the effects on gait, balance, functional status, cognitive function, and quality of life in patient with stroke. Methods: We retrospectively identified 107 cases of new cerebral stroke. They were allocated into 2 groups. In the RT group (n = 36), patients received RT (Lokomat; 2 times per week) combined with CP (3 times per week) for at least 30 sessions. In the CP group (n = 71), patients received a program at least 30 sessions, 5 times per week. The evaluation parameters included modified Ashworth Spasticity Scale (MASS), Brunnstrom Recovery Scale (BRS), Functional Independence Measure (FIM), Functional Ambulation Categories (FAC), Berg Balance Scale (BBS), Mini-Mental State Examination (MMSE), and Short Form-36 (SF-36) Health Survey. Results: Posttreatment results showed significant improvements for all parameters (except lower extremity MASS scores) in both groups. However, when we compared the percentage changes of parameters at discharge relative to pretreatment values, improvements in FIM, MMSE, and all subparts of SF-36 were better in the RT group (P < .05). Comparison of posttreatment evaluation parameters for categorical variables showed that the lower extremity categories in the BRS were significantly better in the RT group than the CP group (P < .05). Conclusion: RT combined with CP produced better improvement in FIM, MMSE, BRS lower extremity categories, and all subparts of SF-36 of the patients with subacute and chronic stroke (up to 1 year) than the CP program. Key words: conventional physiotherapy, robotic rehabilitation, stroke
emiplegia is one of the most common impairments after stroke and contributes significantly to reduced gait performance. The recovery of independent walking is one of the major goals of rehabilitation after stroke.1 More than 30% of patients who have had a stroke do not achieve a complete motor recovery after the rehabilitation process.2 For this reason, new rehabilitation approaches are needed to improve quality of life in stroke patients.3 Conventional gait training may not restore a normal gait pattern in the majority of stroke patients.4 There has been a growing interest in using robotic therapy to improve walking ability in individuals following hemispheric stroke.5 Regarding rehabilitation strategies, the most
H
common robotic devices for gait restoration are based on task-specific repetitive movements, which have been shown to improve muscular strength, movement coordination, and locomotor retraining in neurologically impaired patients.6 Several robotic systems have been developed for automating locomotor training of individuals poststroke, such as the Lokomat7 and Gait Trainer.8 Although the underlying hypothesis of roboticassisted locomotor devices is that walking can be restored by imposing reciprocal, symmetrical motion approximating upright gait, there are insufficient data to indicate that this form of treatment will maximize recovery of independent ambulation in persons with incomplete neurological injury. In contrast, existing robotic devices appear
Corresponding author: Umit Dundar, MD, Physical Medicine and Rehabilitation, Faculty of Medicine, Kocatepe University, 03200 Afyon, Turkey; phone: +90 272 2463333; fax: +90 272 2463344; e-mail: [email protected]
Top Stroke Rehabil 2014;21(6):453–461 © 2014 Thomas Land Publishers, Inc. www.strokejournal.com doi: 10.1310/tsr2106-453
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to facilitate gait practice when the constraints on therapists and the amount of practice are limited.9 The aim of this retrospective study was to compare conventional physiotherapy (CP) with robotic training (RT) (Lokomat) combined with CP and to measure the effects on gait, balance, functional status, cognitive function, and quality of life in the patients with stroke. Methods Using a database of all patients admitted to Kocatepe University Physical Therapy and Rehabilitation Hospital (Afyon, Turkey) with a diagnosis of new ischemic or hemorrhagic stroke, we retrospectively identified all consecutive cases of new cerebral stroke admitted between January 1, 2011 and December 31, 2013. Inclusion criteria were a primary indication for admission for inpatient rehabilitation of first cerebral hemorrhage or cerebral infarction and availability of data on evaluation parameters. Patient selection criteria for retrospective analysis were as follows: a hemiparesis as the result of a first stroke according to the definitions of the World Health Organization, no prior stroke, no prior rehabilitation program, spasticity graded 2 or less in lower extremity according to modified Ashworth Spasticity Scale (MASS),10 no change in the spasticity medical treatment during admission or treatment, no other neurologic or orthopedic disorder, independent ambulation before the stroke, and no severe medical illnesses. The interval between the stroke and the start of the rehabilitation protocol had to be at least 28 days but no longer than 365 days. According to inclusion criteria, we observed that the first enrolled patient completed the rehabilitation program on March 1, 2011, and the last enrolled patient completed the rehabilitation on December 30, 2013. Enrolled patients participated in a rehabilitation program lasting at least 30 sessions consisting of either CP (5 times per week for 6 or more weeks) or RT (Lokomat; 2 times per week for 6 or more weeks) combined with CP (3 times per week for 6 or more weeks). Exclusion criteria were a primary indication for inpatient rehabilitation other than new cerebral stroke (including functional impairment related to previous stroke or other neurological disease), the use of functional electrical stimulation, absence of evaluation parameters data, rehabilitation program lasting less than 30 sessions, or a rehabilitation
program with different combination formula (eg, robotic training for 1, 3, or 4 times per week plus CP for 1, 2 or 4 times per week), and death during inpatient rehabilitation therapy. After cases had been identified, the medical records were reviewed, and demographic, clinical, and rehabilitation program features were obtained. According to rehabilitation program, the patients were assigned into 2 groups. In the first group (RT group, n = 36), patients received RT (Lokomat; 2 times per week for 6 or more weeks) combined with CP (3 times per week for 6 or more weeks) for at least 30 sessions. In the second group (CP group, n = 71), patients received a program for at least 30 sessions, 5 times per week for 6 or more weeks. Each session lasted 60 minutes in both groups. The CP rehabilitation program, shared by both groups, was a 60-minute program. The CP program focused on the facilitation of movements on the paretic side, range of motion, stretching exercises, upper and lower limb strengthening exercises, and improving balance, standing, sitting, transferring, and walking. According to the patient’s ability, the walking therapy focused on trunk stabilization, weight transfer to the paretic leg, and walking between parallel bars or on the ground. One to 2 therapists assisted the patients as needed in the CP program. In the RT group, robotic training was performed using the robotic-driven gait orthosis, the Lokomat, which includes a treadmill, a body weight–support system, and 2 lightweight robotic actuators that attach to the subject’s legs (Figure 1). The overall time of the Lokomat treatment, including the time to get in and get out of the orthosis, was 1 hour, whereas the net robotic gait training lasted 35 to 40 minutes. The speed of the treadmill could be adjusted from 0 km/h to 3 km/h. The velocity of the treadmill was set to the maximum speed tolerated by the patients during the treatments. Usually, at the beginning of the treatment, patients required intensive support of their body weight to stand on the treadmill without their knees buckling. Therefore, at the beginning of the treatment, approximately 40% to 50% of each subject’s body weight needed to be supported by the harness system. During the following walking sessions, body weight support was reduced in approximately 10% increments per session as tolerated without substantial knee buckling or toe drag.11
