Alterations in muscle activation patterns during robotic-assisted walking

An interaction model for predicting brace migration and validation through walking experiment

Brace migration undermines therapeutic efficacy, which is traditionally evaluated through walking experiments. This study developed an interaction model that considered the instantaneous center of rotation (ICR) misalignment to predict migration. The model was validated by walking experiment. Results show a strong positive correlation for four-linkage (FL) (r = 0.952, p < 0.01, root mean squared error (RMSE) = 0.53 mm) and spur gear (SG) (r = 0.898, p < 0.01, RMSE = 1.35 mm) mechanisms. The FL exhibits lower migration than SG (p < 0.05). In conclusion, the interaction model accurately predicts migration, emphasizing the influence of mechanism on migration.

Evaluation of EMG patterns in children during assisted walking in the exoskeleton

While exoskeleton technology is becoming more and more common for gait rehabilitation in children with neurological disorders, evaluation of gait performance still faces challenges and concerns. The reasoning behind evaluating the spinal locomotor output is that, while exoskeleton's guidance forces create the desired walking kinematics, they also affect sensorimotor interactions, which may lead to an abnormal spatiotemporal integration of activity in particular spinal segments and the risk of abnormalities in gait recovery. Therefore, traditional indicators based on kinematic or kinetic characteristics for optimizing exoskeleton controllers for gait rehabilitation may be supplemented by performance measures associated with the neural control mechanisms. The purpose of this study on a sample of children was to determine the basic features of lower limb muscle activity and to implement a method for assessing the neuromechanics of spinal locomotor output during exoskeleton-assisted gait. To this end, we assessed the effects of a robotic exoskeleton (ExoAtlet Bambini) on gait performance, by recording electromyographic activity of leg muscles and analyzing the corresponding spinal motor pool output. A slower walking setting (about 0.2 m/s) was chosen on the exoskeleton. The results showed that, even with slower walking, the level of muscle activation was roughly comparable during exoskeleton-assisted gait and normal walking. This suggests that, despite full assistance for leg movements, the child's locomotor controllers can interpret step-related afferent information promoting essential activity in leg muscles. This is most likely explained by the active nature of stepping in the exoskeleton (the child was not fully relaxed, experienced full foot loading and needed to maintain the upper trunk posture). In terms of the general muscle activity patterns, we identified notable variations for the proximal leg muscles, coactivation of the lumbar and sacral motor pools, and weak propulsion from the distal extensors at push-off. These changes led to the lack of characteristic lumbosacral oscillations of the center of motoneuron activity, normally associated with the pendulum mechanism of bipedal walking. This work shows promise as a useful technique for analyzing exoskeleton performance to help children develop their natural gait pattern and to guide system optimization in the future for inclusion into clinical care.

A Recurrent Deep Network for Gait Phase Identification from EMG Signals During Exoskeleton-Assisted Walking

Lower limb exoskeletons represent a relevant tool for rehabilitating gait in patients with lower limb movement disorders. Partial assistance exoskeletons adaptively provide the joint torque needed, on top of that produced by the patient, for a correct and stable gait, helping the patient to recover an autonomous gait. Thus, the device needs to identify the different phases of the gait cycle to produce precisely timed commands that drive its joint motors appropriately. In this study, EMG signals have been used for gait phase detection considering that EMG activations lead limb kinematics by at least 120 ms. We propose a deep learning model based on bidirectional LSTM to identify stance and swing gait phases from EMG data. We built a dataset of EMG signals recorded at 1500 Hz from four muscles from the dominant leg in a population of 26 healthy subjects walking overground (WO) and walking on a treadmill (WT) using a lower limb exoskeleton. The data were labeled with the corresponding stance or swing gait phase based on limb kinematics provided by inertial motion sensors. The model was studied in three different scenarios, and we explored its generalization abilities and evaluated its applicability to the online processing of EMG data. The training was always conducted on 500-sample sequences from WO recordings of 23 subjects. Testing always involved WO and WT sequences from the remaining three subjects. First, the model was trained and tested on 500 Hz EMG data, obtaining an overall accuracy on the WO and WT test datasets of 92.43% and 91.16%, respectively. The simulation of online operation required 127 ms to preprocess and classify one sequence. Second, the trained model was evaluated against a test set built on 1500 Hz EMG data. The accuracies were lower, yet the processing times were 11 ms faster. Third, we partially retrained the model on a subset of the 1500 Hz training dataset, achieving 87.17% and 89.64% accuracy on the 1500 Hz WO and WT test sets, respectively. Overall, the proposed deep learning model appears to be a valuable candidate for entering the control pipeline of a lower limb rehabilitation exoskeleton in terms of both the achieved accuracy and processing times.

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.

Changes in pressure of strap while walking in a robotic gait training system

Exoskeletons have been developed and widely used for medical, industrial, military applications. Since the exoskeletons are designed to provide the users with torques needed for the specific applications, it is important for the torques generated by either the users or the exoskeletons to be transmitted without any loss for their effectiveness. It is typical for the users to be attached to the exoskeletons using straps. However, it is inevitable for the straps to be loosened during a gait cycle due to compliance inherited in the tissues of skin and materials used for the straps, deformation of the muscles when activated, and misalignment of the joints. In this research, the pressures of strap on the user in an exoskeleton robot as well as the relative acceleration between the user and exoskeleton were measured. Experimental results showed higher pressures during the stance phase and larger relative motions in the swing phase. Furthermore, the relative motions were similar to each other regardless of the pressure settings.

Preliminary Virtual Constraint-Based Control Evaluation on a Pediatric Lower-Limb Exoskeleton

Pediatric gait rehabilitation and guidance strategies using robotic exoskeletons require a controller that encourages user volitional control and participation while guiding the wearer towards a stable gait cycle. Virtual constraint-based controllers have created stable gait cycles in bipedal robotic systems and have seen recent use in assistive exoskeletons. This paper evaluates a virtual constraint-based controller for pediatric gait guidance through comparison with a traditional time-dependent position tracking controller on a newly developed exoskeleton system. Walking experiments were performed with a healthy child subject wearing the exoskeleton under proportional-derivative control, virtual constraint-based control, and while unpowered. The participant questionnaires assessed the perceived exertion and controller usability measures, while sensors provided kinematic, control torque, and muscle activation data. The virtual constraint-based controller resulted in a gait similar to the proportional-derivative controlled gait but reduced the variability in the gait kinematics by 36.72% and 16.28% relative to unassisted gait in the hips and knees, respectively. The virtual constraint-based controller also used 35.89% and 4.44% less rms torque per gait cycle in the hips and knees, respectively. The user feedback indicated that the virtual constraint-based controller was intuitive and easy to utilize relative to the proportional-derivative controller. These results indicate that virtual constraint-based control has favorable characteristics for robot-assisted gait guidance.

