Modulation of corticospinal excitability related to the forearm muscle during robot-assisted stepping in humans.

In recent years, the neural control mechanisms of the arms and legs during human bipedal walking have been clarified. Rhythmic leg stepping leads to suppression of monosynaptic reflex excitability in forearm muscles. However, it is unknown whether and how corticospinal excitability of the forearm muscle is modulated during leg stepping. The purpose of the present study was to investigate the excitability of the corticospinal tract in the forearm muscle during passive and voluntary stepping. To compare the neural effects on corticospinal excitability to those on monosynaptic reflex excitability, the present study also assessed the excitability of the H-reflex in the forearm muscle during both types of stepping. A robotic gait orthosis was used to produce leg stepping movements similar to those of normal walking. Motor evoked potentials (MEPs) and H-reflexes were evoked in the flexor carpi radialis (FCR) muscle during passive and voluntary stepping. The results showed that FCR MEP amplitudes were significantly enhanced during the mid-stance and terminal-swing phases of voluntary stepping, while there was no significant difference between the phases during passive stepping. Conversely, the FCR H-reflex was suppressed during both voluntary and passive stepping, compared to the standing condition. The present results demonstrated that voluntary commands to leg muscles, combined with somatosensory inputs, may facilitate corticospinal excitability in the forearm muscle, and that somatosensory inputs during walking play a major role in monosynaptic reflex suppression in forearm muscle.

Cost-effectiveness analysis of robot-assisted gait training in patients with bilateral spastic cerebral palsy.

BACKGROUND: To date, there have been no published studies evaluating the cost-effectiveness of robot-assisted gait training (RAGT) in adolescent and adult patients with cerebral palsy (CP). The study´s aim was to analyse the cost-effectiveness of RAGT versus conventional kinesiotherapy (CON) from the health care provider's perspective. METHODS: We expressed the cost-effectiveness of RAGT in the Lokomat® system after analysing the costs and effects of RAGT and conventional therapy through the Incremental Cost-Effectiveness Ratio (ICER) based on a bicentric randomized controlled study, in which we demonstrated that the intensive RAGT regimen is more effective than conventional therapy in terms of improvements in gross motor functions in adolescent and adult patients with bilateral spastic CP. RESULTS: According to the calculated ICER ratio for Lokomat®, an additional improvement per unit of effect (1% in GMFM), compared to conventional therapy, results in an average cost increase of EUR70.38 per patient in a therapeutic block consisting of 20 TUs (Therapeutic Units). CONCLUSION: However, from the comprehensive analysis of the results and evaluation of the long-term effects, it follows that RAGT applied in adolescent and adult patients with bilateral spastic CP is not only more effective in terms of evaluation of monitored clinical parameters, but in the long term it is also more cost-effective compared to conventional therapy.

Feasibility and outcomes of supplemental gait training by robotic and conventional means in acute stroke rehabilitation.

INTRODUCTION: Practicality of implementation and dosing of supplemental gait training in an acute stroke inpatient rehabilitation setting are not well studied but can have positive impact on outcomes. OBJECTIVES: To determine the feasibility of early, intense supplemental gait training in inpatient stroke rehabilitation, compare functional outcomes and the specific mode of delivery. DESIGN AND SETTING: Assessor blinded, randomized controlled trial in a tertiary Inpatient Rehabilitation Facility. PARTICIPANTS: Thirty acute post-stroke patients with unilateral hemiparesis (≥ 18 years of age with a lower limb MAS ≤ 3). INTERVENTION: Lokomat® or conventional gait training (CGT) in addition to standard mandated therapy time. MAIN OUTCOME MEASURES: Number of therapy sessions; adverse events; functional independence measure (FIM motor); functional ambulation category (FAC); passive range of motion (PROM); modified Ashworth scale (MAS); 5 times sit-to-stand (5x-STS); 10-m walk test (10MWT); 2-min walk test (2MWT) were assessed before (pre) and after training (post). RESULTS: The desired supplemental therapy was implemented during normal care delivery hours and the patients generally tolerated the sessions well. Both groups improved markedly on several measures; the CGT group obtained nearly 45% more supplemental sessions (12.8) than the Lokomat® group (8.9). Both groups showed greater FIM improvement scores (discharge - admission) than those from a reference group receiving no supplemental therapy. An overarching statistical comparison between methods was skewed towards a differential benefit (but not significant) in the Lokomat® group with medium effect sizes. By observation, the robotic group completed a greater number of steps, on average. These results provide some evidence for Lokomat® being a more efficient tool for gait retraining by providing a more optimal therapy "dose". CONCLUSIONS: With careful planning, supplemental therapy was possible with minimal intrusion to schedules and was well tolerated. Participants showed meaningful functional improvement with relatively little supplemental therapy over a relatively short time in study.