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Figure 1. A subject undergoing robot-driven gait therapy with the Lokomat device. Evaluation parameters
From the medical record, the evaluation parameters data were obtained at the time of admission and after discharge. The evaluation parameters included MASS, Brunnstrom Recovery Scale (BRS), Functional Independence Measure (FIM), Functional Ambulation Categories (FAC), Berg Balance Scale (BBS), Mini-Mental State Examination (MMSE), and Short Form-36 (SF-36) Health Survey. The MASS was used to test the muscle spasticity in lower extremity. The MASS is a validated scale grading the resistance of a relaxed limb to rapid passive stretch in 6 stages (range, 0-5; 0 = no increase in muscle tone; 5 = joint is rigid in flexion or extension).10 The BRS was used to assess lower extremity motor recovery. The 6 grades of the Brunnstrom stages for the lower extremity are (1) flaccidity, (2) synergy development (minimal voluntary movements), (3) voluntary synergistic movement
(combined hip flexion, knee flexion, and ankle dorsiflexion, both sitting and standing), (4) some movements deviating from synergy (knee flexion exceeding 90° and ankle dorsiflexion with the heel on the floor in the sitting position), (5) independence from basic synergies (isolated knee flexion with the hip extended and isolated ankle dorsiflexion with the knee extended in the standing position), and (6) isolated joint movements (hip abduction in the standing position and knee rotation with inversion and eversion of the ankle in the sitting position).12 The FIM is a scale that assesses the severity of motor and neuropsychological disability; it consists of 18 items classified into 6 domains: 4 motor and 2 cognitive. Each item envisages 7 levels of independent performance (7 = total independence and 1 = total dependence or inaccessible). The minimum score of FIM is 18, and the maximum score is 126, which is equivalent to total functional independence.13
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The FAC assesses gait ability. This scale includes 6 levels ranging from 0 to 5: 0 = patient can’t walk or requires help from 2 or more people to walk; 1 = patient requires firm, continuous support from 1 person who helps with carrying weight and with balance; 2 = patient needs continuous or intermittent support from 1 person to help with balance or coordination; 3 = able to walk with 1 assistant beside them to give them confidence without physical contact; 4 = independent walking but need some help with stairs or uneven ground; 5 = independent for gait function in any given place.11,14 The BBS is comprised of 14 static and dynamic balance tasks with a maximum score of 56. This measure demonstrates good reliability and validity in the patients with stroke.15 The MMSE was used to evaluate cognitive function. MMSE quantitatively assesses cognitive impairment on a scale from 0 to 30 based on answers to a variety of questions (11 different items). Lower scores of MMSE mean higher cognitive impairment.16 The SF-36 has been widely used to evaluate quality of life of people with different diseases. SF-36 includes 36 questions that are aggregated to score 8 domains: physical functioning, role limitations due to physical functioning, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and general mental health. The 8 domains were scored from 0 to 100 indicating worst to best possible health.17 The study was approved by the local ethics committee for Medical Research and Ethics at the Afyon Kocatepe University Faculty of Medicine (approval number, 2013/15-180; approval date, December 19, 2013). Statistical analysis
Distribution of data was evaluated by Kolmogorov-Smirnov test. All parametric (continuous variables) results were expressed as means and standard deviations for each group. Nonparametric variables were expressed as medians and minimum-maximum for each group. A level of significance of P < .05 (2-tailed) was accepted for this study. The chi-square test
was used for comparison of categorical variables. Numerical data with normal distribution were analyzed with independent sample t test, and numerical data without normal distribution and non-numerical data were analyzed with Mann-Whitney U test (for comparision of pretreatment data and the mean values of the percentage changes calculated for both groups). The paired t test for numerical data with normal distribution and Wilcoxon runk sum test for numerical data without normal distribution and nonnumerical data were used for comparison of pre- and posttreatment values within groups. All analyses were performed using the IBM SPSS for Windows 18.0 software program (IBM, Armonk, NY). Results One hundred seven cases were identified that fulfilled inclusion criteria (63 men, 44 women; 92 infarcts, 15 hemorrhages). According to their treatment protocols, they were allocated into 2 groups. Baseline characteristics of both groups are displayed in Table 1. There were no statistically significant differences in the demographic features and pretreatment evaluation parameters of the patients at admission. Posttreatment results (after discharge) showed significant improvement for all parameters (except lower extremity MASS scores) in both groups (Tables 2 and 3). However, when we compared the percentage changes of parameters (continuous variables) at discharge relative to pretreatment values, improvements in FIM, MMSE, and all subparts of SF-36 were better in the robotic rehabilitation group. Comparison of the percentage changes of BBS did not show a significant difference between 2 groups, although there was greater improvement in BBS in the RT group (Table 4). Comparision of posttreatment evaluation parameters for categorical variables showed that the lower extremity categories of the BRS were significantly better in the RT group than the CP group, although the medians in both groups were the same. Comparison of the other parameters (MASS and FAC) did not show a significant difference between the 2 groups (Table 5).
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Table 1. Demographic features and pretreatment values for evaluation parameters [median (minimummaximum) or mean ± SD] of the groups
Age, years Gender, F/M Time since stroke, months Hemiparesis side, R/L Infarct/hemorrhage Treatment sessions MASS, lower extremity BRS, lower extremity FAC FIM BBS MMSE SF-36a PF RL BP GH V SF RLEP GMH
Group 1: Robotic training + physiotherapy (n = 36)
Group 2: Conventional physiotherapy (n = 71)
P
66.5 ± 10.6 15/21 4.4 ± 2.8 16/20 31/5 32.3 ± 5.9 1 (0-2) 3 (1-6) 2 (0-4) 76.8 ± 20.6 20.6 ± 13.0 24.4 ± 2.1
65.4 ± 12.0 29/42 4.9 ± 3.5 33/38 61/10 31.8 ± 4.9 1 (0-2) 4 (1-6) 2 (0-4) 83.4 ± 22.9 21.7 ± 15.9 25.1 ± 2.4
.726 .935 .492 .842 .978 .466 .830 .151 .716 .149 .706 .104
49.8 ± 12.8 47.1 ± 13.0 48.1 ± 12.6 49.6 ± 12.7 48.4 ± 12.5 44.0 ± 11.2 42.5 ± 13.0 48.5 ± 11.7
48.8 ± 14.1 47.5 ± 13.8 48.5 ± 13.6 50.1 ± 15.2 47.4 ± 13.3 44.6 ± 12.1 43.1 ± 11.2 49.2 ± 13.5
.772 .863 .884 .873 .700 .793 .815 .790
Note: F/M = female/male; R/L = right/left; MASS = modified Asworth Spasticity Scale; BRS = Brunstrom Recovery Scale; FIM = Functional Independence Measure; BBS = Berg Balance Scale; FAC = Functional Ambulation Categories; MMSE = Mini-Mental State Examination; SF-36 = Short Form-36 Health Survey. a PF = Physical Function; RL = Role Limitations Due to Physical Functioning; BP = Bodily Pain; GH = General Health; V = Vitality; SF = Social Functioning; RLEP = Role Limitations Due to Emotional Problems; GMH = General Mental Health.