Adaptive gait responses to varying weight-bearing conditions: Inferences from gait dynamics and H-reflex magnitude

This study investigates the effects of varying loading conditions on excitability in neural pathways and gait dynamics. We focussed on evaluating the magnitude of the Hoffman reflex (H-reflex), a neurophysiological measure representing the capability to activate motor neurons and the timing and placement of the foot during walking. We hypothesized that weight manipulation would alter H-reflex magnitude, footfall and lower body kinematics. Twenty healthy participants were recruited and subjected to various weight-loading conditions. The H-reflex, evoked by stimulating the tibial nerve, was assessed from the dominant leg during walking. Gait was evaluated under five conditions: body weight, 20% and 40% additional body weight, and 20% and 40% reduced body weight (via a harness). Participants walked barefoot on a treadmill under each condition, and the timing of electrical stimulation was set during the stance phase shortly after the heel strike. Results show that different weight-loading conditions significantly impact the timing and placement of the foot and gait stability. Weight reduction led to a 25% decrease in double limb support time and an 11% narrowing of step width, while weight addition resulted in an increase of 9% in step width compared to body weight condition. Furthermore, swing time variability was higher for both the extreme weight conditions, while the H-reflex reduced to about 45% between the extreme conditions. Finally, the H-reflex showed significant main effects on variability of both stance and swing phases, indicating that muscle-motor excitability might serve as feedback for enhanced regulation of gait dynamics under challenging conditions.

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.

Effects of a soft robotic exosuit on the quality and speed of overground walking depends on walking ability after stroke

BACKGROUND

Soft robotic exosuits can provide partial dorsiflexor and plantarflexor support in parallel with paretic muscles to improve poststroke walking capacity. Previous results indicate that baseline walking ability may impact a user's ability to leverage the exosuit assistance, while the effects on continuous walking, walking stability, and muscle slacking have not been evaluated. Here we evaluated the effects of a portable ankle exosuit during continuous comfortable overground walking in 19 individuals with chronic hemiparesis. We also compared two speed-based subgroups (threshold: 0.93 m/s) to address poststroke heterogeneity.

METHODS

We refined a previously developed portable lightweight soft exosuit to support continuous overground walking. We compared five minutes of continuous walking in a laboratory with the exosuit to walking without the exosuit in terms of ground clearance, foot landing and propulsion, as well as the energy cost of transport, walking stability and plantarflexor muscle slacking.

RESULTS

Exosuit assistance was associated with improvements in the targeted gait impairments: 22% increase in ground clearance during swing, 5° increase in foot-to-floor angle at initial contact, and 22% increase in the center-of-mass propulsion during push-off. The improvements in propulsion and foot landing contributed to a 6.7% (0.04 m/s) increase in walking speed (R2 = 0.82). This enhancement in gait function was achieved without deterioration in muscle effort, stability or cost of transport. Subgroup analyses revealed that all individuals profited from ground clearance support, but slower individuals leveraged plantarflexor assistance to improve propulsion by 35% to walk 13% faster, while faster individuals did not change either.

CONCLUSIONS

The immediate restorative benefits of the exosuit presented here underline its promise for rehabilitative gait training in poststroke individuals.

Biomechanics of Exoskeleton-Assisted Treadmill Walking

To exploit the benefits of treadmill-based exoskeletons, it is crucial to assess possible deviations from natural walking depending on assistive parameters. This study evaluated the biomechanics of exoskeleton-assisted treadmill walking by comparing it with free gait. Five healthy participants walked freely on a treadmill and with the assistance of the Lokomat gait trainer, while changing Body Weight Support (BWS), Gait Speed (GS), and Guidance Force (GF). Results showed that the hip and knee joint kinematics depended on BWS and GS, while changes due to GF were limited. Moreover, joint kinematics and the activity of related muscles were altered with respect to free gait, for any combination of robot parameters in the case of the ankle, and especially for low GS and with BWS in the case of hip and knee. Overall, walking with the Lokomat can mostly resemble free gait at high speed and without BWS.

The FreeD module's lateral translation timing in the gait robot Lokomat: a manual adaptation is necessary

BACKGROUND

Pelvic and trunk movements are often restricted in stationary robotic gait trainers. The optional FreeD module of the driven gait orthosis Lokomat offers a combined, guided lateral translation and transverse rotation of the pelvis and may therefore support weight shifting during walking. However, from clinical experience, it seems that the default setting of this timing does not correspond well with the timing of the physiological pelvic movement during the gait cycle. In the software, a manual adaptation of the lateral translation's timing with respect to the gait cycle is possible. The aim of this study was to investigate if such an offset is indeed present and if a manual adaptation by the therapist can improve the timing towards a more physiological pattern comparable to physiological overground walking.

METHODS & RESULTS

Children and adolescents with neurologic gait disorders and a Gross Motor Function Classification System level I-IV completed two different walking conditions (FreeD Default and FreeD Time Offset) in the Lokomat. The medio-lateral center of mass positions were calculated from RGB-Depth video recordings with a marker-less motion capture algorithm. Data of 22 patients (mean age: 12 ± 3 years) were analyzed. Kinematic analyses showed that in the FreeD Default condition, the maximum lateral center of mass excursion occurred too early. In the FreeD Time Offset condition, the manual adaptation by the therapists led to a delay of the maximum center of mass displacement by 8.2% in the first phase of the gait cycle and by 4.9% in the second phase of the gait cycle compared to the FreeD Default condition. The maximum lateral center of mass excursion was closer to that during physiological overground walking in the FreeD Time Offset condition than in the FreeD Default condition.

CONCLUSION

A manual adaptation of the timing of the FreeD module in the Lokomat shifts pelvis kinematics in a direction of physiological overground walking. We recommend therapists to use this FreeD Time Offset function to adjust the phase of weight shifting for each patient individually to optimize the kinematic walking pattern when a restorative therapy approach is adopted.

Comparing the Lower-Limb Muscle Activation Patterns of Simulated Walking Using an End-Effector-Type Robot with Real Level and Stair Walking in Children with Spastic Bilateral Cerebral Palsy

Cerebral palsy is a neurologic disorder caused by lesions on an immature brain, often resulting in spasticity and gait abnormality. This study aimed to compare the muscle activation patterns of real level and stair walking with those of simulated walking using an end-effector-type robot in children with spastic cerebral palsy. The electromyographic activities of the vastus lateralis, biceps femoris, tibialis anterior and medial gastrocnemius of nine children with spastic bilateral cerebral palsy were measured during gait using a wireless surface EMG device. Morning walk was used for the simulated gait. Differences in the muscle activation patterns between the real and simulated gait conditions were analyzed. In the loading response, all four muscles showed reduced activity during two simulated conditions. In mid-stance, mGCM showed reduced activity during simulated conditions, whereas BFem showed greater activity during simulated level walking. In the swing phase, BFem and TAnt activity was reduced during the simulated conditions. The onset-offset of the VLat, BFem and TAnt activity was significantly delayed during simulated versus real level walking. No differences in activity onset-offset were observed between the simulated level and stair conditions. In conclusion, the robot-simulated gait showed differences in its muscle activation patterns compared with the real gait conditions, which must be considered for gait training using an end-effector-type robot.

Clustering trunk movements of children and adolescents with neurological gait disorders undergoing robot-assisted gait therapy: the functional ability determines if actuated pelvis movements are clinically useful

INTRODUCTION

Robot-assisted gait therapy is frequently used for gait therapy in children and adolescents but has been shown to limit the physiological excursions of the trunk and pelvis. Actuated pelvis movements might support more physiological trunk patterns during robot-assisted training. However, not every patient is expected to react identically to actuated pelvis movements. Therefore, the aim of the present study was to identify different trunk movement patterns with and without actuated pelvis movements and compare them based on their similarity to the physiological gait pattern.

