Leg surface electromyography patterns in children with neuro-orthopedic disorders walking on a treadmill unassisted and assisted by a robot with and without encouragement

Specific Instructions Are Important: A Cross-sectional Study on Device Parameters and Instruction Types While Walking With a Robot in Children and Adolescents

OBJECTIVE

The aim of the study is to evaluate how gait kinematics and muscle activity during robot-assisted gait training are affected by different combinations of parameter settings and a number of instruction types, ranging from no instructions to goal-specific instructions.

DESIGN

Robots for gait therapy provide a haptic guidance, but too much guidance can limit the active participation. Therapists can stimulate this active participation either with instructions or by adapting device parameters. How these two factors interact is still unknown. In the present study, we test the interaction of three different parameter settings and four instruction types in a cross-sectional study with 20 children and adolescents without impairment. Gait kinematics and surface electromyography were measured to evaluate the immediate effects.

RESULTS

We found that only goal-specific instructions in combination with a low guidance led to a moderate but significant change in gait kinematics. The muscle activity was altered by all instructions, but the biggest effect was found for goal-specific instructions with a 2.5 times higher surface electromyography amplitude compared to no instruction.

CONCLUSIONS

Goal-specific instructions are a key element of robot-assisted gait therapy interventions and device parameter adjustments may be used to modulate their effects. Therapists should pay close attention to how they instruct patients.

Clinical study on the safety and feasibility of AiWalker-K for lower limbs exercise rehabilitation in children with cerebral palsy

BACKGROUND

Robotic-assisted gait training (RAGT) devices are effective for children with cerebral palsy (CP). Many RAGT devices have been created and put into clinical rehabilitation treatment. Therefore, we aimed to investigate the safety and feasibility of a new RAGT for children with CP.

METHODS

This study is a cross-over design with 23 subjects randomly divided into two groups. The occurrence of adverse events and changes in heart rate and blood pressure were recorded during each AiWalker-K training. Additionally, Gross Motor Function Measure-88 (GMFM-88), Pediatric Balance Scale (PBS), 6 Minutes Walking Test (6MWT), Physiological Cost Index, and Edinburgh Visual Gait Score (EVGS) were used to assess treatment, period, carry-over, and follow-up effects in this study.

RESULTS

Adverse events included joint pain, skin pain, and injury. Heart rate and blood pressure were higher with the AiWalker-K compared to the rest (P < 0.05), but remained within safe ranges. After combined treatment with AiWalker-K and routine rehabilitation treatment, significant improvements in 6MWT, GMFM-88 D and E, PBS, and EVGS were observed compared to routine rehabilitation treatment alone (P < 0.05).

CONCLUSIONS

Under the guidance of experienced medical personnel, AiWalker-K can be used for rehabilitation in children with CP.

Robot-assisted rehabilitation for children with neurological disabilities: Results of the Italian consensus conference CICERONE

BACKGROUND

The use of robotic technologies in pediatric rehabilitation has seen a large increase, but with a lack of a comprehensive framework about their effectiveness.

OBJECTIVE

An Italian Consensus Conference has been promoted to develop recommendations on these technologies: definitions and classification criteria of devices, indications and limits of their use in neurological diseases, theoretical models, ethical and legal implications. In this paper, we present the results for the pediatric age.

METHODS

A systematic search on Cochrane Library, PEDro and PubMed was performed. Papers published up to March 1st, 2020, in English, were included and analyzed using the methodology of the Centre for Evidence-Based Medicine in Oxford, AMSTAR2 and PEDro scales for systematic reviews and RCT, respectively.

RESULTS

Some positives aspects emerged in the area of gait: an increased number of children reaching the stance, an improvement in walking distance, speed and endurance. Critical aspects include the heterogeneity of the studied cases, measurements and training protocols.

CONCLUSION

Many studies demonstrate the benefits of robotic training in developmental age. However, it is necessary to increase the number of trials to achieve greater homogeneity between protocols and to confirm the effectiveness of pediatric robotic rehabilitation.