Table 2. Results [median (minimum-maximum) or mean ± SD] and statistical comparisons of the pretreatment and posttreatment evaluation parameters in robotic rehabilitation group (n = 36)
MASS, lower extremity BRS, lower extremity FAC FIM BBS MMSE SF-36a PF RL BP GH V SF RLEP GMH
Admission
Discharge
P
1 (0-2) 3 (1-6) 2 (0-4) 76.8 ± 20.6 20.6 ± 13.0 24.4 ± 2.1
1 (0-2) 4 (1-6) 3 (1-5) 95.1 ± 20.2 32.1 ± 14.6 26.8 ± 1.9
.850 .000 .000 .000 .000 .000
49.8 ± 12.8 47.1 ± 13.0 48.1 ± 12.6 49.6 ± 12.7 48.4 ± 12.5 44.0 ± 11.2 42.5 ± 13.0 48.5 ± 11.7
76.1 ± 10.6 74.9 ± 10.7 77.3 ± 10.1 78.1 ± 10.9 77.8 ± 10.4 73.7 ± 10.4 73.0 ± 11.1 78.5 ± 10.7
.000 .000 .000 .000 .000 .000 .000 .000
Note: MASS = modified Asworth Spasticity Scale; BRS = Brunstrom Recovery Scale; FIM = Functional Independence Measure; BBS = Berg Balance Scale; FAC = Functional Ambulation Categories; MMSE = Mini-Mental State Examination; SF-36 = Short Form-36 Health Survey. a PF = Physical Function; RL = Role Limitations Due to Physical Functioning; BP = Bodily Pain; GH = General Health; V = Vitality; SF = Social Functioning; RLEP = Role Limitations Due to Emotional Problems; GMH = General Mental Health.
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Table 3. Results [median (minimum-maximum) or mean ± SD] and statistical comparisons of the pretreatment and posttreatment evaluation parameters in conventional physiotherapy group (n = 71)
MASS, lower extremity BRS, lower extremity FAC FIM BBS MMSE SF-36a PF RL BP GH V SF RLEP GMH
Admission
Discharge
P
1 (0-2) 4 (1-6) 2 (0-4) 83.4 ± 22.9 21.7 ± 15.9 25.1 ± 2.4
1 (0-2) 4 (1-6) 3 (0-5) 95.3 ± 21.8 29.1 ± 16.2 26.5 ± 2.3
.357 .000 .000 .000 .000 .000
48.8 ±14.1 47.5 ±13.8 48.5 ± 13.6 50.1 ± 15.2 47.4 ± 13.3 44.6 ± 12.1 43.1 ± 11.2 49.2 ± 13.5
61.7 ± 12.8 60.5 ± 12.4 61.5 ± 12.6 63.4 ± 13.5 61.1 ± 12.5 58.7 ± 11.2 57.3 ± 11.4 62.8 ± 12.1
.000 .000 .000 .000 .000 .000 .000 .000
Note: MASS = modified Asworth Spasticity Scale; BRS = Brunstrom Recovery Scale; FIM = Functional Independence Measure; BBS = Berg Balance Scale; FAC = Functional Ambulation Categories; MMSE = MiniMental State Examination; SF-36 = Short Form-36 Health Survey. a
PF = Physical Function; RL = Role Limitations Due to Physical Functioning; BP = Bodily Pain; GH = General Health; V = Vitality; SF = Social Functioning; RLEP = Role Limitations Due to Emotional Problems; GMH = General Mental Health.
Table 4. Comparison of the 2 groups on the basis of the posttreatment percentage changes and difference scores relative to pretreatment values
FIM BBS MMSE SF-36a PF RL BP GH V SF RLEP GMH
Group 1: Robotic training + physiotherapy (n = 36)
Group 2: Conventional physiotherapy (n = 71)
P
0.26 ± 0.15 0.84 ± 1.0 0.10 ± 0.05
0.16 ± 0.14 0.63 ± 0.79 0.05 ± 0.04
.002 .262 .000
0.58 ± 0.30 0.66 ± 0.37 0.68 ± 0.37 0.64 ± 0.34 0.68 ± 0.37 0.74 ± 0.35 0.82 ± 0.43 0.68 ± 0.32
0.30 ± 0.20 0.31 ± 0.22 0.30 ± 0.21 0.31 ± 0.23 0.33 ± 0.22 0.35 ± 0.24 0.36 ± 0.25 0.31 ± 0.21
.000 .000 .000 .000 .000 .000 .000 .000
Note: FIM = Functional Independence Measure; BBS = Berg Balance Scale; MMSE = Mini-Mental State Examination; SF-36 = Short Form36 Health Survey. a PF = Physical Function; RL = Role Limitations Due to Physical Functioning; BP = Bodily Pain; GH = General Health; V = Vitality; SF = Social Functioning; RLEP = Role Limitations Due to Emotional Problems; GMH = General Mental Health.
Table 5. Comparison of the 2 groups on the basis of the posttreatment MASS, BRS, and FAC values [median (minimum-maximum)]
MASS, lower extremity BRS, lower extremity FAC
Group 1: Robotic training + physiotherapy (n = 36)
Group 2: Conventional physiotherapy (n = 71)
P
1 (0-2)
1 (0-2)
.830
4 (1-6)
4 (1-6)
.031
3 (1-5)
3 (0-5)
.577
Note: MASS = modified Asworth Spasticity Scale; BRS = Brunstrom Recovery Scale; FAC = Functional Ambulation Categories.
Discussion Three months after stroke, about a quarter of the patients were still bound to the wheelchair. In 60% of patients, the gait became slower to a degree that is practically important in normal life.18 Robotand system-supported motor rehabilitation opens new perspectives for stroke patients. It intensifies the therapy without placing excessive demands on the therapist. Currently available results appear to justify this development, even though the available data are still sparse.19 Despite 20 years of studies on robotic devices, including a system for body weight support for walking recovery after stroke, their true efficacy is unknown.20 Studies examining the clinical efficacy of robot-aided gait therapy have shown mixed results. In a controlled study, Schwartz et al showed that robotic locomotor therapy combined with regular physiotherapy produced promising effects on functional and motor outcomes in patients after subacute stroke as compared with regular physiotherapy alone at the end of a 6-week trial.11 In nonambulant patients with subacute stroke, electromechanically assisted walking training was more effective21 or equally effective but less strenuous22 than floor-assisted therapy out to 6 months of follow-up. In contrast, Duncan et al reported that 1-year follow-up of body weight–supported treadmill training was not superior to home-based rehabilitation in patients with autonomous ambulatory capacity.23 Morone et al found that more severely affected patients with subacute stroke were the ideal candidates for effective electromechanically assisted walking
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training.24 They aimed to identify who would have durable benefit from robotic gait training. They found that the higher efficacy of the combination of robotic therapy and conventional therapy versus conventional therapy alone that was observed at discharge only in patients with greater motor impairments was sustained after 2 years.25 Although the results are conflicting, there is a consensus that robot-aided gait training is not demonstrably superior to conventional therapy in participants who have preserved ambulatory capacity.26 Moreover, 2 major clinical trials in subacute and chronic stroke survivors revealed that robot-aided gait rehabilitation is substantially inferior to conventional rehabilitation.27,28 In another study, Kelley et al stated that walking measures did not show significant changes between groups (robotic-assisted body weight–supported treadmill training using the Lokomat vs overground gait training) in adults with chronic stroke.29 Positive results were, in fact, also found in chronic stroke patients.30 Ucar et al31 studied the potential efficacy of a robotic-assisted gait device, Lokomat, for treadmill training with partial body weight support in subjects with chronic hemiplegia. They found that the robotic-assisted device provides innovative possibilities for gait training in chronic hemiplegia rehabilitation by allowing training at higher intensity levels for longer durations than traditional home exercise. They used home exercise, which has already been proven to be less efficacious than any supervised exercise, in the control group. In a Cochrane review, the authors stated that 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. 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.32 Our study group was not a pure group of only patients with subacute or chronic stroke. In our retrospective study, patients with subacute and chronic stroke (up to 1 year) were enrolled. There was no limitation in patient selection criteria in terms of BRS, FIM, BBS, and FAC in our study. Posttreatment results (after discharge) showed significant improvement for all parameters (except lower extremity MASS scores) in both groups (Tables 2 and 3). Comparison of the FAC did not