METHODS AND RESULTS

A clustering algorithm was used to separate pediatric patients into three groups based on different kinematic reactions of the trunk to walking with and without actuated pelvis movements. The three clusters included 9, 11 and 15 patients and showed weak to strong correlations with physiological treadmill gait. The groups also statistically differed in clinical assessment scores, which were consistent with the strength of the correlations. Patients with a higher gait capacity reacted with more physiological trunk movements to actuated pelvis movements.

CONCLUSION

Actuated pelvis movements do not lead to physiological trunk movements in patients with a poor trunk control, while patients with better walking functions can show physiological trunk movements. Therapists should carefully consider for whom and why they decide to include actuated pelvis movements in their therapy plan.

Mechanical disturbances applied by motorized ankle foot orthosis to adapt ankle muscles activation—A validation study

Background: Reduced function of ankle muscles usually leads to impaired gait. Motorized ankle foot orthoses (MAFOs) have shown potential to improve neuromuscular control and increase volitional engagement of ankle muscles. In this study, we hypothesize that specific disturbances (adaptive resistance-based perturbations to the planned trajectory) applied by a MAFO can be used to adapt the activity of ankle muscles. The first goal of this exploratory study was to test and validate two different ankle disturbances based on plantarflexion and dorsiflexion resistance while training in standing still position. The second goal was to assess neuromuscular adaptation to these approaches, namely, in terms of individual muscle activation and co-activation of antagonists.

Methods: Two ankle disturbances were tested in ten healthy subjects. For each subject, the dominant ankle followed a target trajectory while the contralateral leg was standing still: a) dorsiflexion torque during the first part of the trajectory (Stance Correlate disturbance—StC), and b) plantarflexion torque during the second part of the trajectory (Swing Correlate disturbance—SwC). Electromyography was recorded from the tibialis anterior (TAnt) and gastrocnemius medialis (GMed) during MAFO and treadmill (baseline) trials.

Results: GMed (plantarflexor muscle) activation decreased in all subjects during the application of StC, indicating that dorsiflexion torque did not enhance GMed activity. On the other hand, TAnt (dorsiflexor muscle) activation increased when SwC was applied, indicating that plantarflexion torque succeeded in enhancing TAnt activation. For each disturbance paradigm, there was no antagonist muscle co-activation accompanying agonist muscle activity changes.

Conclusion: We successfully tested novel ankle disturbance approaches that can be explored as potential resistance strategies in MAFO training. Results from SwC training warrant further investigation to promote specific motor recovery and learning of dorsiflexion in neural-impaired patients. This training can potentially be beneficial during intermediate phases of rehabilitation prior to overground exoskeleton-assisted walking. Decreased activation of GMed during StC might be attributed to the unloaded body weight in the ipsilateral side, which typically decreases activation of anti-gravity muscles. Neural adaptation to StC needs to be studied thoroughly in different postures in futures studies.

Effect of exoskeleton-assisted Body Weight-Supported Treadmill Training on gait function for patients with chronic stroke: a scoping review

BACKGROUND

Therapeutic exercise for gait function using an exoskeleton-assisted Body Weight Supported Treadmill Training (BWSTT) has been identified as a potential intervention that allows for task-based repetitive training with appropriate kinematics while adjusting the amount of body weight support (BWS). Nonetheless, its effect on gait in patients with stroke in the chronic phase are yet to be clarified. The primary aim of this scoping review was to present the status of effectiveness of exoskeleton-assisted BWSTT in patients with chronic stroke. The secondary aims were to summarise intervention protocols, types and functions of BWSTT exoskeletal robotic devices currently used clinically.

METHOD AND RESULTS

Articles were accessed and collected from PubMed, Ovid MEDLINE, Cochrane Central Register of Controlled Trials, and Web of Science databases, which were completed in October 2020. Articles were included if the subjects were adults with stroke in the chronic phase (onset ≥ 6 months) and if they utilised a robotic exoskeleton with treadmill and body weight support and investigated the efficacy of gait exercise. A total of 721 studies were identified, of which 11 randomised controlled trials were selected. All included studies were published from 2008 to 2020. Overall, 309 subjects were enrolled; of these, 241 (156 males, 85 females) participated. Walking outcome measures were used more often to evaluate the functional aspects of gait than to evaluate gait independence. In 10 of 11 studies, showed the effectiveness of exoskeleton robot-assisted BWSTT in terms of outcomes contributing to improved gait function. Two studies reported that exoskeleton-assisted BWSTT with combination therapy was significantly more effective in improving than exoskeleton-assisted BWSTT alone. However, no significant difference was identified between the groups; compared with therapist-assisted BWSTT groups, exoskeleton-assisted BWSTT groups did not exhibit significant change.

CONCLUSION

This review suggests that exoskeleton-assisted BWSTT for patients with chronic stroke may be effective in improving walking function. However, the potential may be "to assist" and not because of using the robot. Further studies are required to verify its efficacy and strengthen evidence on intervention protocols.

Assessment methodology for human-exoskeleton interactions: Kinetic analysis based on muscle activation

During the development and assessment of an exoskeleton, many different analyzes need to be performed. The most frequently used evaluate the changes in muscle activations, metabolic consumption, kinematics, and kinetics. Since human-exoskeleton interactions are based on the exchange of forces and torques, the latter of these, kinetic analyzes, are essential and provide indispensable evaluation indices. Kinetic analyzes, however, require access to, and use of, complex experimental apparatus, involving many instruments and implicating lengthy data analysis processes. The proposed methodology in this paper, which is based on data collected via EMG and motion capture systems, considerably reduces this burden by calculating kinetic parameters, such as torque and power, without needing ground reaction force measurements. This considerably reduces the number of instruments used, allows the calculation of kinetic parameters even when the use of force sensors is problematic, does not need any dedicated software, and will be shown to have high statistical validity. The method, in fact, combines data found in the literature with those collected in the laboratory, allowing the analysis to be carried out over a much greater number of cycles than would normally be collected with force plates, thus enabling easy access to statistical analysis. This new approach evaluates the kinetic effects of the exoskeleton with respect to changes induced in the user's kinematics and muscular activation patterns and provides indices that quantify the assistance in terms of torque (AMI) and power (API). Following the User-Center Design approach, which requires driving the development process as feedback from the assessment process, this aspect is critical. Therefore, by enabling easy access to the assessment process, the development of exoskeletons could be positively affected.