Effects of asymmetrical support on lower limb muscle activity during Lokomat guided gait in persons with a chronic stroke: an explorative study

BACKGROUND

The Lokomat, one of the most popular robotic exoskeletons, can take the asymmetry in the gait pattern of unilaterally affected patients into account with its opportunity to provide unequal levels of movement support (or 'guidance') to each of the legs. This asymmetrical guidance may be used to selectively unburden limbs with impaired voluntary control and/or to exploit the interlimb couplings for training purposes. However, there is a need to explore and understand these specific device opportunities more broadly before implementing them in training.

AIM

The aim of this study was to explore the effects of (a)symmetrical guidance settings on lower limb muscle activity in persons with post stroke hemiparesis, during Lokomat guided gait.

DESIGN

A single group, dependent factorial design.

SETTING

Rehabilitation center; a single session of Lokomat guided walking.

POPULATION

A group of ten persons with post stroke hemiparesis.

METHODS

Participants walked in the Lokomat in eight conditions, consisting of symmetrical and asymmetrical guidance situations, at both 0.28 m/s and 0.56 m/s. During symmetrical conditions, both legs received 30% or 100% guidance, while during asymmetrical conditions one leg received 30% and the other leg 100% guidance. Surface electromyography was bilaterally measured from: Biceps Femoris, Rectus Femoris, Vastus Medialis, Medial Gastrocnemius and Tibialis Anterior. Statistical effects were assessed using Statistical Parametric Mapping.

RESULTS

The provision of assymetrical guidance did not affect the level of lower limb muscle activity. In addition, no effect (except for Vastus Medialis in the affected leg during 1.5-2.4% of the gait cycle) of symmetrical guidance on muscle amplitude could be observed.

CONCLUSIONS

The results show no evidence that either symmetrical or asymmetrical guidance settings provided by the Lokomat can be used to manipulate activity of lower limb musculature in persons with post stroke hemiparesis.

CLINICAL REHABILITATION IMPACT

This study provides insights for the use of specific opportunities provided by the Lokomat for training purposes post stroke.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-022-01017-3.

Gait changes following robot-assisted gait training in children with cerebral palsy

This study investigated changes of gait pattern induced by a 4-week robot-assisted gait training (RAGT) in twelve ambulatory spastic diparesis children with cerebral palsy (CP) aged 10.4+/-3.2 years old by using computerized gait analysis (CGA). Pre-post intervention CGA data of children with CP was contrasted to the normative data of typically developing children by using cross-correlation and statistically evaluated by a Wilcoxon test. Significant pre-post intervention changes (p<0.01) include: decreased muscle activity of biceps femoris, rectus femoris, and tibialis anterior; a decrease in range of internal hip joint rotation, higher cadence, step length, and increased stride time. This study suggests that RAGT can be used in muscle reeducation and improved hip joint motion range in ambulatory children with CP.

Effects of body weight support and guidance force settings on muscle synergy during Lokomat walking

BACKGROUND

The Lokomat is a robotic device that has been suggested to make gait therapy easier, more comfortable, and more efficient. In this study, we asked whether the Lokomat promotes physiological muscle activation patterns, a fundamental question when considering motor learning and adaptation.

METHODS

We investigated lower limb muscles coordination in terms of muscle activity level, muscle activity pattern similarity, and muscle synergy in 15 healthy participants walking at 3 km/h on either a treadmill or in a Lokomat at various guidance forces (GF: 30, 50 or 70%) and body weight supports (BWS: 30, 50 or 70% of participant's body weight).

RESULTS

Walking in the Lokomat was associated with a greater activation level of the rectus femoris and vastus medialis (×2-3) compared to treadmill walking. The level of activity tended to be diminished in gastrocnemius and semi-tendinosus, which particularly affected the similarity with treadmill walking (normalized scalar product NSP = 0.7-0.8). GF and BWS independently altered the muscle activation pattern in terms of amplitude and shape. Increasing BWS decreased the level of activity in all but one muscle (the soleus). Increasing GF slightly improved the similarity with treadmill walking for the tibialis anterior and vastus medialis muscles. The muscle synergies (N = 4) were similar (NSP = 0.93-0.97), but a cross-validation procedure revealed an alteration by the Lokomat. The activation of these synergies differed (NSP = 0.74-0.82).

CONCLUSION

The effects of GF and BWS are modest compared to the effect of the Lokomat itself, suggesting that Lokomat design should be improved to promote more typical muscle activity patterns.