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show a significant difference between the 2 groups after discharge (Table 5). However, when we compared the percentage changes of parameters (continuous variables) at discharge relative to pretreatment values, improvement in FIM, MMSE, and all subparts of SF-36 were better in the RT group (Table 4). The inclusion of a motor learning task is based on a large body of evidence that suggests that the human brain has a remarkable ability to undergo structural and functional alterations (neuroplasticity) in response to motor training.33,34 Because neuroplasticity is critical for recovery after a neurological injury, it has been suggested that the same mechanisms underlying motor learning may also contribute to motor recovery after stroke.35,36 There is evidence to support that plastic changes are also possible in the leg motor area following motor training.37-39 In our patients, robotic training not only improved BRS–lower extremity categories and FIM scores, but also improved MMSE and quality of life of the patients with stroke. By using neuroplasticity, robotic training may improve brain function better than conventional physiotherapy and this may result in a better perception of environment; eventually the patient may have better cognitive function and better quality of life. Quality of life was not extensively assessed in the studies that are mentioned above involving robotic therapy versus conventional physiotherapy. In our opinion, more prospective study involving robotic training is needed to evaluate the changes in quality of life and cognitive function of the patients with stroke. Paker et al40 studied the effects of robotic treadmill training on the motor symptoms and quality of life of patients with Parkinson’s disease. They found that robotic treadmill training was useful for improving the functional mobility, walking capacity, and motor symptoms in mild to moderate Parkinson’s disease. Robotic treadmill training provided a transient improvement in the quality of life during the treatment. In our study, comparison of the percentage changes of BBS did not show a significant difference between the 2 groups, although improvement in BBS was better in the robotic rehabilitation group. Swinnen et al41 investigated the effects of robot-assisted gait rehabilitation over balance in stroke patients. They stated that robotic-assisted gait rehabilitation could lead to improvements
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in balance in stroke patients; however, it is not clear whether the improvements are greater compared with those associated with other gait rehabilitation methods. They also stated that because a limited number of studies are available, more specific research (eg, randomized controlled trials with larger, specific populations) is necessary to draw stronger conclusions. Comparison of FAC did not show a significant difference between the 2 groups in this study. A possible explanation for this result may be the heterogeneity of the study group that contained patients with subacute and chronic stroke (up to 1 year). There was no limitation in patient selection criteria in terms of BRS, FIM, BBS, and FAC in our study. For example, if we had selected only nonambulatory patients, the results might be significantly different between the groups. There is not a consensus about the frequency (number of sessions per week) and optimal length of robotic training in patients with stroke. In our study, the RT group received robotic training (2 times per week for 6 or more weeks ) combined with the CP program (3 times per week for 6 or more weeks). Our combination formula produced greater improvement in FIM, MMSE, BRS–lower extremity categories, and all subparts of SF-36 in patients with stroke than the CP program. The major limitation of this study is the absence of a prospective randomization related
to the group allocation between robotic and conventional treatment. The other limitations are the low number of patients included in this study and the study group comprising patients with subacute and chronic stroke. Conclusion Although comparison of the FAC did not show a significant difference between the 2 groups after discharge, we conclude that RT combined with CP produces greater improvement in FIM, MMSE, BRS–lower extremity categories, and all subparts of SF-36 in the patients with subacute and chronic stroke (up to 1 year) than the CP program. However, some questions still need to be answered. First, the optimal length of time, frequency (number of sessions per week), and duration of robotic rehabilitation programs need to be established. Second, more prospective robotic training studies with longer follow-up periods and different treatment protocols are needed to evaluate the changes in gait, balance, functional status, quality of life, and cognitive function of the patients with stroke. Acknowledgments The authors have no conflicts of interest to disclose.
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11. Schwartz I, Sajin A, Fisher I, et al. The effectiveness of locomotor therapy using robotic assisted gait training in subacute stroke patients: A randomized controlled trial. PMR. 2009;1(6):516-523. 12. Eser F, Yavuzer G, Karakus D, Karaoglan B. The effect of balance training on motor recovery and ambulation after stroke: A randomized controlled trial. Eur J Phys Rehabil Med. 2008;44:19-25. 13. Center for Functional Assessment Research. Guide for Uniform Data Set for Medical Rehabilitation (Adult FIM), Version 4.0. Buffalo: New York State University of New York at Buffalo; 1993. 14. Holden MK, Gill KM, Magliozzi MR. Gait assessment for neurologically impaired patients. Phys Ther. 1986;66:1530-1539. 15. Berg K, Wood-Dauphinee S, Williams JI. The Balance Scale: Reliability assessment with elderly residents and patients with an acute stroke. Scand J Rehabil Med. 1995;27:27-36. 16. Lancu I, Olmer A. The Mini Mental State Examination-an up-to-date review. Harefuah. 2006;145:687-690,701. 17. Ware JE, Sherbourne CD. The MOS 36-Item Short-Form Health Survey (SF-36): I. Conceptual framework and item selection. Med Care. 1992;30(6):473-483. 18. Jorgensen HS, Nakayama H, Raaschou HO, Olsen TS. Recovery of walking function in stroke patients: The Copenhagen Stroke Study. Arch Phys Med Rehabil. 1995;76:27-32. 19. Hesse S, Mehrholz J, Werner C. Robot-assisted upper and lower limb rehabilitation after stroke walking and arm/hand function. Dtsch Arztebl Int. 2008;105(18):330-336. 20. Dobkin BH. Progressive staging of pilot studies to improve phase III. trials for motor interventions. Neurorehabil Neural Repair. 2009;23:197-206. 21. Ng MF, Tong RK, Li LS. A pilot study of randomized clinical controlled trial of gait training in subacute stroke patients with partial body-weight support electromechanical gait trainer and functional electrical stimulation: Six-month follow-up. Stroke. 2008;39:154-160. 22. Peurala SH, Airaksinen O, Huuskonen P, et al. Effects of intensive therapy using gait trainer or floor walking exercises early after stroke. J Rehabil Med. 2009;41:166-173. 23. Duncan PW, Sullivan KJ, Behrman AL, et al; LEAPS Investigative Team. Body-weight-supported treadmill rehabilitation after stroke. N Engl J Med. 2011;26:2026-2036. 24. Morone G, Bragoni M, Iosa M, et al. Who may benefit from robotic-assisted gait training? A randomized clinical trial in patients with subacute stroke. Neurorehabil Neural Repair. 2011;25:636-644. 25. Morone G, Iosa M, Bragoni M, et al. Who may have durable benefit from robotic gait training? A 2-year follow-up randomized controlled trial in patients with subacute stroke. Stroke. 2012;43:1140-1142. 26. Dickstein R. Rehabilitation of gait speed after stroke: A critical review of intervention approaches. Neurorehabil Neural Repair. 2008;22:649–660.