Stroke survivor perceptions of using an exoskeleton during acute gait rehabilitation

Robotic-assisted gait training (RAGT) devices allow intensive high repetition of the gait cycle in individuals with locomotor disability, with reduced therapist effort. In addition to usual rehabilitation, RAGT post-stroke improves the likelihood of regaining independent walking, with maximum efficacy identified in the acute and subacute phases of stroke. This study explores the usability and acceptance of RAGT among persons with stroke in an acute hospital setting and examines users’ perceptions of two different modes of robotic assistance provided during rehabilitation. A mixed-methods approach comprised semi-structed interviews of end-user perspectives of RAGT in an acute hospital setting following stroke and two 10-point Likert scales rating how comfortable and how natural robotic gait felt using different assistance modes. Content analysis of qualitative data was undertaken with results synthesised by common meaning units. Quantitative data were reported using summary statistics, with Spearmann’s correlation co-efficient examining the relationship between Likert scale ratings and measures of participants’ stroke related disability. Ten individuals (6 men; 4 women; mean age of 64.5. ± 13 years) were recruited in an acute hospital setting following admission with a stroke diagnosis. Content analysis of interview transcripts identified discussion units centring around positive aspects of how helpful the device was, negative aspects related to set-up time, weight of the device and multiple instructions delivered during use. Initially participants identified that the device could look intimidating, and they feared falling in the device but they subsequently identified the correct mindset for using the device is to trust the technology and not be afraid. Mean ratings for device comfort (7.94 ± 1.4) and how natural walking felt (7.05 ± 1.9) were favourable. Interestingly, a strong relationship was identified, whereby the higher the level of disability, the more natural participants rated walking in the device during maximal assistance mode (rho = 0.62; p = 0.138). This study suggests individuals in the early phases of stroke perceive RAGT to be acceptable and helpful in the main, with some associated negative aspects. Walking in the device was rated as comfortable and natural. Those with greater disability rated the assisted walking as more natural.

"Design of a Suspension Lever Mechanism in Biomedical Robotic System"

The article discusses the design of a suspended lever mechanism with elastic elements, which is used as a safety device in a robotic system for the rehabilitation of the lower limbs. The article analyzes the existing mechanical structures of devices for rehabilitation, identifies the problems of operation, design, and safety systems and suggests a new design of the device. The process of reverse development of a lever mechanism scheme to ensure safety during rehabilitation of the lower limbs is presented. The design of the lever mechanism consists of movable levers connected by elastic elements. The device allows you to dampen the force during active rehabilitation. The power calculation of the lever mechanism in the rehabilitation system was carried out. The article addresses the issues present in the current mechanical designs with a brief discussion on the system architecture.

Comparative effects of passive and active mode robot-assisted gait training on brain and muscular activities in sub-acute and chronic stroke

BACKGROUND

Robot-assisted gait training (RAGT) was initially developed based on the passive controlled (PC) mode, where the target or ideal locomotor kinematic trajectory is predefined and a patient basically 'rides' the robot instead of actively participating in the actual locomotor relearning process. A new insightful contemporary neuroscience and mechatronic evidence suggest that robotic-based locomotor relearning can be best achieved through active interactive (AI) mode rather than PC mode.

OBJECTIVE

The purpose of this study was to compare the pattern of gait-related cortical activity, specifically gait event-related spectral perturbations (ERSPs), and muscle activity from the tibialis anterior (TA) and clinical functional tests in subacute and chronic stroke patients during robot-assisted gait training (RAGT) in passive controlled (PC) and active interactive (AI) modes.

METHODS

The present study involves a two-group pretest-posttest design in which two groups (i.e., PC-RAGT group and AI-RAGT group) of 14 stroke subjects were measured to assess changes in ERSPs, the muscle activation of TA, and the clinical functional tests, following 15- 18 sessions of intervention according to the protocol of each group.

RESULTS

Our preliminary results demonstrated that the power in the μ band (8- 12 Hz) was increased in the leg area of sensorimotor cortex (SMC) and supplementary motor area (SMA) at post-intervention as compared to pre-intervention in both groups. Such cortical neuroplasticity change was associated with TA muscle activity during gait and functional independence in functional ambulation category (FAC) and motor coordination in Fugl- Meyer Assessment for lower extremity (FMA-LE) test as well as spasticity in the modified Ashworth scale (MAS) measures.

CONCLUSIONS

We have first developed a novel neuroimaging experimental paradigm which distinguished gait event related cortical involvement between pre- and post-intervention with PC-RAGT and AI-RAGT in individuals with subacute and chronic hemiparetic stroke.

sEMG Signals Characterization and Identification of Hand Movements by Machine Learning Considering Sex Differences

Developing a robust machine-learning algorithm to detect hand motion is one of the most challenging aspects of prosthetic hands and exoskeleton design. Machine-learning methods that considered sex differences were used to identify and describe hand movement patterns in healthy individuals. To this purpose, surface Electromyographic (sEMG) signals have been acquired from muscles in the forearm and hand. The results of statistical analysis indicated that most of the same muscle pairs in the right hand (females and males) showed significant differences during the six hand movements. Time features were used an as input to machine-learning algorithms for the recognition of six gestures. Specifically, two types of hand-gesture recognition methods that considered sex differences(differentiating sex datasets and adding a sex label)were proposed and applied to the k-nearest neighbor (k-NN), support vector machine (SVM) and artificial neural network (ANN) algorithms for comparison. In addition, a t-test statistical analysis approach and 5-fold cross validation were used as complements to verify whether considering sex differences could significantly improve classification performance. It was demonstrated that considering sex differences can significantly improve classification performance. The ANN algorithm with the addition of a sex label performed best in movement classification (98.4% accuracy). In the future, hand movement recognition algorithms considering sex differences could be applied to control systems for prosthetic hands or exoskeletons.

The effect of pelvic movements of a gait training system for stroke patients: a single blind, randomized, parallel study

BACKGROUND

Aging societies lead to higher demand for gait rehabilitation as age-related neurological disorders such as stroke and spinal cord injury increase. Since conventional methods for gait rehabilitation are physically and economically burdensome, robotic gait training systems have been studied and commercialized, many of which provided movements confined in the sagittal plane. For better outcomes of gait rehabilitation with more natural gait patterns, however, it is desirable to provide pelvic movements in the transverse plane. In this study, a robotic gait training system capable of pelvic motions in the transverse plane was used to evaluate the effect of the pelvic motions on stroke patients.

METHOD

Healbot T, which is a robotic gait training system and capable of providing pelvic movements in the transverse plane as well as flexion/extension of the hip and knee joints and adduction/abduction of the hip joints, is introduced and used to evaluate the effect of the pelvic movement on gait training of stroke patients. Gait trainings in Healbot T with and without pelvic movements are carried out with stroke patients having hemiparesis.

EXPERIMENT

Twenty-four stroke patients with hemiparesis were randomly assigned into two groups and 23 of them successfully completed the experiment except one subject who had dropped out due to personal reasons. Pelvis-on group was provided with pelvic motions whereas no pelvic movement was allowed for pelvis-off group during 10 sessions of gait trainings in Healbot T. Electromyography (EMG) signals and interaction forces as well as the joint angles of the robot were measured. Gait parameters such as stride length, cadence, and walking speed were measured while walking on the ground without assistance of Healbot T after gait training on 1st, 5th, and 10th day.

RESULT

Stride length significantly increased in both groups. Furthermore, cadence and walking speed of the pelvis-on group were increased by 10.6% and 11.8%. Although interaction forces of both groups except the thighs showed no differences, EMG signals from gluteus medius of the pelvis-on group increased by 88.6% during stance phase. In addition, EMG signals of biceps femoris, gastrocnemius medial, and gastrocnemius lateral of the pelvis-on group increased whereas EMG signals of the pelvis-off group except gastrocnemius lateral showed no difference after gait trainings.