Assessing walking ability using a robotic gait trainer: opportunities and limitations of assist-as-needed control in spinal cord injury.

BACKGROUND: Walking impairments are a common consequence of neurological disorders and are assessed with clinical scores that suffer from several limitations. Robot-assisted locomotor training is becoming an established clinical practice. Besides training, these devices could be used for assessing walking ability in a controlled environment. Here, we propose an adaptive assist-as-needed (AAN) control for a treadmill-based robotic exoskeleton, the Lokomat, that reduces the support of the device (body weight support and impedance of the robotic joints) based on the ability of the patient to follow a gait pattern displayed on screen. We hypothesize that the converged values of robotic support provide valid and reliable information about individuals' walking ability. METHODS: Fifteen participants with spinal cord injury and twelve controls used the AAN software in the Lokomat twice within a week and were assessed using clinical scores (10MWT, TUG). We used a regression method to identify the robotic measure that could provide the most relevant information about walking ability and determined the test-retest reliability. We also checked whether this result could be extrapolated to non-ambulatory and to unimpaired subjects. RESULTS: The AAN controller could be used in patients with different injury severity levels. A linear model based on one variable (robotic knee stiffness at terminal swing) could explain 74% of the variance in the 10MWT and 61% in the TUG in ambulatory patients and showed good relative reliability but poor absolute reliability. Adding the variable 'maximum hip flexor torque' to the model increased the explained variance above 85%. This did not extend to non-ambulatory nor to able-bodied individuals, where variables related to stance phase and to push-off phase seem more relevant. CONCLUSIONS: The novel AAN software for the Lokomat can be used to quantify the support required by a patient while performing robotic gait training. The adaptive software might enable more challenging training conditions tuned to the ability of the individuals. While the current implementation is not ready for assessment in clinical practice, we could demonstrate that this approach is safe, and it could be integrated as assist-as-needed training, rather than as assessment. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02425332.

Effect of Robotic-Assisted Gait at Different Levels of Guidance and Body Weight Support on Lower Limb Joint Kinematics and Coordination.

The Lokomat provides task-oriented therapy for patients with gait disorders. This robotic technology drives the lower limbs in the sagittal plane. However, normative gait also involves motions in the coronal and transverse planes. This study aimed to compare the Lokomat with Treadmill gait through three-dimensional (3D)-joint kinematics and inter-joint coordination. Lower limb kinematics was recorded in 18 healthy participants who walked at 3 km/h on a Treadmill or in a Lokomat with nine combinations of Guidance (30%, 50%, 70%) and bodyweight support (30%, 50%, 70%). Compared to the Treadmill, the Lokomat altered pelvic rotation, decreased pelvis obliquity and hip adduction, and increased ankle rotation. Moreover, the Lokomat resulted in significantly slower velocity at the hip, knee, and ankle flexion compared to the treadmill condition. Moderate to strong correlations were observed between the Treadmill and Lokomat conditions in terms of inter-joint coordination between hip-knee (r = 0.67-0.91), hip-ankle (r = 0.66-0.85), and knee-ankle (r = 0.90-0.95). This study showed that some gait determinants, such as pelvis obliquity, rotation, and hip adduction, are altered when walking with Lokomat in comparison to a Treadmill. Kinematic deviations induced by the Lokomat were most prominent at high levels of bodyweight support. Interestingly, different levels of Guidance did not affect gait kinematics. The present results can help therapists to adequately select settings during Lokomat therapy.

Robot-assisted gait training: more randomized controlled trials are needed! Or maybe not?