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27. Hidler J, Nichols D, Pelliccio M, et al. Multicenter randomized clinical trial evaluating the effectiveness of the Lokomat in subacute stroke. Neurorehabil Neural Repair. 2009;23:5-13. 28. Hornby TG, Campbell DD, Kahn JH, et al. Enhanced gait-related improvements after therapist- versus robotic-assisted locomotor training in subjects with chronic stroke: A randomized controlled study. Stroke. 2008;39:1786-1792. 29. Kelley CP, Childress J, Boake C, Noser EA. Overground and robotic-assisted locomotor training in adults with chronic stroke: A blinded randomized clinical trial. Disabil Rehabil Assistive Technol. 2013;8(2):161-168. 30. Geroin C, Picelli A, Munari D, et al. Combined transcranial direct current stimulation and robotassisted gait training in patients with chronic stroke: A preliminary comparison. Clin Rehabil. 2011;25:537-548. 31. Ucar DE, Paker N, Bugdayci D. Lokomat: Therapeutic chance for patients with chronic hemiplegia [published online ahead of print January 24, 2014]. NeuroRehabilitation. doi:10.3233/NRE141054 32. Mehrholz J, Elsner B, Werner C, Kugler J, Pohl M. Electromechanical-assisted training for walking after stroke. Cochrane Database Syst Rev. 2013;25;7:CD006185. 33. Bezzola L, Merillat S, Gaser C, Jancke L. Traininginduced neural plasticity in golf novices. J Neurosci. 2011;31:12444-12448. 34. Hanggi J, Koeneke S, Bezzola L, Jancke L. Structural neuroplasticity in the sensorimotor network of professional female ballet dancers. Hum Brain Mapp. 2010;31:1196-1206. 35. Kitago T, Krakauer JW. Motor learning principles for neurorehabilitation. Handb Clin Neurol. 2013;110:93-103. 36. Krakauer JW. Motor learning: Its relevance to stroke recovery and neurorehabilitation. Curr Opin Neurol. 2006;19:84-90. 37. Krishnan C, Ranganathan R, Kantak SS, Dhaher YY, Rymer WZ. Active robotic training improves locomotor function in a stroke survivor. J Neuroeng Rehabil. 2012;9:57. 38. Perez MA, Lungholt BK, Nyborg K, Nielsen JB. Motor skill training induces changes in the excitability of the leg cortical area in healthy humans. Exp Brain Res. 2004;159:197-205. 39. Krishnan C, Ranganathan R, Dhaher YY, Rymer WZ. A pilot study on the feasibility of robot-aided leg motor training to facilitate active participation. PLoS One. 2013;8(10):e77370. 40. Paker N, Bugdayci D, Goksenoglu G, Sen A, Kesiktas N. Effects of robotic treadmill training on functional mobility, walking capacity, motor symptoms and quality of life in ambulatory patients with Parkinson’s disease: A preliminary prospective longitudinal study. NeuroRehabilitation. 2013;33(2):323-328. 41. Swinnen E, Beckwee D, Meeusen R, Baeyens JP, Kerckhofs E. Does robot assisted gait rehabilitation improve balance in stroke patients? A systematic review. Top Stroke Rehabil. 2014;21(2):87-100.
emiplegia is one of the most common impairments after stroke and contributes significantly to reduced gait performance. The recovery of independent walking is one of the major goals of rehabilitation after stroke.1 More than 30% of patients who have had a stroke do not achieve a complete motor recovery after the rehabilitation process.2 For this reason, new rehabilitation approaches are needed to improve quality of life in stroke patients.3 Conventional gait training may not restore a normal gait pattern in the majority of stroke patients.4 There has been a growing interest in using robotic therapy to improve walking ability in individuals following hemispheric stroke.5 Regarding rehabilitation strategies, the most
H
common robotic devices for gait restoration are based on task-specific repetitive movements, which have been shown to improve muscular strength, movement coordination, and locomotor retraining in neurologically impaired patients.6 Several robotic systems have been developed for automating locomotor training of individuals poststroke, such as the Lokomat7 and Gait Trainer.8 Although the underlying hypothesis of roboticassisted locomotor devices is that walking can be restored by imposing reciprocal, symmetrical motion approximating upright gait, there are insufficient data to indicate that this form of treatment will maximize recovery of independent ambulation in persons with incomplete neurological injury. In contrast, existing robotic devices appear
Corresponding author: Umit Dundar, MD, Physical Medicine and Rehabilitation, Faculty of Medicine, Kocatepe University, 03200 Afyon, Turkey; phone: +90 272 2463333; fax: +90 272 2463344; e-mail: [email protected]
Top Stroke Rehabil 2014;21(6):453–461 © 2014 Thomas Land Publishers, Inc. www.strokejournal.com doi: 10.1310/tsr2106-453
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to facilitate gait practice when the constraints on therapists and the amount of practice are limited.9 The aim of this retrospective study was to compare conventional physiotherapy (CP) with robotic training (RT) (Lokomat) combined with CP and to measure the effects on gait, balance, functional status, cognitive function, and quality of life in the patients with stroke. Methods Using a database of all patients admitted to Kocatepe University Physical Therapy and Rehabilitation Hospital (Afyon, Turkey) with a diagnosis of new ischemic or hemorrhagic stroke, we retrospectively identified all consecutive cases of new cerebral stroke admitted between January 1, 2011 and December 31, 2013. Inclusion criteria were a primary indication for admission for inpatient rehabilitation of first cerebral hemorrhage or cerebral infarction and availability of data on evaluation parameters. Patient selection criteria for retrospective analysis were as follows: a hemiparesis as the result of a first stroke according to the definitions of the World Health Organization, no prior stroke, no prior rehabilitation program, spasticity graded 2 or less in lower extremity according to modified Ashworth Spasticity Scale (MASS),10 no change in the spasticity medical treatment during admission or treatment, no other neurologic or orthopedic disorder, independent ambulation before the stroke, and no severe medical illnesses. The interval between the stroke and the start of the rehabilitation protocol had to be at least 28 days but no longer than 365 days. According to inclusion criteria, we observed that the first enrolled patient completed the rehabilitation program on March 1, 2011, and the last enrolled patient completed the rehabilitation on December 30, 2013. Enrolled patients participated in a rehabilitation program lasting at least 30 sessions consisting of either CP (5 times per week for 6 or more weeks) or RT (Lokomat; 2 times per week for 6 or more weeks) combined with CP (3 times per week for 6 or more weeks). Exclusion criteria were a primary indication for inpatient rehabilitation other than new cerebral stroke (including functional impairment related to previous stroke or other neurological disease), the use of functional electrical stimulation, absence of evaluation parameters data, rehabilitation program lasting less than 30 sessions, or a rehabilitation