CONCLUSION

Gait training using a robotic gait training system with pelvic movements was conducted to investigate the effects of lateral and rotational pelvic movements in gait training of stroke patients. The pelvic movements affected to increase voluntary muscle activation during the stance phase as well as cadence and walking speed.

CLINICAL TRIAL REGISTRATION

KCT0003762, 2018-1254, Registered 28 October 2018, https://cris.nih.go.kr/cris/search/search_result_st01_kren.jsp?seq=14310&ltype=&rtype=.

Gait Improvement in Chronic Stroke Survivors by Using an Innovative Gait Training Machine: A Randomized Controlled Trial

Chronic stroke leads to the impairment of lower limb function and gait performance. After in-hospital rehabilitation, most individuals lack continuous gait training because of the limited number of physical therapists. This study aimed to evaluate the effects of a newly invented gait training machine (I-Walk) on lower limb function and gait performance in chronic stroke individuals. Thirty community-dwelling chronic stroke individuals were allocated to the I-Walk machine group (n = 15) or the overground gait training (control) group (n = 15). Both groups received 30 min of upper limb and hand movement and sit-to-stand training. After that, the I-Walk group received 30 min of I-Walk training, while the control followed a 30-minute overground training program. All the individuals were trained 3 days/week for 8 weeks. The primary outcome of the motor recovery of lower limb impairment was measured using the Fugl-Meyer Assessment (FMA). The secondary outcomes for gait performance were the 6-minute walk test (6 MWT), the 10-meter walk test (10 MWT), and the Timed Up and Go (TUG). The two-way mixed-model ANOVA with the Bonferroni test was used to compare means within and between groups. The post-intervention motor and sensory subscales of the FMA significantly increased compared to the baseline in both groups. Moreover, the 6 MWT and 10 MWT values also improved in both groups. In addition, the mean difference of TUG in the I-Walk was higher than the control. The efficiency of I-Walk training was comparable to overground training and might be applied for chronic stroke gait training in the community.

Mechanical Efficiency Investigation of an Ankle-Assisted Robot for Human Walking With a Backpack-Load

The purpose of this work is to investigate the efficiency of wearable assistive devices under different load-carriage walking. We designed an experimental platform with a lightweight ankle-assisted robot. Eight subjects were tested in three experimental conditions: free walk with load (FWL), power-off with load (POFL), and power-on with load for different levels of force at a walking speed of 3.6 km/h. We recorded the metabolic expenditure and kinematics of the subjects under three levels of load-carried (10%, 20%, and 30% of body mass). We define the critical force, where at a certain load, the robot inputs a certain force to the human body, and with the assistance of this force, the positive effect of the robot on the human body exactly compensates for the negative effect. The critical forces from the fit of the assistive force and metabolic cost curves were 130 N, 160 N, and 215 N at three different load levels. The intrinsic weight of our device increases mechanical work at the ankle as the load weight rises with 2.08 J, 2.43 J, and 2.73 J for one leg during a gait cycle. With weight bearing increasing, the ratio of the mechanical work input by the robot to the mechanical work output by the weight of the device decreases (from 0.904 to 0.717 and 0.513), verifying that the walking assistance efficiency of such devices decreases as the weight rises.

Intramuscular Coherence of the Lower Flexor Muscles during Robotic Ankle-Assisted Gait

A close-fitting assisted walking device (RE-Gait) designed to assist ankle movements might be a novel approach for acquiring the forefoot rocker function in the gait cycle. The purpose of the present study was to investigate the effects of using RE-Gait by evaluating the intramuscular coherence (IMC) of the two parts of the tibialis anterior muscles (TA), which could indicate whether a common synaptic drive is present. Seventeen healthy volunteers walked on a treadmill at a comfortable speed before, during, and immediately after 15-minute RE-Gait intervention. After RE-Gait intervention, IMC of the two parts of the TA muscles in the beta frequency band in the initial swing phase was significantly enhanced during RE-Gait intervention. In addition, IMCs in the beta and low-gamma frequency bands were significantly correlated with the enhancement ratio of the step length. These results suggest that robotic ankle plantar flexion and dorsiflexion assistance in the initial swing phase may be effective for improving gait function with enhancement of the functioning of the sensorimotor loop.

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.

Overground Robot-Assisted Gait Training for Pediatric Cerebral Palsy

The untethered exoskeletal robot provides patients with the freest and realistic walking experience by assisting them based on their intended movement. However, few previous studies have reported the effect of robot-assisted gait training (RAGT) using wearable exoskeleton in children with cerebral palsy (CP). This pilot study evaluated the effect of overground RAGT using an untethered torque-assisted exoskeletal wearable robot for children with CP. Three children with bilateral spastic CP were recruited. The robot generates assistive torques according to gait phases automatically detected by force sensors: flexion torque during the swing phase and extension torque during the stance phase at hip and knee joints. The overground RAGT was conducted for 17~20 sessions (60 min per session) in each child. The evaluation was performed without wearing a robot before and after the training to measure (1) the motor functions using the gross motor function measure and the pediatric balance scale and (2) the gait performance using instrumented gait analysis, the 6-min walk test, and oxygen consumption measurement. All three participants showed improvement in gross motor function measure after training. Spatiotemporal parameters of gait analysis improved in participant P1 (9-year-old girl, GMFCS II) and participant P2 (13-year-old boy, GMFCS III). In addition, they walked faster and farther with lower oxygen consumption during the 6-min walk test after the training. Although participant P3 (16-year-old girl, GMFCS IV) needed the continuous help of a therapist for stepping at baseline, she was able to walk with the platform walker independently after the training. Overground RAGT using a torque-assisted exoskeletal wearable robot seems to be promising for improving gross motor function, walking speed, gait endurance, and gait efficiency in children with CP. In addition, it was safe and feasible even for children with severe motor impairment (GMFCS IV).

Simulated muscle activity in locomotion: implications of co-occurrence between effort minimisation and gait modularity for robot-assisted rehabilitation therapy

Evolution of gait rehabilitation robotic devices for stroke survivors has aimed at providing transparency to user's efforts and implementing 'assist-as-needed' paradigm. Alteration of muscle activity and synergies recruitment has been noticed in trials involving healthy subjects but no analytic tool has been proposed to understand root causes. In this paper, a simplified neuro-mechanical model is introduced for simulating lower limbs' muscle activity during unrestrained and device-constrained gait, taking into consideration exoskeleton-plus-treadmill and end-effector categories. Muscle control is based on the key hypothesis that optimality criterion pursues co-occurrence between effort minimisation and modularity during regular gait. Results highlight that modelised motion constraints on lower body raise additional redundancies which alter muscle activity and increase intervention external to unrestrained gait synergies. Accordingly, the developed simulations help to identify the inherent limitations of current technology: further degree of freedom addition to exoskeleton-plus-treadmill device could be useful but impractical, while end-effector devices would benefit significantly from an improved interaction management.

