BackgroundRobotic wearable exoskeletons have been utilized as a gait training device in persons with spinal cord injury. This pilot study investigated the feasibility of offering exoskeleton-assisted gait training (EGT) on gait in individuals with incomplete spinal cord injury (iSCI) in preparation for a phase III RCT. The objective was to assess treatment reliability and potential efficacy of EGT and conventional physical therapy (CPT).MethodsForty-four individuals were screened, and 13 were eligible to participate in the study. Nine participants consented and were randomly assigned to receive either EGT or CPT with focus on gait. Subjects received EGT or CPT, five sessions a week (1 h/session daily) for 3 weeks. American Spinal Injury Association (ASIA) Lower Extremity Motor Score (LEMS), 10-Meter Walk Test (10MWT), 6-Minute Walk Test (6MWT), Timed Up and Go (TUG) test, and gait characteristics including stride and step length, cadence and stance, and swing phase durations were assessed at the pre- and immediate post- training. Mean difference estimates with 95% confidence intervals were used to analyze the differences.ResultsAfter training, improvement was observed in the 6MWT for the EGT group. The CPT group showed significant improvement in the TUG test. Both the EGT and the CPT groups showed significant increase in the right step length. EGT group also showed improvement in the stride length.ConclusionEGT could be applied to individuals with iSCI to facilitate gait recovery. The subjects were able to tolerate the treatment; however, exoskeleton size range may be a limiting factor in recruiting larger cohort of patients. Future studies with larger sample size are needed to investigate the effectiveness and efficacy of exoskeleton-assisted gait training as single gait training and combined with other gait training strategies.Trial registrationClinicaltrials.org, NCT03011099, retrospectively registered on January 3, 2017.

Active lower limb transfemoral prostheses have enabled amputees to perform different locomotion modes such as walking, stair ascent, stair descent, ramp ascent and ramp descent. To achieve seamless mode transitions, these devices either rely on neural information from the amputee's residual limbs or sensors attached to the prosthesis to identify the intended locomotion modes or both. We present an approach for classification of locomotion modes based on the framework of muscle synergies underlying electromyography signals. Neural information at the critical instances (e.g., heel contact and toe-off) was decoded for this purpose. Non-negative matrix factorization was used to extract the muscles synergies from the muscle feature matrix. The estimation of the neural command was done using non-negative least squares. The muscle synergy approach was compared with linear discriminant analysis (LDA), support vector machine (SVM), and neural network (NN) and was tested on seven able-bodied subjects. There was no significant difference ( p > 0.05 ) in transitional and steady state classification errors during stance phase. The muscle synergy approach performed significantly better ( ) than NN and LDA during swing phase while results were similar to SVM. These results suggest that the muscle synergy approach can be used to discriminate between locomotion modes involving transitions.

No abstract

Objective. Powered exoskeletons have been used to help persons with gait impairment regain some walking ability. However, little is known about its impact on neuromuscular coordination in persons with stroke. The objective of this study is to investigate how a powered exoskeleton could affect the neuromuscular coordination of persons with post-stroke hemiparesis. Approach. Eleven able-bodied subjects and ten stroke subjects participated in a single-visit treadmill walking assessment, in which their motion and lower-limb muscle activities were captured. By comparing spatiotemporal parameters, kinematics, and muscle synergy pattern between two groups, we characterized the normal gait pattern and the post-stroke motor deficits. Five eligible stroke subjects received exoskeleton-assisted gait trainings and walking assessments were conducted pre-intervention (Pre) and post-intervention (Post), without (WO) and with (WT) the exoskeleton. We compared their gait performance between (a) Pre and Post to investigate the effect of exoskeleton-assisted gait training and, (b) WO and WT the exoskeleton to investigate the effect of exoskeleton wearing on stroke subjects. Main results. While four distinct motor modules were needed to describe lower-extremity activities during stead-speed walking among able-bodied subjects, three modules were sufficient for the paretic leg from the stroke subjects. Muscle coordination complexity, module composition and activation timing were preserved after the training, indicating the intervention did not significantly change the neuromuscular coordination. In contrast, walking WT the exoskeleton altered the stroke subjects’ synergy pattern, especially on the paretic side. The changes were dominated by the activation profile modulation towards the normal pattern observed from the able-bodied group. Significance. This study gave us some critical insight into how a powered exoskeleton affects the stroke subjects’ neuromuscular coordination during gait and demonstrated the potential to use muscle synergy as a method to evaluate the effect of the exoskeleton training. This study was registered at ClinicalTrials.gov (identifier: NCT03057652).