Amplitude and stride-to-stride variability of muscle activity during Lokomat guided walking and treadmill walking in children with cerebral palsy

BACKGROUND

The Lokomat is a commercially available exoskeleton for gait training in persons with cerebral palsy (CP). Because active contributions and variability over movement repetitions are determinants of training effectiveness, we studied muscle activity in children with CP, and determined (i) differences between treadmill and Lokomat walking, and (ii) the effects of Lokomat training parameters, on the amplitude and the stride-to-stride variability.

METHODS

Ten children with CP (age 13.2 ± 2.9, GMFCS level II(n = 6)/III(n = 4)) walked on a treadmill (±1 km/h; 0% bodyweight support(BWS)), and in the Lokomat (50% and 100% guidance; ±1 km/h and ±2 km/h; 0% and 50% BWS). Activity was recorded from Gluteus Medius (GM), Vastus Lateralis (VL), Biceps Femoris (BF), Medial Gastrocnemius (MG) and Tibialis Anterior (TA) of the most affected side. The averaged amplitude per gait phase, and the second order coefficient of variation was used to determine the active contribution and stride-to-stride variability, respectively.

RESULTS

Generally, the amplitude of activity was lower in the Lokomat than on the treadmill. During Lokomat walking, providing guidance and BWS resulted in slightly lower amplitudes whereas increased speed was associated with higher amplitudes. No significant differences in stride-to-stride variability were observed between Lokomat and treadmill walking, and in the Lokomat only speed (MG) and guidance (BF) affected variability.

CONCLUSIONS

Lokomat walking reduces muscle activity in children with CP, whereas altering guidance or BWS generally does not affect amplitude. This urges additional measures to encourage active patient contributions, e.g. by increasing speed or through instruction.

Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people

BACKGROUND

Gait disorders are major symptoms of neurological diseases affecting the quality of life. Interventions that restore walking and allow patients to maintain safe and independent mobility are essential. Robot-assisted gait training (RAGT) proved to be a promising treatment for restoring and improving the ability to walk. Due to heterogenuous study designs and fragmentary knowlegde about the neural correlates associated with RAGT and the relation to motor recovery, guidelines for an individually optimized therapy can hardly be derived. To optimize robotic rehabilitation, it is crucial to understand how robotic assistance affect locomotor control and its underlying brain activity. Thus, this study aimed to investigate the effects of robotic assistance (RA) during treadmill walking (TW) on cortical activity and the relationship between RA-related changes of cortical activity and biomechanical gait characteristics.

METHODS

Twelve healthy, right-handed volunteers (9 females; M = 25 ± 4 years) performed unassisted walking (UAW) and robot-assisted walking (RAW) trials on a treadmill, at 2.8 km/h, in a randomized, within-subject design. Ground reaction forces (GRFs) provided information regarding the individual gait patterns, while brain activity was examined by measuring cerebral hemodynamic changes in brain regions associated with the cortical locomotor network, including the sensorimotor cortex (SMC), premotor cortex (PMC) and supplementary motor area (SMA), using functional near-infrared spectroscopy (fNIRS).

RESULTS

A statistically significant increase in brain activity was observed in the SMC compared with the PMC and SMA (p < 0.05), and a classical double bump in the vertical GRF was observed during both UAW and RAW throughout the stance phase. However, intraindividual gait variability increased significantly with RA and was correlated with increased brain activity in the SMC (p = 0.05; r = 0.57).

CONCLUSIONS

On the one hand, robotic guidance could generate sensory feedback that promotes active participation, leading to increased gait variability and somatosensory brain activity. On the other hand, changes in brain activity and biomechanical gait characteristics may also be due to the sensory feedback of the robot, which disrupts the cortical network of automated walking in healthy individuals. More comprehensive neurophysiological studies both in laboratory and in clinical settings are necessary to investigate the entire brain network associated with RAW.