I was encouraged by the recent article by Kuo et al. entitled "Prediction of robotic neurorehabilitation functional ambulatory outcome in patients with neurological disorders" to write an opinion piece on the possible further development of stationary robot-assisted gait training research. Randomized clinical trials investigating stationary gait robots have not shown the superiority of these devices over comparable interventions regarding clinical effectiveness, and there are clinical practice guidelines that even recommend against their use. Nevertheless, these devices are still widely used, and our field needs to find ways to apply these devices more effectively. The authors of the article mentioned above feed different machine learning algorithms with patients' data from the beginning of a robot-assisted gait training intervention using the robot Lokomat. The output of these algorithms allows predictions of the clinical outcome (i.e., functional ambulation categories) while the patients are still participating in the intervention. Such an analysis based on the collection of the device's data could optimize the application of these devices. The article provides an example of how our field of research could make progress as we advance, and in this opinion piece, I would like to present my view on the prioritization of upcoming research on robot-assisted gait training. Furthermore, I briefly speculate on some drawbacks of randomized clinical trials in the field of robot-assisted gait training and how the quality and thus the effectiveness of robot-assisted gait training could potentially be improved based on the collection and analysis of clinical training data, a better patient selection and by giving greater weight to the motivational aspects for the participants.

Settings matter: a scoping review on parameters in robot-assisted gait therapy identifies the importance of reporting standards.

BACKGROUND: Lokomat therapy for gait rehabilitation has become increasingly popular. Most evidence suggests that Lokomat therapy is equally effective as but not superior to standard therapy approaches. One reason might be that the Lokomat parameters to personalize therapy, such as gait speed, body weight support and Guidance Force, are not optimally used. However, there is little evidence available about the influence of Lokomat parameters on the effectiveness of the therapy. Nevertheless, an appropriate reporting of the applied therapy parameters is key to the successful clinical transfer of study results. The aim of this scoping review was therefore to evaluate how the currently available clinical studies report Lokomat parameter settings and map the current literature on Lokomat therapy parameters. METHODS AND RESULTS: A systematic literature search was performed in three databases: Pubmed, Scopus and Embase. All primary research articles performing therapy with the Lokomat in neurologic populations in English or German were included. The quality of reporting of all clinical studies was assessed with a framework developed for this particular purpose. We identified 208 studies investigating Lokomat therapy in patients with neurologic diseases. The reporting quality was generally poor. Less than a third of the studies indicate which parameter settings have been applied. The usability of the reporting for a clinical transfer of promising results is therefore limited. CONCLUSION: Although the currently available evidence on Lokomat parameters suggests that therapy parameters might have an influence on the effectiveness, there is currently not enough evidence available to provide detailed recommendations. Nevertheless, clinicians should pay close attention to the reported therapy parameters when translating research findings to their own clinical practice. To this end, we propose that the quality of reporting should be improved and we provide a reporting framework for authors as a quality control before submitting a Lokomat-related article.

Energy cost and psychological impact of robotic-assisted gait training in people with spinal cord injury: effect of two different types of devices.

BACKGROUND: In the last years, there has been an intense technological development of robotic devices for gait rehabilitation in spinal cord injury (SCI) patients. The aim of the present study was to evaluate energy cost and psychological impact during a rehabilitation program with two different types of robotic rehabilitation systems (stationary system on a treadmill, Lokomat, and overground walking system, Ekso GT). METHODS: Fifteen SCI patients with different injury levels underwent robot-assisted gait training sessions, divided into 2 phases: in the first phase, all subjects completed 3 sessions both Lokomat and Ekso GT. Afterwards, participants were randomly assigned to Lokomat or the Ekso for 17 sessions. A questionnaire, investigating the subjective psychological impact (SPI) during gait training, was administered. The functional outcome measures were oxygen consumption (VO2), carbon dioxide production (VCO2), metabolic equivalent of task (MET), walking economy, and heart rate (HR). RESULTS: The metabolic responses (7.73 ± 1.02 mL/kg/min) and MET values (3.20 ± 1.01) during robotic overground walking resulted to be higher than those during robotic treadmill walking (3.91 ± 0.93 mL/kg/min and 1.58 ± 0.44; p < 0.01). Both devices showed high scores in emotion and satisfaction. Overground walking resulted in higher scores of fatigue, mental effort, and discomfort while walking with Lokomat showed a higher score in muscle relaxation. All patients showed improvements in walking economy due to a decrease in energy cost with increased speed and workload. CONCLUSIONS: Overground robotic-assisted gait training in rehabilitation program needs higher cognitive and cardiovascular efforts than robot-assisted gait training on a treadmill.

Prediction of robotic neurorehabilitation functional ambulatory outcome in patients with neurological disorders.