Five-day rehabilitation of patients undergoing total knee arthroplasty using an end-effector gait robot as a neuromodulation blending tool for deafferentation, weight offloading and stereotyped movement: Interim analysis

Deafferentation and weight offloading can increase brain and spinal motor neuron excitability, respectively. End-effector gait robots (EEGRs) can blend these effects with stereotyped movement-induced neuroplasticity. The authors aimed to evaluate the usefulness of EEGRs as a postoperative neuro-muscular rehabilitation tool. This prospective randomized controlled trial included patients who had undergone unilateral total knee arthroplasty (TKA). Patients were randomly allocated into two groups: one using a 200-step rehabilitation program in an EEGR or the other using a walker on a floor (WF) three times a day for five weekdays. The two groups were compared by electrophysiological and biomechanical methods. Since there were no more enrollments due to funding issues, interim analysis was performed. Twelve patients were assigned to the EEGR group and eight patients were assigned to the WF group. Although the muscle volume of the quadriceps and hamstring did not differ between the two groups, the normalized peak torque of the operated knee flexors (11.28 ± 16.04 Nm/kg) was improved in the EEGR group compared to that of the operated knee flexors in the WF group (4.25 ± 14.26 Nm/kg) (p = 0.04). The normalized compound motor action potentials of the vastus medialis (VM) and biceps femoris (BF) were improved in the EEGR group (p < 0.05). However, the normalized real-time peak amplitude and total, mean area under the curve of VM were decreased during rehabilitation in the EEGR group (p < 0.05). No significant differences were found between operated and non-operated knees in the EEGR group. Five-day EEGR-assisted rehabilitation induced strengthening in the knee flexors and the muscular reactivation of the BF and VM after TKA, while reducing the real-time use of the VM. This observation may suggest the feasibility of this technique: EEGR modulated the neuronal system of the patients rather than training their muscles. However, because the study was underpowered, all of the findings should be interpreted with the utmost caution.

How does physical guidance affect motor learning and learner's workload?

[Purpose] Physical guidance is routinely used in clinical practices such as rehabilitation to facilitate motor learning. Physical guidance would facilitate motor learning and reduce the workload; however, this relationship is unknown. Thus, we aimed to investigate this relationship using a physical guidance device. [Participants and Methods] Twenty-seven healthy young adults were randomly assigned to three groups and underwent varying practice conditions. The participants used a physical guidance device during practice for 2 days, did not use the device during practice for 2 days, or used the device on the first but not the second practice day. Motor learning was assessed by measuring the instability generated by the participants while maintaining a standing position on the Biodex Balance System. Psychological status was evaluated by analyzing the participants’ responses to the National Aeronautics and Space Administration-Task Load Index. [Results] Improved performance was noted in all participants; however, those who used a physical guidance device during practice for 2 days exhibited poor motor learning compared with those assigned to the other two conditions. Frustration was significantly lower in participants who used a physical guidance device during practice than those who did not. [Conclusion] The use of physical guidance during practice can reduce participant frustration, but excessive physical guidance during practice reduces learning efficiency.

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.

Gait Event Detection for Stroke Patients during Robot-Assisted Gait Training

Functional electrical stimulation and robot-assisted gait training are techniques which are used in a clinical routine to enhance the rehabilitation process of stroke patients. By combining these technologies, therapy effects could be further improved and the rehabilitation process can be supported. In order to combine these technologies, a novel algorithm was developed, which aims to extract gait events based on movement data recorded with inertial measurement units. In perspective, the extracted gait events can be used to trigger functional electrical stimulation during robot-assisted gait training. This approach offers the possibility of equipping a broad range of potential robot-assisted gait trainers with functional electrical stimulation. In particular, the aim of this study was to test the robustness of the previously developed algorithm in a clinical setting with patients who suffered a stroke. A total amount of N = 10 stroke patients participated in the study, with written consent. The patients were assigned to two different robot-assisted gait trainers (Lyra and Lokomat) according to their performance level, resulting in five recording sessions for each gait-trainer. A previously developed algorithm was applied and further optimized in order to extract the gait events. A mean detection rate across all patients of 95.8% ± 7.5% for the Lyra and 98.7% ± 2.6% for the Lokomat was achieved. The mean type 1 error across all patients was 1.0% ± 2.0% for the Lyra and 0.9% ± 2.3% for the Lokomat. As a result, the developed algorithm was robust against patient specific movements, and provided promising results for the further development of a technique that can detect gait events during robot-assisted gait training, with the future aim to trigger functional electrical stimulation.

Effects of robotic exoskeleton control options on lower limb muscle synergies during overground walking: An exploratory study among able-bodied adults

BACKGROUND

The effects of lower limb (L/L) control options, developed for overground walking with a wearable robotic exoskeleton (WRE), on the neuromotor control of L/L muscles [i.e., muscle synergies (MSs)] during walking remain uncertain.

OBJECTIVE

To gain initial insights regarding the effects of different control options on the number of MSs at the L/L and on their muscle weighting within each MS when walking with a WRE.

METHODS

Twenty able-bodied adults walked overground without and with the WRE set at two control options with a predetermined foot pathway imposed by the WRE, and at three other control options with free L/L kinematics in the sagittal plane. Surface electromyography of eight right L/L muscles was recorded. MSs were extracted using a non-negative matrix factorisation algorithm. Cosine similarity and correlation coefficients characterised similarities between the MSs characteristics.

RESULTS

Freely moving the L/L in the sagittal plane (i.e., non-trajectory controlled options) during WRE walking best duplicated typical MSs extracted when walking without WRE. Conversely, WRE walking while fully controlling the L/L trajectory presented the lowest correlations to all MSs extracted when walking without WRE, especially during early swing and L/L deceleration.

CONCLUSION

Neuromotor control of L/L muscles is affected by the selected control option during WRE walking, particularly when a predetermined foot pathway is imposed.

SIGNIFICANCE

This exploratory study represents the first step in informing the decision-making process regarding the use of different L/L control options when using WRE and calls for further research among adults with sensorimotor impairments.

[Effectiveness of robotic assistance for gait training in children with cerebral palsy. a systematic review]

INTRODUCTION

In recent years, the use of gait training using robotic assistance systems has progressively increased in the paediatric population with cerebral palsy.

OBJECTIVE

To systematically assess the effects of robotic assistance for gait training compared with physical rehabilitation therapy in children with cerebral palsy (CP), based on the International Classification of Functioning, Health and Disability (ICF).

MATERIALS AND METHODS

A systematic review was carried out according to the recommendations of the Cochrane Collaboration. We included randomised or quasi-randomised clinical trials that analysed children with CP classified according to The Gross Motor Function Classification System (GMFCS) I-III. The search was carried out in PubMed, PEDro, CENTRAL, CINALH, Cochrane, Embase, Europe PMC, LILACS and Science Direct. The selection and extraction of data from the studies was carried out by two independent researchers. Disagreements were resolved by consensus. A descriptive analysis of the selected studies was performed. Assessment of risk of bias was performed with the Cochrane Collaboration tool.

RESULTS

Four studies met the eligibility criteria. Most of the temporal-spatial, kinetic and kinematic parameters of gait were evaluated, all corresponding to the activity component of the ICF.

CONCLUSIONS

Due to the methodological variability of the studies, it is not possible to determine whether robot-assisted gait training is effective for treatment in children with CP.