An Increase in Kinematic Freedom in the Lokomat Is Related to the Ability to Elicit a Physiological Muscle Activity Pattern: A Secondary Data Analysis Investigating Differences Between Guidance Force, Path Control, and FreeD

Background: Robot-assisted gait therapy is a fast-growing field in pediatric neuro-rehabilitation. Understanding how these constantly developing technologies work is a prerequisite for shaping clinical application. For the Lokomat, two new features are supposed to increase patients' movement variability and should enable a more physiological gait pattern: Path Control and FreeD. This work provides a secondary data analysis of a previously published study, and looks at surface electromyography (sEMG) during Guidance Force walking and six sub-conditions of Path Control and FreeD. Objective: The aim was to evaluate different levels of kinematic freedom on the gait pattern of pediatric patients by modulating settings of Path Control and FreeD. Methods: Fifteen patients (mean age 16 ± 2 years) with neurological gait disorders completed the measurements. We analyzed sEMG amplitudes and the correlation of sEMG patterns with normative data of five leg muscles during walking conditions with increasing kinematic freedom in the Lokomat. The new outcome measure of inter-step similarity is introduced as a proxy for walking task complexity. Results: Within Path Control, sub-conditions showed significantly higher sEMG amplitudes in a majority of muscles with increasing kinematic freedom, and correlations with the norm pattern increased with increasing kinematic freedom. FreeD sub-conditions generally showed low or even negative correlations with the norm pattern and a lower inter-step similarity compared to Guidance Force. Conclusions: In general, this work highlights that the new hard- and software approaches of the Lokomat influence muscle activity differently. An increase of kinematic freedom of the walking condition led to an increase in muscular effort (Path Control) or to a higher step variability (FreeD) which can be interpreted as an increased task complexity of this condition. The inter-step similarity could be a helpful tool for the therapist to estimate the patient's state of strain.

The FreeD module for the Lokomat facilitates a physiological movement pattern in healthy people - a proof of concept study

BACKGROUND

A contralateral pelvic drop, a transverse rotation and a lateral translation of the pelvis are essential features of normal human gait. These motions are often restricted in robot-assisted gait devices. The optional FreeD module of the driven gait orthosis Lokomat (Hocoma AG, Switzerland) incorporates guided lateral translation and transverse rotation of the pelvis. It consequently should support weight shifting during walking. This study aimed to investigate the influence of the FreeD module on trunk kinematics and hip and trunk muscle activity.

METHODS

Thirty- one healthy adults participated. A video analysis of their trunk movements was performed to investigate the lateral chest and pelvis displacement within the Lokomat (with and without FreeD), and this was compared to treadmill walking. Furthermore, surface electromyography (sEMG) signals from eight muscles were collected during walking in the Lokomat (with and without FreeD), on the treadmill, and overground. To compare the similarity of the sEMG patterns, Spearman's correlation analyses were applied.

RESULTS

Walking with FreeD elicited a significantly higher lateral pelvis displacement and a lower lateral chest displacement (relative to the pelvis) compared to walking with a fixated pelvis. No significant differences in the sEMG patterns were found for the Lokomat conditions (with and without FreeD) when comparing it to treadmill or overground walking.

CONCLUSIONS

The differences in pelvis displacement act as a proof of concept of the FreeD module. The reduction of relative lateral chest movement corresponds to a decrease in compensatory trunk movements and has its origin in allowing weight shifting through the FreeD module. Both Lokomat conditions showed very similar muscle activity patterns of the trunk and hip compared to overground and treadmill walking. This indicates that the Lokomat allows a physiological muscle activity of the trunk and hip during gait.

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.

Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies

Background

The application of rehabilitation robots has grown during the last decade. While meta-analyses have shown beneficial effects of robotic interventions for some patient groups, the evidence is less in others. We established the Advanced Robotic Therapy Integrated Centers (ARTIC) network with the goal of advancing the science and clinical practice of rehabilitation robotics. The investigators hope to exploit variations in practice to learn about current clinical application and outcomes. The aim of this paper is to introduce the ARTIC network to the clinical and research community, present the initial data set and its characteristics and compare the outcome data collected so far with data from prior studies.

Methods

ARTIC is a pragmatic observational study of clinical care. The database includes patients with various neurological and gait deficits who used the driven gait orthosis Lokomat® as part of their treatment. Patient characteristics, diagnosis-specific information, and indicators of impairment severity are collected. Core clinical assessments include the 10-Meter Walk Test and the Goal Attainment Scaling. Data from each Lokomat® training session are automatically collected.

Results

At time of analysis, the database contained data collected from 595 patients (cerebral palsy: n = 208; stroke: n = 129; spinal cord injury: n = 93; traumatic brain injury: n = 39; and various other diagnoses: n = 126). At onset, average walking speeds were slow. The training intensity increased from the first to the final therapy session and most patients achieved their goals.