INTRODUCTION: Conflicting results persist regarding the effectiveness of robotic-assisted gait training (RAGT) for functional gait recovery in post-stroke survivors. We used several machine learning algorithms to construct prediction models for the functional outcomes of robotic neurorehabilitation in adult patients. METHODS AND MATERIALS: Data of 139 patients who underwent Lokomat training at Taipei Medical University Hospital were retrospectively collected. After screening for data completeness, records of 91 adult patients with acute or chronic neurological disorders were included in this study. Patient characteristics and quantitative data from Lokomat were incorporated as features to construct prediction models to explore early responses and factors associated with patient recovery. RESULTS: Experimental results using the random forest algorithm achieved the best area under the receiver operating characteristic curve of 0.9813 with data extracted from all sessions. Body weight (BW) support played a key role in influencing the progress of functional ambulation categories. The analysis identified negative correlations of BW support, guidance force, and days required to complete 12 Lokomat sessions with the occurrence of progress, while a positive correlation was observed with regard to speed. CONCLUSIONS: We developed a predictive model for ambulatory outcomes based on patient characteristics and quantitative data on impairment reduction with early-stage robotic neurorehabilitation. RAGT is a customized approach for patients with different conditions to regain walking ability. To obtain a more-precise and clearer predictive model, collecting more RAGT training parameters and analyzing them for each individual disorder is a possible approach to help clinicians achieve a better understanding of the most efficient RAGT parameters for different patients. TRIAL REGISTRATION: Retrospectively registered.

Towards a Clinical Decision-Making Algorithm Guiding Locomotor Therapy Modality in Subacute Stroke: An Exploratory Study.

OBJECTIVES: To propose a clinical decision-making algorithm guiding modality choice and transition from the Lokomat® robotic to body-weight supported treadmill training in subacute stroke, due to current evidence being limited, making clinical decisions difficult. MATERIALS AND METHODS: For 10 adult patients with subacute stroke completing Lokomat® therapy, physiotherapist clinical judgement regarding body-weight supported treadmill training readiness and the following objective measurements were collected; Functional Ambulation Category; sit to stand/standing ability; Lokomat® settings; maximal active hip and knee flexion in standing; and gait biomechanics during body-weight supported treadmill training. Based on observed patterns a proposed clinical decision-making algorithm was developed. RESULTS: Clinical judgement deemed four of 10 participants ready to transition to body-weight supported treadmill training. Unlike participants judged not ready, these participants had: a) a Functional Ambulation Category of 1; b) independence with sit to stand and standing with even weight bearing; c) Lokomat®: Body-Weight Support <30%, Guidance Force <30-35%, speed >2.0kph; d) >45° standing active hip and knee flexion; e) no significant issues with physiological stepping in treadmill training or only requiring assistance from one therapist to achieve this. CONCLUSION: Participants judged ready for transition from the Lokomat® to body-weight supported treadmill training presented with increased independent functional ability, more challenging Lokomat® settings, greater active volitional lower-limb control, and less issues with physiological stepping in treadmill training, than those participants judged not ready. Results were translated into a proposed clinical decision-making algorithm guiding transition from the Lokomat® to body-weight supported treadmill training, to be further tested in clinical trials.

Highest ambulatory speed using Lokomat gait training for individuals with a motor-complete spinal cord injury: a clinical pilot study.

BACKGROUND: Motor impairment and loss of ambulatory function are major consequences of a spinal cord injury (SCI). Exoskeletons are robotic devices that allow SCI patients with limited ambulatory function to walk. The mean walking speed of SCI patients using an exoskeleton is low: 0.26 m/s. Moreover, literature shows that a minimum speed of 0.59 m/s is required to replace wheelchairs in the community. OBJECTIVE: To investigate the highest ambulatory speed for SCI patients in a Lokomat. METHODS: This clinical pilot study took place in the Rehabilitation Center Kladruby, in Kladruby (Czech Republic). Six persons with motor-complete sub-acute SCI were recruited. Measurements were taken at baseline and directly after a 30 min Lokomat training. The highest achieved walking speed, vital parameters (respiratory frequency, heart rate, and blood pressure), visual analog scale for pain, and modified Ashworth scale for spasticity were recorded for each person. RESULTS: The highest reached walking speed in the Lokomat was on average 0.63 m/s (SD 0.03 m/s). No negative effects on the vital parameters, pain, or spasticity were observed. A significant decrease in pain after the Lokomat training was observed: 95% CI [0.336, 1.664] (p = 0.012). CONCLUSION: This study shows that it is possible for motor-complete SCI individuals to ambulate faster on a Lokomat (on average 0.63 m/s) than what is currently possible with over-ground exoskeletons. No negative effects were observed while ambulating on a Lokomat. Further research investigating walking speed in exoskeletons after SCI is recommended.