Context: To investigate the feasibility of combining the lower-limb exoskeleton and body weight unweighing technology for assisted walking in tetraplegia following spinal cord injury (SCI). Findings: A 66-year-old participant with a complete SCI at the C7 level, graded on the American Spinal Injury Association Impairment Scale (AIS) as AIS A, participated in nine sessions of overground walking with the assistance from exoskeleton and body weight unweighing system. The participant could tolerate the intensity and ambulate with exoskeleton assistance for a short distance with acceptable and appropriate gait kinematics after training. Conclusion: This report showed that using technology can assist non-ambulatory individuals following SCI to stand and ambulate with assistance which may promote general physical and psychological health if used in the long term.

No abstract

BackgroundSpasticity, characterized by hyperreflexia, is a motor impairment that can arise following a hemispheric stroke. While the neural mechanisms underlying spasticity in chronic stroke survivors are unknown, one probable cause of hyperreflexia is increased motoneuron (MN) excitability. Potential sources of increased spinal MN excitability after a stroke include increased vestibulospinal (VS) and/or reticulospinal (RS) drive. Spasticity, as clinically assessed in stroke survivors, is highly lateralized, thus RS contributions to stroke-induced spasticity are more difficult to reconcile, as RS nuclei routinely project bilaterally to the spinal cord. Yet studies in stroke survivors suggest that there may also be changes in neuromodulation at the spinal level, indicative of RS tract influence. We hypothesize that after hemispheric stroke, alterations in the excitability of the RS nuclei affect both sides of the spinal cord, and thereby contribute to increased MN excitability on both paretic/spastic and contralateral sides of stroke survivors, as compared to neurologically intact subjects.MethodsWe estimated stretch reflex thresholds of the biceps brachii (BB) muscle using a position-feedback controlled linear motor to progressively indent the BB distal tendon in both spastic and contralateral limbs of hemispheric stroke survivors and in age-matched intact subjects.ResultsOur previously reported results show a significant difference between reflex thresholds of spastic and contralateral limbs of stroke survivors recorded from BB-medial (p < 0.005) and BB-lateral (p < 0.001). For this study, we report that there is also a significant difference between the reflex thresholds in the contralateral limb of stroke subjects and the dominant arm of intact subjects, again measured from both BB-medial (p < 0.05) and BB-lateral (p < 0.05).ConclusionThe reduction in stretch reflex thresholds in the contralateral limb of stroke survivors, based here on comparisons with thresholds of intact subjects, suggests an increased MN excitability on contralateral sides of stroke survivors as compared to intact subjects. This in turn supports our contention that RS tract activation, which has bilateral descending influences, is at least partially responsible for increased stretch reflex excitability, post-stroke, as both contralateral and affected sides show increased MN excitability as compared to intact subjects. Still, spasticity, presently diagnosed only on the affected side, with increased MN excitability on the affected side as compared to the contralateral side (our previous study), may be due to a different strongly lateralized pathway, such as the VS tract, which has not been directly tested here. Currently available clinical methods of spasticity assessment, such as the Modified Ashworth Scale, lack the resolution to quantify this phenomenon of a bilateral increase in MN excitability.

Myoelectric control of lower limb prostheses requires discrimination of task-specific muscle patterns. In this paper we present a method based on the notion of muscle synergies to discriminate between various non-weight-bearing movements such as knee extension/flexion, femur rotation in/out, tibia rotation in/out and ankle dorsiflexion/plantarflexion. Data is recorded from eight targeted muscle sites on the thigh. Non-negative matrix factorization is used to identify the muscle synergies using multiple features and estimation of electromyographic (EMG) patterns is done using non-negative least squares (NNLS). Classification accuracy for the movements involving the knee joint was higher than the movements involving the ankle joint. The proposed algorithm performs at par with the common machine learning algorithm Linear Discriminant Analysis (LDA) in offline analysis.