Conclusions

The characteristics of the patients matched epidemiological data for the target populations. When patient characteristics differed from epidemiological data, this was mainly due to the selection criteria used to assess eligibility for Lokomat® training. While patients included in randomized controlled interventional trials have to fulfill many inclusion and exclusion criteria, the only selection criteria applying to patients in the ARTIC database are those required for use of the Lokomat®. We suggest that the ARTIC network offers an opportunity to investigate the clinical application and effectiveness of rehabilitation technologies for various diagnoses. Due to the standardization of assessments and the use of a common technology, this network could serve as a basis for researchers interested in specific interventional studies expanding beyond the Lokomat®.

Can Lokomat therapy with children and adolescents be improved? An adaptive clinical pilot trial comparing Guidance force, Path control, and FreeD

Background

Robot-assisted gait therapy is increasingly being used in pediatric neurorehabilitation to complement conventional physical therapy. The robotic device applied in this study, the Lokomat (Hocoma AG, Switzerland), uses a position control mode (Guidance Force), where exact positions of the knee and hip joints throughout the gait cycle are stipulated. Such a mode has two disadvantages: Movement variability is restricted, and patients tend to walk passively. Kinematic variability and active participation, however, are crucial for motor learning. Recently, two new control modes were introduced. The Path Control mode allows the patient to walk within a virtual tunnel surrounding the ideal movement trajectory. The FreeD was developed to support weight shifting through mediolaterally moveable pelvis and leg cuffs. The aims of this study were twofold: 1) To present an overview of the currently available control modes of the Lokomat. 2) To evaluate if an increase in kinematic variability as provided by the new control modes influenced leg muscle activation patterns and intensity, as well as heart rate while walking in the Lokomat.

Methods

In 15 adolescents with neurological gait disorders who walked in the Lokomat, 3 conditions were compared: Guidance Force, Path Control, and FreeD. We analyzed surface electromyographic (sEMG) activity from 5 leg muscles of the more affected leg and heart rate. Muscle activation patterns were compared with norm curves.

Results

Several muscles, as well as heart rate, demonstrated tendencies towards a higher activation during conditions with more kinematic freedom. sEMG activation patterns of the M.rectus femoris and M.vastus medialis showed the highest similarity to over-ground walking under Path Control, whereas walking under FreeD led to unphysiological muscle activation in the tested sample.

Conclusions

Results indicate that especially Path Control seems promising for adolescent patients undergoing neurorehabilitation, as it increases proximal leg muscle activity while facilitating a physiological muscle activation. Therefore, this may be a solution to increase kinematic variability and patients’ active participation in robot-assisted gait training.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-017-0287-1) contains supplementary material, which is available to authorized users.

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 combined effects of guidance force, bodyweight support and gait speed on muscle activity during able-bodied walking in the Lokomat

BACKGROUND

The ability to provide automated movement guidance is unique for robot assisted gait trainers such as the Lokomat. For the design of training protocols for the Lokomat it is crucial to understand how movement guidance affects the patterning of muscle activity that underlies walking, and how these effects interact with settings for bodyweight support and gait speed.

METHODS

Ten healthy participants walked in the Lokomat, with varying levels of guidance (0, 50 and 100%), bodyweight support (0 or 50% of participants' body weight) and gait speed (0.22, 0.5 or 0.78m/s). Surface electromyography of Erector Spinae, Gluteus Medius, Vastus Lateralis, Biceps Femoris, Medial Gastrocnemius and Tibialis Anterior were recorded. Group averaged levels of muscle activity were compared between conditions, within specific phases of the gait cycle.

FINDINGS

The provision of guidance reduced the amplitude of activity in muscles associated with stability and propulsion (i.e. Erector Spinae, Gluteus Medius, Biceps Femoris and Medial Gastrocnemius) and normalized abnormally high levels of activity observed in a number of muscles (i.e. Gluteus Medius, Biceps Femoris, and Tibialis anterior). The magnitude of guidance effects depended on both speed and bodyweight support, as reductions in activity were most prominent at low speeds and high levels of bodyweight support.

INTERPRETATION

The Lokomat can be effective in eliciting normal patterns of muscle activity, but only under specific settings of its training parameters.