Effects of robotic neurorehabilitation through lokomat plus virtual reality on cognitive function in patients with traumatic brain injury: A retrospective case-control study.

Background: Traumatic brain injury (TBI) is a clinical condition characterized by damage due to a mechanical physical event, which has a devastating impact on both the patient and his/her family. The purpose of this study is to evaluate the effects of robotic neurorehabilitation using Lokomat with virtual reality (VR) on attention processes and executive functions in patients with TBI.Materials and Methods: This is a retrospective case-control study. Fifty-six TBI patients have been included in the analysis, using an electronic recovery data system. The enrolled patients were divided into two groups: the experimental group (LPG) underwent rehabilitation training with Lokomat Pro, equipped with a VR screen, whereas the control group (LNG) performed rehabilitation training using Lokomat Nanos, without VR. The two groups matched for age, sex, education, brain lesions, interval from TBI. The rehabilitation protocol consisted of a total of 40 training sessions.Results: LPG and LNG had a significant improvement in mood and in the perception of physical well-being. However, only the LPG had a significant improvement in global cognitive, executive and attention functions. Furthermore, LPG presented a significant enhancement of the quality of life, with regard to the perception of the mental and physical state.Conclusion: Our study supports the idea that Lokomat is a useful tool in the rehabilitation of patients with TBI; in particular, the integration of the VR device can implement the cognitive and behavioral functions of TBI patients, enhancing also their physical and mental well-being.

Augmented Performance Feedback during Robotic Gait Therapy Results in Moderate Intensity Cardiovascular Exercise in Subacute Stroke.

BACKGROUND: Low cardiovascular fitness is common poststroke. Conventional subacute stroke rehabilitation does not meet Australian National Stroke Guidelines for cardiovascular exercise, particularly in mobility-dependent patients. Walking robotics can potentially achieve recommended cardiovascular exercise with these patients. AIM: The primary aim was to determine whether sustained moderate intensity cardiovascular exercise can be achieved using 3 Lokomat Augmented Performance Feedback activities in mobility-dependent adults with subacute stroke. Secondary aims were to assess if cardiovascular workload was influenced by the activity completed, participants motivation or enjoyment, or changes in Lokomat settings. METHODS: Ten patients with subacute stroke (mean (SD) age: 63.4 (13) years) participated in 6x20-minute Lokomat study sessions. Each study session involved a warm-up and 3x5-minute APF activities presented in a random order. Metabolic data were collected using the COSMED-K5. Participants rated their perceived exertion on the BORG CR10 scale and Lokomat settings of body-weight support, guidance force, and speed were recorded. RESULTS: Moderate intensity cardiovascular exercise was achieved and maintained over the 15 minutes of exercise, objectively demonstrated by a mean (SD) Metabolic Equivalent Task of 3.1 (1.3), and mean (SD) oxygen consumption of 8.0 (3.8) ml/kg/min, estimated as 52% VO2max. This was subjectively confirmed by exertion scores between 3 and 5. The cardiovascular workload was not affected by which activity was completed, participant motivation or enjoyment, or significant progression of Lokomat settings between study sessions. CONCLUSIONS: Mobility-dependent patients with subacute stroke can achieve sustained moderate intensity cardiovascular exercise on the Lokomat when using APF activities.

Dual-task training of children with neuromotor disorders during robot-assisted gait therapy: prerequisites of patients and influence on leg muscle activity.