program with different combination formula (eg, robotic training for 1, 3, or 4 times per week plus CP for 1, 2 or 4 times per week), and death during inpatient rehabilitation therapy. After cases had been identified, the medical records were reviewed, and demographic, clinical, and rehabilitation program features were obtained. According to rehabilitation program, the patients were assigned into 2 groups. In the first group (RT group, n = 36), patients received RT (Lokomat; 2 times per week for 6 or more weeks) combined with CP (3 times per week for 6 or more weeks) for at least 30 sessions. In the second group (CP group, n = 71), patients received a program for at least 30 sessions, 5 times per week for 6 or more weeks. Each session lasted 60 minutes in both groups. The CP rehabilitation program, shared by both groups, was a 60-minute program. The CP program focused on the facilitation of movements on the paretic side, range of motion, stretching exercises, upper and lower limb strengthening exercises, and improving balance, standing, sitting, transferring, and walking. According to the patient’s ability, the walking therapy focused on trunk stabilization, weight transfer to the paretic leg, and walking between parallel bars or on the ground. One to 2 therapists assisted the patients as needed in the CP program. In the RT group, robotic training was performed using the robotic-driven gait orthosis, the Lokomat, which includes a treadmill, a body weight–support system, and 2 lightweight robotic actuators that attach to the subject’s legs (Figure 1). The overall time of the Lokomat treatment, including the time to get in and get out of the orthosis, was 1 hour, whereas the net robotic gait training lasted 35 to 40 minutes. The speed of the treadmill could be adjusted from 0 km/h to 3 km/h. The velocity of the treadmill was set to the maximum speed tolerated by the patients during the treatments. Usually, at the beginning of the treatment, patients required intensive support of their body weight to stand on the treadmill without their knees buckling. Therefore, at the beginning of the treatment, approximately 40% to 50% of each subject’s body weight needed to be supported by the harness system. During the following walking sessions, body weight support was reduced in approximately 10% increments per session as tolerated without substantial knee buckling or toe drag.11
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Figure 1. A subject undergoing robot-driven gait therapy with the Lokomat device. Evaluation parameters
From the medical record, the evaluation parameters data were obtained at the time of admission and after discharge. The evaluation parameters included MASS, Brunnstrom Recovery Scale (BRS), Functional Independence Measure (FIM), Functional Ambulation Categories (FAC), Berg Balance Scale (BBS), Mini-Mental State Examination (MMSE), and Short Form-36 (SF-36) Health Survey. The MASS was used to test the muscle spasticity in lower extremity. The MASS is a validated scale grading the resistance of a relaxed limb to rapid passive stretch in 6 stages (range, 0-5; 0 = no increase in muscle tone; 5 = joint is rigid in flexion or extension).10 The BRS was used to assess lower extremity motor recovery. The 6 grades of the Brunnstrom stages for the lower extremity are (1) flaccidity, (2) synergy development (minimal voluntary movements), (3) voluntary synergistic movement
(combined hip flexion, knee flexion, and ankle dorsiflexion, both sitting and standing), (4) some movements deviating from synergy (knee flexion exceeding 90° and ankle dorsiflexion with the heel on the floor in the sitting position), (5) independence from basic synergies (isolated knee flexion with the hip extended and isolated ankle dorsiflexion with the knee extended in the standing position), and (6) isolated joint movements (hip abduction in the standing position and knee rotation with inversion and eversion of the ankle in the sitting position).12 The FIM is a scale that assesses the severity of motor and neuropsychological disability; it consists of 18 items classified into 6 domains: 4 motor and 2 cognitive. Each item envisages 7 levels of independent performance (7 = total independence and 1 = total dependence or inaccessible). The minimum score of FIM is 18, and the maximum score is 126, which is equivalent to total functional independence.13
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The FAC assesses gait ability. This scale includes 6 levels ranging from 0 to 5: 0 = patient can’t walk or requires help from 2 or more people to walk; 1 = patient requires firm, continuous support from 1 person who helps with carrying weight and with balance; 2 = patient needs continuous or intermittent support from 1 person to help with balance or coordination; 3 = able to walk with 1 assistant beside them to give them confidence without physical contact; 4 = independent walking but need some help with stairs or uneven ground; 5 = independent for gait function in any given place.11,14 The BBS is comprised of 14 static and dynamic balance tasks with a maximum score of 56. This measure demonstrates good reliability and validity in the patients with stroke.15 The MMSE was used to evaluate cognitive function. MMSE quantitatively assesses cognitive impairment on a scale from 0 to 30 based on answers to a variety of questions (11 different items). Lower scores of MMSE mean higher cognitive impairment.16 The SF-36 has been widely used to evaluate quality of life of people with different diseases. SF-36 includes 36 questions that are aggregated to score 8 domains: physical functioning, role limitations due to physical functioning, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and general mental health. The 8 domains were scored from 0 to 100 indicating worst to best possible health.17 The study was approved by the local ethics committee for Medical Research and Ethics at the Afyon Kocatepe University Faculty of Medicine (approval number, 2013/15-180; approval date, December 19, 2013). Statistical analysis
Distribution of data was evaluated by Kolmogorov-Smirnov test. All parametric (continuous variables) results were expressed as means and standard deviations for each group. Nonparametric variables were expressed as medians and minimum-maximum for each group. A level of significance of P < .05 (2-tailed) was accepted for this study. The chi-square test
was used for comparison of categorical variables. Numerical data with normal distribution were analyzed with independent sample t test, and numerical data without normal distribution and non-numerical data were analyzed with Mann-Whitney U test (for comparision of pretreatment data and the mean values of the percentage changes calculated for both groups). The paired t test for numerical data with normal distribution and Wilcoxon runk sum test for numerical data without normal distribution and nonnumerical data were used for comparison of pre- and posttreatment values within groups. All analyses were performed using the IBM SPSS for Windows 18.0 software program (IBM, Armonk, NY). Results One hundred seven cases were identified that fulfilled inclusion criteria (63 men, 44 women; 92 infarcts, 15 hemorrhages). According to their treatment protocols, they were allocated into 2 groups. Baseline characteristics of both groups are displayed in Table 1. There were no statistically significant differences in the demographic features and pretreatment evaluation parameters of the patients at admission. Posttreatment results (after discharge) showed significant improvement for all parameters (except lower extremity MASS scores) in both groups (Tables 2 and 3). However, when we compared the percentage changes of parameters (continuous variables) at discharge relative to pretreatment values, improvements in FIM, MMSE, and all subparts of SF-36 were better in the robotic rehabilitation group. Comparison of the percentage changes of BBS did not show a significant difference between 2 groups, although there was greater improvement in BBS in the RT group (Table 4). Comparision of posttreatment evaluation parameters for categorical variables showed that the lower extremity categories of the BRS were significantly better in the RT group than the CP group, although the medians in both groups were the same. Comparison of the other parameters (MASS and FAC) did not show a significant difference between the 2 groups (Table 5).