Analysis of Human-Exoskeleton System Interaction for Ergonomic Design

OBJECTIVE

Lower-limb exoskeleton systems are defined as gait training or walking-assisting devices for spinal cord injury or hemiplegic patients. Crutches, straps, and baffles are designed to protect subjects from falling. However, skin abrasions occur when the interaction forces are too large. In this study, the interaction forces between the human body and an exoskeleton system named the AIDER were measured to confirm whether the design was ergonomic.

BACKGROUND

The AIDER system is a wearable lower-limb exoskeleton. It secures a subject by binding on the waist, thighs, shanks, and feet.

METHOD

Eight healthy subjects participated in the study. The interaction forces of the waist strap, thigh baffles, shank baffles, and crutch handles were measured by pressure sensors. Ten repetitions were completed in this study. After one repetition, custom comfort questionnaires were completed by the subjects.

RESULTS

Although a few of the peak values of the maximum intensities of pressure between the hands and crutch handles reached the minimum value of the pain-pressure threshold (PPT), the average pressure intensities were much smaller than the PPT value.

CONCLUSIONS

The results indicated that the mechanical structure and control strategy of the AIDER must be improved to be more ergonomic in the future.

Effects of bodyweight support and guidance force on muscle activation during Locomat walking in people with stroke: a cross-sectional study

BACKGROUND

Locomat is a robotic exoskeleton providing guidance force and bodyweight support to facilitate intensive walking training for people with stroke. Although the Locomat has been reported to be effective in improving walking performance, the effects of training parameters on the neuromuscular control remain unclear. This study aimed to compare the muscle activities between Locomat walking and treadmill walking at a normal speed, as well as to investigate the effects of varying bodyweight support and guidance force on muscle activation patterns during Locomat walking in people with stroke.

METHODS

A cross-sectional study design was employed. Participants first performed an unrestrained walking on a treadmill and then walked in the Locomat with different levels of bodyweight support (30% or 50%) and guidance force (40% or 70%) at the same speed (1.2 m/s). Surface electromyography (sEMG) of seven muscles of the affected leg was recorded. The sEMG envelope was time-normalised and averaged over gait cycles. Mean sEMG amplitude was then calculated by normalising the sEMG amplitude with respect to the peak amplitude during treadmill walking for statistical analysis. A series of Non-parametric test and post hoc analysis were performed with a significance level of 0.05.

RESULTS

Fourteen participants with stroke were recruited at the Yangzhi Affiliated Rehabilitation Hospital of Tongji University (female n = 1; mean age 46.1 ± 11.1 years). Only the mean sEMG amplitude of vastus medialis oblique during Locomat walking (50% bodyweight support and 70% guidance force) was significantly lower than that during treadmill walking. Reducing both bodyweight and guidance increased muscle activity of gluteus medius and tibialis anterior. Activity of vastus medialis oblique muscle increased as bodyweight support reduced, while that of rectus femoris increased as guidance force decreased.

CONCLUSIONS

The effects of Locomat on reducing muscle activity in people with stroke were minimized when walking at a normal speed. Reducing bodyweight support and guidance force increased the activity of specific muscles during Locomat walking. Effects of bodyweight support, guidance force and speed should be taken into account when developing individualized Locomat training protocols for clients with stroke.

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.

Feasibility of a Sensor-Based Gait Event Detection Algorithm for Triggering Functional Electrical Stimulation during Robot-Assisted Gait Training

Technologies such as robot-assisted gait trainers or functional electrical stimulation can improve the rehabilitation process of people affected with gait disorders due to stroke or other neurological defects. By combining both technologies, the potential disadvantages of each technology could be compensated and simultaneously, therapy effects could be improved. Thus, an algorithm was designed that aims to detect the gait cycle of a robot-assisted gait trainer. Based on movement data recorded with inertial measurement units, gait events can be detected. These events can further be used to trigger functional electrical stimulation. This novel setup offers the possibility of equipping a broad range of potential robot-assisted gait trainers with functional electrical stimulation. The aim of this paper in particular was to test the feasibility of a system using inertial measurement units for gait event detection during robot-assisted gait training. Thus, a 39-year-old healthy male adult executed a total of six training sessions with two robot-assisted gait trainers (Lokomat and Lyra). The measured data from the sensors were analyzed by a custom-made gait event detection algorithm. An overall detection rate of 98.1% ± 5.2% for the Lokomat and 94.1% ± 6.8% for the Lyra was achieved. The mean type-1 error was 0.3% ± 1.2% for the Lokomat and 1.9% ± 4.3% for the Lyra. As a result, the setup provides promising results for further research and a technique that can enhance robot-assisted gait trainers by adding functional electrical stimulation to the rehabilitation process.

Immediate muscle strengthening by an end-effector type gait robot with reduced real-time use of leg muscles: A case series and review of literature

BACKGROUND

De-afferentation or non-weight bearing induces rapid cortical and spinal α-motor neuron excitability. Author supposed that an end-effector type gait robot (EEGR) could provide patients with a training condition that was specific enough to activate rapid cortical/spinal neuroplasticity, leading to immediate muscle strengthening. The electromyographic and biomechanical comparisons were conducted.

AIM

To compare the electromyographic activities of the thigh and shank muscles and isometric peak torque (PT) before and after walking training on a floor or in the end-effector gait robot.

METHODS

Twelve outpatients without ambulatory dysfunction were recruited. Order of two interventions (5-min training on a floor at a comfortable pace or training in an EEGR with non-weight bearing on their feet and 100% guidance force at 2.1 km/h) were randomly chosen. Isometric PT, maximal ratio of torque development, amplitude of compound motor action potential (CMAP), and area under the curve (AUC) were evaluated before and 10 min after both interventions.

RESULTS

The degree of PT improvement of the dominant knee flexors was larger in the EEGR than on the floor (9.6 ± 22.4 Nm/BW, P < 0.01). The EEGR-trained patients had greater PT improvement of the dominant knee extensors than those who trained on the floor (4.5 ± 28.1 Nm/BW, P < 0.01). However, all electromyographic activities of the thigh and shank muscles (peak CMAP, mean and peak AUC) were significantly lower for the use of the EEGR than walking on the floor.

CONCLUSION

Immediate strengthening of the knee flexors and extensors was induced after the 5-min EEGR training, despite reduced muscular use.

Muscle Synergies During Repetitive Stoop Lifting With a Bioelectrically-Controlled Lumbar Support Exoskeleton

Lower back problems are common in the world, which leads to the development of various lumbar support exoskeletons to alleviate this problem. In general, previous studies evaluating lumbar support devices quantified assistance by reporting the reduction in back muscle activity and perceived fatigue. However, despite the beneficial effects of such devices, the effects of using such exoskeletons on muscle coordination are not well-studied. In this study, we examined the short-term change in muscle coordination of subjects using a bioelectrically-controlled lumbar support exoskeleton in a fatiguing stoop lifting task with muscle synergy analysis. Results indicate that muscle coordination changes were dominated by changes in timing coefficients, with minimal change in muscle synergy vectors. Analysis on muscle coordination changes would be useful to design future generations of exoskeletons.