BACKGROUND: Walking in daily life is complex entailing various prerequisites such as leg strength, trunk stability or cognitive and motor dual task (DT) activities. Conventional physiotherapy can be complemented with robot-assisted gait therapy (RAGT) and exergames to enhance the number of step repetitions, feedback, motivation, and additional simultaneously performed tasks besides walking (e.g., dual-task (DT) activities). Although DT gait training leads to improvements in daily ambulation in adult patient groups, no study has evaluated RAGT with a DT exergame in children with neurological gait disorders. Therefore, we investigated children's functional and cognitive prerequisites to walk physiologically during RAGT with a DT exergame and analysed the influence of DT on leg muscle activity. METHODS: Children and adolescents (6-18 years) with neurological gait disorders completed RAGT with and without a DT exergame in this quasi-experimental study. We assessed several measures on the body function and activity domains (according to the International Classification of Functioning, Disability, and Health (ICF)) and determined whether these measures could distinguish well between children who walked physiologically during the DT RAGT or not. We measured leg muscle activity with surface electrodes to identify changes in EMG-amplitudes and -patterns. RESULTS: Twenty-one children participated (7 females, 6.5-17.3 years, Gross Motor Function Classification System (GMFCS) levels I-IV). Most activity measures distinguished significantly between participants performing the DT exergame physiologically or not with moderate to good sensitivity (0.8 ≤ sensitivity≤1.0) and specificity (0.5 ≤ specificity≤0.9). Body function measures differentiated less well. Despite that the EMG-amplitudes of key stance muscles were significantly lower during DT versus no DT exergaming, the mean activation patterns of all muscles correlated high (ρ > 0.75) between the conditions. CONCLUSION: This study is the first that investigated effects of a DT exergame during RAGT in children with neurological gait disorders. Several performance measures could differentiate well between patients who walked with physiological versus compensatory movements while performing the DT exergame. While the DT exergame affected the leg muscle activity amplitudes, it did not largely affect the activity patterns of the muscles.

Differences in muscle activity and temporal step parameters between Lokomat guided walking and treadmill walking in post-stroke hemiparetic patients and healthy walkers.

BACKGROUND: The Lokomat is a robotic exoskeleton that can be used to train gait function in hemiparetic stroke. To purposefully employ the Lokomat for training, it is important to understand (1) how Lokomat guided walking affects muscle activity following stroke and how these effects differ between patients and healthy walkers, (2) how abnormalities in the muscle activity of patients are modulated through Lokomat guided gait, and (3) how temporal step characteristics of patients were modulated during Lokomat guided walking. METHODS: Ten hemiparetic stroke patients (>3 months post-stroke) and ten healthy age-matched controls walked on the treadmill and in the Lokomat (guidance force 50%, no bodyweight support) at matched speeds (0.56 m/s). Electromyography was used to record the activity of Gluteus Medius, Biceps Femoris, Vastus Lateralis, Medial Gastrocnemius and Tibialis Anterior, bilaterally in patients and of the dominant leg in healthy walkers. Pressure sensors placed in the footwear were used to determine relative durations of the first double support and the single support phases. RESULTS: Overall, Lokomat guided walking was associated with a general lowering of muscle activity compared to treadmill walking, in patients as well as healthy walkers. The nature of these effects differed between groups for specific muscles, in that reductions in patients were larger if muscles were overly active during treadmill walking (unaffected Biceps Femoris and Gluteus Medius, affected Biceps Femoris and Vastus Lateralis), and smaller if activity was already abnormally low (affected Medial Gastrocnemius). Also, Lokomat guided walking was associated with a decrease in asymmetry in the relative duration of the single support phase. CONCLUSIONS: In stroke patients, Lokomat guided walking results in a general reduction of muscle activity, that affects epochs of overactivity and epochs of reduced activity in a similar fashion. These findings should be taken into account when considering the clinical potential of the Lokomat training environment in stroke, and may inform further developments in the design of robotic gait trainers.

The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial.

BACKGROUND: Many studies have demonstrated the usefulness of repetitive task practice by using robotic-assisted gait training (RAGT) devices, including Lokomat, for the treatment of lower limb paresis. Virtual reality (VR) has proved to be a valuable tool to improve neurorehabilitation training. The aim of our pilot randomized clinical trial was to understand the neurophysiological basis of motor function recovery induced by the association between RAGT (by using Lokomat device) and VR (an animated avatar in a 2D VR) by studying electroencephalographic (EEG) oscillations. METHODS: Twenty-four patients suffering from a first unilateral ischemic stroke in the chronic phase were randomized into two groups. One group performed 40 sessions of Lokomat with VR (RAGT + VR), whereas the other group underwent Lokomat without VR (RAGT-VR). The outcomes (clinical, kinematic, and EEG) were measured before and after the robotic intervention. RESULTS: As compared to the RAGT-VR group, all the patients of the RAGT + VR group improved in the Rivermead Mobility Index and Tinetti Performance Oriented Mobility Assessment. Moreover, they showed stronger event-related spectral perturbations in the high-γ and ß bands and larger fronto-central cortical activations in the affected hemisphere. CONCLUSIONS: The robotic-based rehabilitation combined with VR in patients with chronic hemiparesis induced an improvement in gait and balance. EEG data suggest that the use of VR may entrain several brain areas (probably encompassing the mirror neuron system) involved in motor planning and learning, thus leading to an enhanced motor performance. TRIAL REGISTRATION: Retrospectively registered in Clinical Trials on 21-11-2016, n. NCT02971371 .