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Table 1. Demographic features and pretreatment values for evaluation parameters [median (minimummaximum) or mean ± SD] of the groups
Age, years Gender, F/M Time since stroke, months Hemiparesis side, R/L Infarct/hemorrhage Treatment sessions MASS, lower extremity BRS, lower extremity FAC FIM BBS MMSE SF-36a PF RL BP GH V SF RLEP GMH
Group 1: Robotic training + physiotherapy (n = 36)
Group 2: Conventional physiotherapy (n = 71)
P
66.5 ± 10.6 15/21 4.4 ± 2.8 16/20 31/5 32.3 ± 5.9 1 (0-2) 3 (1-6) 2 (0-4) 76.8 ± 20.6 20.6 ± 13.0 24.4 ± 2.1
65.4 ± 12.0 29/42 4.9 ± 3.5 33/38 61/10 31.8 ± 4.9 1 (0-2) 4 (1-6) 2 (0-4) 83.4 ± 22.9 21.7 ± 15.9 25.1 ± 2.4
.726 .935 .492 .842 .978 .466 .830 .151 .716 .149 .706 .104
49.8 ± 12.8 47.1 ± 13.0 48.1 ± 12.6 49.6 ± 12.7 48.4 ± 12.5 44.0 ± 11.2 42.5 ± 13.0 48.5 ± 11.7
48.8 ± 14.1 47.5 ± 13.8 48.5 ± 13.6 50.1 ± 15.2 47.4 ± 13.3 44.6 ± 12.1 43.1 ± 11.2 49.2 ± 13.5
.772 .863 .884 .873 .700 .793 .815 .790
Note: F/M = female/male; R/L = right/left; MASS = modified Asworth Spasticity Scale; BRS = Brunstrom Recovery Scale; FIM = Functional Independence Measure; BBS = Berg Balance Scale; FAC = Functional Ambulation Categories; MMSE = Mini-Mental State Examination; SF-36 = Short Form-36 Health Survey. a PF = Physical Function; RL = Role Limitations Due to Physical Functioning; BP = Bodily Pain; GH = General Health; V = Vitality; SF = Social Functioning; RLEP = Role Limitations Due to Emotional Problems; GMH = General Mental Health.
Table 2. Results [median (minimum-maximum) or mean ± SD] and statistical comparisons of the pretreatment and posttreatment evaluation parameters in robotic rehabilitation group (n = 36)
MASS, lower extremity BRS, lower extremity FAC FIM BBS MMSE SF-36a PF RL BP GH V SF RLEP GMH
Admission
Discharge
P
1 (0-2) 3 (1-6) 2 (0-4) 76.8 ± 20.6 20.6 ± 13.0 24.4 ± 2.1
1 (0-2) 4 (1-6) 3 (1-5) 95.1 ± 20.2 32.1 ± 14.6 26.8 ± 1.9
.850 .000 .000 .000 .000 .000
49.8 ± 12.8 47.1 ± 13.0 48.1 ± 12.6 49.6 ± 12.7 48.4 ± 12.5 44.0 ± 11.2 42.5 ± 13.0 48.5 ± 11.7
76.1 ± 10.6 74.9 ± 10.7 77.3 ± 10.1 78.1 ± 10.9 77.8 ± 10.4 73.7 ± 10.4 73.0 ± 11.1 78.5 ± 10.7
.000 .000 .000 .000 .000 .000 .000 .000
Note: MASS = modified Asworth Spasticity Scale; BRS = Brunstrom Recovery Scale; FIM = Functional Independence Measure; BBS = Berg Balance Scale; FAC = Functional Ambulation Categories; MMSE = Mini-Mental State Examination; SF-36 = Short Form-36 Health Survey. a PF = Physical Function; RL = Role Limitations Due to Physical Functioning; BP = Bodily Pain; GH = General Health; V = Vitality; SF = Social Functioning; RLEP = Role Limitations Due to Emotional Problems; GMH = General Mental Health.
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Table 3. Results [median (minimum-maximum) or mean ± SD] and statistical comparisons of the pretreatment and posttreatment evaluation parameters in conventional physiotherapy group (n = 71)
MASS, lower extremity BRS, lower extremity FAC FIM BBS MMSE SF-36a PF RL BP GH V SF RLEP GMH
Admission
Discharge
P
1 (0-2) 4 (1-6) 2 (0-4) 83.4 ± 22.9 21.7 ± 15.9 25.1 ± 2.4
1 (0-2) 4 (1-6) 3 (0-5) 95.3 ± 21.8 29.1 ± 16.2 26.5 ± 2.3
.357 .000 .000 .000 .000 .000
48.8 ±14.1 47.5 ±13.8 48.5 ± 13.6 50.1 ± 15.2 47.4 ± 13.3 44.6 ± 12.1 43.1 ± 11.2 49.2 ± 13.5
61.7 ± 12.8 60.5 ± 12.4 61.5 ± 12.6 63.4 ± 13.5 61.1 ± 12.5 58.7 ± 11.2 57.3 ± 11.4 62.8 ± 12.1
.000 .000 .000 .000 .000 .000 .000 .000
Note: MASS = modified Asworth Spasticity Scale; BRS = Brunstrom Recovery Scale; FIM = Functional Independence Measure; BBS = Berg Balance Scale; FAC = Functional Ambulation Categories; MMSE = MiniMental State Examination; SF-36 = Short Form-36 Health Survey. a
PF = Physical Function; RL = Role Limitations Due to Physical Functioning; BP = Bodily Pain; GH = General Health; V = Vitality; SF = Social Functioning; RLEP = Role Limitations Due to Emotional Problems; GMH = General Mental Health.
Table 4. Comparison of the 2 groups on the basis of the posttreatment percentage changes and difference scores relative to pretreatment values
FIM BBS MMSE SF-36a PF RL BP GH V SF RLEP GMH
Group 1: Robotic training + physiotherapy (n = 36)
Group 2: Conventional physiotherapy (n = 71)
P
0.26 ± 0.15 0.84 ± 1.0 0.10 ± 0.05
0.16 ± 0.14 0.63 ± 0.79 0.05 ± 0.04
.002 .262 .000
0.58 ± 0.30 0.66 ± 0.37 0.68 ± 0.37 0.64 ± 0.34 0.68 ± 0.37 0.74 ± 0.35 0.82 ± 0.43 0.68 ± 0.32
0.30 ± 0.20 0.31 ± 0.22 0.30 ± 0.21 0.31 ± 0.23 0.33 ± 0.22 0.35 ± 0.24 0.36 ± 0.25 0.31 ± 0.21
.000 .000 .000 .000 .000 .000 .000 .000
Note: FIM = Functional Independence Measure; BBS = Berg Balance Scale; MMSE = Mini-Mental State Examination; SF-36 = Short Form36 Health Survey. a PF = Physical Function; RL = Role Limitations Due to Physical Functioning; BP = Bodily Pain; GH = General Health; V = Vitality; SF = Social Functioning; RLEP = Role Limitations Due to Emotional Problems; GMH = General Mental Health.
Table 5. Comparison of the 2 groups on the basis of the posttreatment MASS, BRS, and FAC values [median (minimum-maximum)]
MASS, lower extremity BRS, lower extremity FAC
Group 1: Robotic training + physiotherapy (n = 36)
Group 2: Conventional physiotherapy (n = 71)
P
1 (0-2)
1 (0-2)
.830
4 (1-6)
4 (1-6)
.031
3 (1-5)
3 (0-5)
.577
Note: MASS = modified Asworth Spasticity Scale; BRS = Brunstrom Recovery Scale; FAC = Functional Ambulation Categories.