EMG Muscle Activation Pattern of Four Lower Extremity Muscles during Stair Climbing, Motor Imagery, and Robot-Assisted Stepping: A Cross-Sectional Study in Healthy Individuals

BACKGROUND

Stair climbing can be a challenging part of daily life and a limiting factor for social participation, in particular for patients after stroke. In order to promote motor relearning of stair climbing, different therapeutical measures can be applied such as motor imagery and robot-assisted stepping therapy. Both are common therapy measures and a positive influence on the rehabilitation process has been reported. However, there are contradictory results regarding the neuromuscular effect of motor imagery, and the effect of robot-assisted tilt table stepping on the EMG activation compared to stair climbing itself is not known. Thus, we investigated the EMG activity during (1) a stepping task on the robot-assisted tilt table Erigo, (2) motor imagery of stair climbing, and (3) real stair climbing in healthy individuals for a subsequent study on patients with lower limb motor impairment. The aim was to assess potential amplitude independent changes of the EMG activation as a function of the different conditions.

METHODS

EMG data of four muscles of the dominant leg were recorded in m. rectus femoris, m. biceps femoris, m. tibialis anterior, and m. gastrocnemius medialis. The cross-correlation analysis was performed to measure similarity/dissimilarity of the EMG curves.

RESULTS

The data of the study participants revealed high cross-correlation coefficients comparing the EMG activation modulation of stair climbing and robot-assisted tilt table stepping in three muscles except for the m. gastrocnemius medialis. As the EMG activation amplitude did not differ between motor imagery and the resting phase the according EMG data of the motor imagery condition were not subjected to a further analysis.

CONCLUSION

Robot-assisted tilt table stepping, but rather not motor imagery, evokes a similar activation in certain leg muscles compared to real stair climbing.

Immediate after-effects of robot-assisted gait with pelvic support or pelvic constraint on overground walking in healthy subjects

Background

Recovery of walking is a primary rehabilitation goal of most stroke survivors. Control of pelvic movements is one of the essential determinants of gait, yet surprisingly, conventional robot-assisted gait trainers constrain pelvic movements. Novel robot-assisted gait trainers, such as LOPES II, are able to support pelvic movements during gait. The aim of this cross-over study was to investigate the immediate after-effects of pelvic support (PS) or pelvic constraint (PC) gait training with LOPES II on overground walking in healthy subjects.

Methods

Thirteen able-bodied subjects (22.8 ± 2.1 years) participated in two 20-min gait training sessions with LOPES II; one with PS and one with PC. During the PS-training, the LOPES II actively guided the lateral displacement of the pelvis, while pelvic rotations were free. During the PC-condition, both lateral displacement and pelvic rotations were constrained and reduced to a minimum. The training sessions were separated by a 30-min resting period. Lateral displacement of the pelvis, hip and knee kinematics, and spatiotemporal parameters during overground walking were determined at baseline and immediately following the training using 3D gait analysis.

Results

During the PS-condition in LOPES II the lateral pelvic displacement was significantly greater (105.6 ± 0 .5 mm) than during the PC-condition (10.8 ± 0 .7 mm; p < 0.001). Analysis of the first five steps of overground walking immediately following PC-condition showed significantly smaller lateral displacements of the pelvis (32.3 ± 12.0 mm) compared to PS-condition (40.1 ± 9 .8 mm; p < 0.01). During the first five steps, step width was significantly smaller after PC-condition (0.17 ± 0. 04 m) compared to PS-condition (0.20 ± 0.04 m; p = 0.01) and baseline (0.19 ± 0. 03 m; p = 0.01). Lateral displacement of the pelvis and step width post training returned to baseline levels within 10 steps. PC- nor PS-condition affected kinematics, gait velocity, cadence, stride length or stance time.

Conclusions

In healthy subjects, robot-assisted gait training with pelvic constraint had immediate negative after-effects on the overground walking pattern, as compared to robot-assisted gait training with pelvic support. Gait training including support of the lateral displacement of the pelvis better resembles the natural gait pattern. It remains to be identified whether pelvic support during robot-assisted gait training is superior to pelvic constraint to promote gait recovery in individuals with neurological disorders.

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.

Alterations in muscle activation patterns during robot-assisted bilateral training: A pilot study

Robot-assisted bilateral training is being developed as a new rehabilitation approach for stroke patients. However, there is still a lack of understanding of muscle functions when performing robot-assisted synchronous movements. The aim of this work is to explore the muscle activation patterns and the voluntary effort of participants during different robot-assisted bilateral training protocols. To this end, 10 healthy participants were recruited to take part in a 60-minute experiment. The experiment included two different bilateral exercises, and each exercise contained four different training protocols. Trajectories of the robots, interaction force and surface electromyogram signals were recorded during training. The results show that the robots do affect the muscle activation patterns during different training protocols and exercises rather than the controller. Specifically, the activity of muscles is reduced in robot-assisted training but is increased in active force involved robot-assisted training when compared to robot-unassisted training. Meanwhile, the voluntary effort of participants can be presented by the adjusted trajectories via the controller. In addition, the results also suggest that the activations for the same muscle groups in the left and right arms are highly correlated with each other in both exercises. Furthermore, the training protocols and methods developed in this work could be further extended in future clinical trials to investigate therapeutic outcomes for patients as well as to better understand bilateral recovery processes.

The effect of a novel gait retraining device on lower limb kinematics and muscle activation in healthy adults

The Re-Link Trainer (RLT) is a modified walking frame with a linkage system designed to apply a non-individualized kinematic constraint to normalize gait trajectory of the left limb. The premise behind the RLT is that a user's lower limb is constrained into a physiologically normal gait pattern, ideally generating symmetry across gait cycle parameters and kinematics. This pilot study investigated adaptations in the natural gait pattern of healthy adults when using the RLT compared to normal overground walking. Bilateral lower limb kinematic and electromyography data were collected while participants walked overground at a self-selected speed, followed by walking in the RLT. A series of 2-way analyses of variance examined between-limb and between-condition differences. Peak hip extension and knee flexion were reduced bilaterally when walking in the RLT. Left peak hip extension occurred earlier in the gait cycle when using the RLT, but later for the right limb. Peak hip flexion was significantly increased and occurred earlier for the constrained limb, while peak plantarflexion was significantly reduced. Peak knee flexion and plantarflexion in the right limb occurred later when using the RLT. Significant bilateral reductions in peak electromyography amplitude were evident when walking in the RLT, along with a significant shift in when peak muscle activity was occurring. These findings suggest that the RLT does impose a significant constraint, but generates asymmetries in lower limb kinematics and muscle activity patterns. The large interindividual variation suggests users may utilize differing motor strategies to adapt their gait pattern to the imposed constraint.

Empowering lower limbs exoskeletons: state-of-the-art

Given the advanced breakthroughs in the field of supportive robotic technologies, interest in the integration of the human body and a robot into a single system has rapidly increased. The aim of this work is to provide an overview of empowering lower limbs exoskeletons. Along with lower exoskeleton limbs, their unique design concepts, operator–exoskeleton interactions and control strategies are described. Although many problems have been solved in recent development, many challenges remain. Especially in the context of infantry soldiers, fire fighters and rescuers, the challenges of empowering exoskeletons are discussed, and improvements are outlined and described. This study is not only a summary of the current state, but also points to weaknesses of empowering lower limbs exoskeletons and outlines possible improvements.