Placebo-controlled study of rTMS combined with Lokomat® gait training for treatment in subjects with motor incomplete spinal cord injury.

High-frequency rTMS combined with gait training improves lower extremity motor score (LEMS) and gait velocity in SCI subjects who are able to walk over ground. The aim of this study was to optimize the functional outcome in early phases of gait rehabilitation in SCI using rTMS as an additional treatment to physical therapy. The present study included 31 motor incomplete SCI subjects randomized to receive real or sham rTMS, just before Lokomat gait training (15 subjects for real, 16 for sham rTMS). rTMS consisted of one daily session for 20 days over vertex (at 20 Hz). The subjects were evaluated using modified Ashworth scale (MAS) for spasticity, upper and lower extremity motor score (UEMS and LEMS, respectively), ten meters walking test (10MWT) and Walking Index for SCI (WISCI-II) for gait at baseline, after last rTMS session, and during follow-up. UEMS and LEMS improved significantly after last session in both groups and during follow-up period. The improvement was greater in real than in sham rTMS group. At follow-up, 71.4 % of the subjects after real rTMS and 40 % of the subjects after sham rTMS could perform 10MWT without significant differences in gait velocity, cadence, step length and WISCI-II between both groups. We conclude that 20 sessions of daily high-frequency rTMS combined with Lokomat gait training can lead to clinical improvement of gait in motor incomplete SCI. Such combined treatment improved motor strength in lower extremity in incomplete SCI subjects and in upper extremity in those with cervical SCI.

Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now?

Gait abnormalities following neurological disorders are often disabling, negatively affecting patients' quality of life. Therefore, regaining of walking is considered one of the primary objectives of the rehabilitation process. To overcome problems related to conventional physical therapy, in the last years there has been an intense technological development of robotic devices, and robotic rehabilitation has proved to play a major role in improving one's ability to walk. The robotic rehabilitation systems can be classified into stationary and overground walking systems, and several studies have demonstrated their usefulness in patients after severe acquired brain injury, spinal cord injury and other neurological diseases, including Parkinson's disease, multiple sclerosis and cerebral palsy. In this review, we want to highlight which are the most widely used devices today for gait neurological rehabilitation, focusing on their functioning, effectiveness and challenges. Novel and promising rehabilitation tools, including the use of virtual reality, are also discussed.

Lokomat training in vascular dementia: motor improvement and beyond!

Vascular dementia (VaD) is a general term describing problems with reasoning, planning, judgment, memory, and other thought processes caused by brain damage from impaired blood flow to the brain. Cognitive rehabilitation and physical therapy are the mainstays of dementia treatment, although often ineffective because of the scarce collaboration of the patients. However, emerging data suggest that physical activity may reduce the risk of cognitive impairment, mainly VaD, in older people living independently. Herein, we describe a 72-year-old male affected by VaD, in which traditional cognitive training in addition to intensive gait robotic rehabilitation (by using Lokomat device) led to a significant improvement in the motor and cognitive function. This promising finding may be related either to the intensive and repetitive aerobic exercises or to the task-oriented training with computerized visual feedback, which can be considered as a relevant tool to increase patients' motor output, involvement, and motivation during robotic training.

Research on Design Theory and Compliant Control for Underactuated Lower-extremity Rehabilitation Robotic Systems code: (51175368); 2012.01-2015.12.

[Purpose] The aim of this study was to investigate the immediate effect of Lokomat versus Ergo_bike training using the Probe Reaction Time (P-RT) and 10-m maximum walking speed as the outcome measures, on incomplete spinal cord injury (iSCI) patients. [Subjects] Thirty male T8-L3 level spinal cord injury patients were the subjects. [Methods] The subjects were randomly divided into 2 groups: a Lokomat group and an Ergo_bike group. Each group consisted of 15 subjects. The P-RT and 10 m maximum walking speed were measured before and after the intervention for each group. [Results] The P-RT and the time taken to cover 10 m at maximum walking speed decreased significantly in the Lokomat group. [Conclusion] The Lokomat training not only decreased P-RT, but also improved the walking ability of subjects with iSCI.