Discussion Three months after stroke, about a quarter of the patients were still bound to the wheelchair. In 60% of patients, the gait became slower to a degree that is practically important in normal life.18 Robotand system-supported motor rehabilitation opens new perspectives for stroke patients. It intensifies the therapy without placing excessive demands on the therapist. Currently available results appear to justify this development, even though the available data are still sparse.19 Despite 20 years of studies on robotic devices, including a system for body weight support for walking recovery after stroke, their true efficacy is unknown.20 Studies examining the clinical efficacy of robot-aided gait therapy have shown mixed results. In a controlled study, Schwartz et al showed that robotic locomotor therapy combined with regular physiotherapy produced promising effects on functional and motor outcomes in patients after subacute stroke as compared with regular physiotherapy alone at the end of a 6-week trial.11 In nonambulant patients with subacute stroke, electromechanically assisted walking training was more effective21 or equally effective but less strenuous22 than floor-assisted therapy out to 6 months of follow-up. In contrast, Duncan et al reported that 1-year follow-up of body weight–supported treadmill training was not superior to home-based rehabilitation in patients with autonomous ambulatory capacity.23 Morone et al found that more severely affected patients with subacute stroke were the ideal candidates for effective electromechanically assisted walking
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training.24 They aimed to identify who would have durable benefit from robotic gait training. They found that the higher efficacy of the combination of robotic therapy and conventional therapy versus conventional therapy alone that was observed at discharge only in patients with greater motor impairments was sustained after 2 years.25 Although the results are conflicting, there is a consensus that robot-aided gait training is not demonstrably superior to conventional therapy in participants who have preserved ambulatory capacity.26 Moreover, 2 major clinical trials in subacute and chronic stroke survivors revealed that robot-aided gait rehabilitation is substantially inferior to conventional rehabilitation.27,28 In another study, Kelley et al stated that walking measures did not show significant changes between groups (robotic-assisted body weight–supported treadmill training using the Lokomat vs overground gait training) in adults with chronic stroke.29 Positive results were, in fact, also found in chronic stroke patients.30 Ucar et al31 studied the potential efficacy of a robotic-assisted gait device, Lokomat, for treadmill training with partial body weight support in subjects with chronic hemiplegia. They found that the robotic-assisted device provides innovative possibilities for gait training in chronic hemiplegia rehabilitation by allowing training at higher intensity levels for longer durations than traditional home exercise. They used home exercise, which has already been proven to be less efficacious than any supervised exercise, in the control group. In a Cochrane review, the authors stated that 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. 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.32 Our study group was not a pure group of only patients with subacute or chronic stroke. In our retrospective study, patients with subacute and chronic stroke (up to 1 year) were enrolled. There was no limitation in patient selection criteria in terms of BRS, FIM, BBS, and FAC in our study. Posttreatment results (after discharge) showed significant improvement for all parameters (except lower extremity MASS scores) in both groups (Tables 2 and 3). Comparison of the FAC did not
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show a significant difference between the 2 groups after discharge (Table 5). However, when we compared the percentage changes of parameters (continuous variables) at discharge relative to pretreatment values, improvement in FIM, MMSE, and all subparts of SF-36 were better in the RT group (Table 4). The inclusion of a motor learning task is based on a large body of evidence that suggests that the human brain has a remarkable ability to undergo structural and functional alterations (neuroplasticity) in response to motor training.33,34 Because neuroplasticity is critical for recovery after a neurological injury, it has been suggested that the same mechanisms underlying motor learning may also contribute to motor recovery after stroke.35,36 There is evidence to support that plastic changes are also possible in the leg motor area following motor training.37-39 In our patients, robotic training not only improved BRS–lower extremity categories and FIM scores, but also improved MMSE and quality of life of the patients with stroke. By using neuroplasticity, robotic training may improve brain function better than conventional physiotherapy and this may result in a better perception of environment; eventually the patient may have better cognitive function and better quality of life. Quality of life was not extensively assessed in the studies that are mentioned above involving robotic therapy versus conventional physiotherapy. In our opinion, more prospective study involving robotic training is needed to evaluate the changes in quality of life and cognitive function of the patients with stroke. Paker et al40 studied the effects of robotic treadmill training on the motor symptoms and quality of life of patients with Parkinson’s disease. They found that robotic treadmill training was useful for improving the functional mobility, walking capacity, and motor symptoms in mild to moderate Parkinson’s disease. Robotic treadmill training provided a transient improvement in the quality of life during the treatment. In our study, comparison of the percentage changes of BBS did not show a significant difference between the 2 groups, although improvement in BBS was better in the robotic rehabilitation group. Swinnen et al41 investigated the effects of robot-assisted gait rehabilitation over balance in stroke patients. They stated that robotic-assisted gait rehabilitation could lead to improvements
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in balance in stroke patients; however, it is not clear whether the improvements are greater compared with those associated with other gait rehabilitation methods. They also stated that because a limited number of studies are available, more specific research (eg, randomized controlled trials with larger, specific populations) is necessary to draw stronger conclusions. Comparison of FAC did not show a significant difference between the 2 groups in this study. A possible explanation for this result may be the heterogeneity of the study group that contained patients with subacute and chronic stroke (up to 1 year). There was no limitation in patient selection criteria in terms of BRS, FIM, BBS, and FAC in our study. For example, if we had selected only nonambulatory patients, the results might be significantly different between the groups. There is not a consensus about the frequency (number of sessions per week) and optimal length of robotic training in patients with stroke. In our study, the RT group received robotic training (2 times per week for 6 or more weeks ) combined with the CP program (3 times per week for 6 or more weeks). Our combination formula produced greater improvement in FIM, MMSE, BRS–lower extremity categories, and all subparts of SF-36 in patients with stroke than the CP program. The major limitation of this study is the absence of a prospective randomization related
to the group allocation between robotic and conventional treatment. The other limitations are the low number of patients included in this study and the study group comprising patients with subacute and chronic stroke. Conclusion Although comparison of the FAC did not show a significant difference between the 2 groups after discharge, we conclude that RT combined with CP produces greater improvement in FIM, MMSE, BRS–lower extremity categories, and all subparts of SF-36 in the patients with subacute and chronic stroke (up to 1 year) than the CP program. However, some questions still need to be answered. First, the optimal length of time, frequency (number of sessions per week), and duration of robotic rehabilitation programs need to be established. Second, more prospective robotic training studies with longer follow-up periods and different treatment protocols are needed to evaluate the changes in gait, balance, functional status, quality of life, and cognitive function of the patients with stroke. Acknowledgments The authors have no conflicts of interest to disclose.
REFERENCES 1. Roger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and stroke statistics–2011 update: A report from the American Heart Association. Circulation. 2011;123:e18-e209. 2. Fernandez de Bobadilla J, Sicras-Mainar A, NavarroArtieda R, et al. Estimation of the prevalence, incidence, comorbidities and direct costs associated to stroke patients requiring care in an area of the Spanish population. Rev Neurol. 2008;46:397-405. 3. Conesa L, Costa U, Morales E, et al. An observational report of intensive robotic and manual gait training in sub-acute stroke. J NeuroEngineering Rehabil. 2012;9:13. 4. Dohring ME, Daly JJ. Automatic synchronization of functional electrical stimulation and robotic assisted treadmill training. IEEE Trans Neural Syst Rehabil Engineering. 2008;16:310-313. 5. Riener R, Lunenburger L, Jezernik S, Anderschitz M, Colombo G, Dietz V. Patient-cooperative strategies for robot-aided treadmill training: First
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