Wearable exoskeleton control modes selected during overground walking affect muscle synergies in adults with a chronic incomplete spinal cord injury

Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness

BACKGROUND

In the past decade, there has been substantial progress in the development of robotic controllers that specify how lower-limb exoskeletons should interact with brain-injured patients. However, it is still an open question which exoskeleton control strategies can more effectively stimulate motor function recovery. In this review, we aim to complement previous literature surveys on the topic of exoskeleton control for gait rehabilitation by: (1) providing an updated structured framework of current control strategies, (2) analyzing the methodology of clinical validations used in the robotic interventions, and (3) reporting the potential relation between control strategies and clinical outcomes.

METHODS

Four databases were searched using database-specific search terms from January 2000 to September 2020. We identified 1648 articles, of which 159 were included and evaluated in full-text. We included studies that clinically evaluated the effectiveness of the exoskeleton on impaired participants, and which clearly explained or referenced the implemented control strategy.

RESULTS

(1) We found that assistive control (100% of exoskeletons) that followed rule-based algorithms (72%) based on ground reaction force thresholds (63%) in conjunction with trajectory-tracking control (97%) were the most implemented control strategies. Only 14% of the exoskeletons implemented adaptive control strategies. (2) Regarding the clinical validations used in the robotic interventions, we found high variability on the experimental protocols and outcome metrics selected. (3) With high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented a combination of trajectory-tracking and compliant control showed the highest clinical effectiveness for acute stroke. However, they also required the longest training time. With high grade of evidence and low number of participants (N = 8), assistive control strategies that followed a threshold-based algorithm with EMG as gait detection metric and control signal provided the highest improvements with the lowest training intensities for subacute stroke. Finally, with high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented adaptive oscillator algorithms together with trajectory-tracking control resulted in the highest improvements with reduced training intensities for individuals with chronic stroke.

CONCLUSIONS

Despite the efforts to develop novel and more effective controllers for exoskeleton-based gait neurorehabilitation, the current level of evidence on the effectiveness of the different control strategies on clinical outcomes is still low. There is a clear lack of standardization in the experimental protocols leading to high levels of heterogeneity. Standardized comparisons among control strategies analyzing the relation between control parameters and biomechanical metrics will fill this gap to better guide future technical developments. It is still an open question whether controllers that provide an on-line adaptation of the control parameters based on key biomechanical descriptors associated to the patients' specific pathology outperform current control strategies.

Comparison of the dynamics of exoskeletal-assisted and unassisted locomotion in an FDA-approved lower extremity device: Controlled experiments and development of a subject-specific virtual simulator

Robotic exoskeletons have considerable, but largely untapped, potential to restore mobility in individuals with neurological disorders, and other conditions that result in partial or complete immobilization. The growing demand for these devices necessitates the development of technology to characterize the human-robot system during exoskeletal-assisted locomotion (EAL) and accelerate robot design refinements. The goal of this study was to combine controlled experiments with computational modeling to build a virtual simulator of EAL. The first objective was to acquire a minimum empirical dataset comprising human-robot kinematics, ground reaction forces, and electromyography during exoskeletal-assisted and unassisted locomotion from an able-bodied participant. The second objective was to quantify the dynamics of the human-robot system using a subject-specific virtual simulator reproducing EAL compared to the dynamics of normal gait. We trained an able-bodied participant to ambulate independently in a Food and Drug Administration-approved exoskeleton, the ReWalk P6.0 (ReWalk Robotics, Yoknaem, Israel). We analyzed the motion of the participant during exoskeletal-assisted and unassisted walking, sit-to-stand, and stand-to-sit maneuvers, with simultaneous measurements of (i) three-dimensional marker trajectories, (ii) ground reaction forces, (iii) electromyography, and (iv) exoskeleton encoder data. We created a virtual simulator in OpenSim, comprising a whole-body musculoskeletal model and a full-scale exoskeleton model, to determine the joint kinematics and moments during exoskeletal-assisted and unassisted maneuvers. Mean peak knee flexion angles of the human subject during exoskeletal-assisted walking were 50.1° ± 0.6° (left) and 52.6° ± 0.7° (right), compared to 68.6° ± 0.3° (left) and 70.7° ± 1.1° (right) during unassisted walking. Mean peak knee extension moments during exoskeletal-assisted walking were 0.10 ± 0.10 Nm/kg (left) and 0.22 ± 0.11 Nm/kg (right), compared to 0.64 ± 0.07 Nm/kg (left) and 0.73 ± 0.10 Nm/kg (right) during unassisted walking. This work provides a foundation for parametric studies to characterize the effects of human and robot design variables, and predictive modeling to optimize human-robot interaction during EAL.

Unilateral symptomatic Achilles tendinopathy has limited effects on bilateral lower limb ground reaction force asymmetries and muscular synergy attributes when walking at natural and fast speeds

BACKGROUND

Achilles tendinopathy (AT) may affect ground reaction force (GRF) and muscle synergy (MS) during walking due to pain, biological integrity changes in the tendon and neuroplastic adaptations. The objective of this study was to compare GRF asymmetries and MS attributes between symptomatic and asymptomatic lower limbs (LL) during walking at natural and fast speeds in adults with unilateral AT.

METHODS

A convenience sample consisting of twenty-eight participants walked on an instrumented treadmill at natural (1.3 m/s) and fast (1.6 m/s) speeds. Peak GRF were measured in mediolateral, anteroposterior and vertical directions. Individualized electromyography (EMG) activation profiles were time- and amplitude-normalized for three consecutive gait cycles and MS were extracted using non-negative matrix factorization algorithms. MS were characterized by the number, composition (i.e., weighting of each muscle) and temporal profiles (i.e., duration and amplitude) of the MS extracted during walking. Paired Student's t-tests assessed peak GRF and MS muscle weighting differences between sides whereas Pearson correlation coefficients characterized the similarities of the individualized EMG and MS activation temporal profiles within sides.

RESULTS

AT had limited effects on peak GRF asymmetries and the number, composition and temporal profiles of MS between symptomatic and asymptomatic LL while walking on a level treadmill at natural and fast speeds. In most participants, four MS with a specific set of predominantly activated muscles were extracted across natural (71 and 61%) and fast (54 and 50%) walking speeds for the symptomatic and asymptomatic side respectively. Individualized EMG activation profiles were relatively similar between sides (r = 0.970 to 0.999). As for MS attributes, relatively similar temporal activation profiles (r = 0.988 to 0.998) and muscle weightings (p < 0.05) were found between sides for all four MS and the most solicited muscles. Although the faster walking speed increased the number of merged MS for both sides, it did not significantly alter MS symmetry.

CONCLUSION

Faster walking speed increased peak GRF values but had limited effects on GRF symmetries and MS attribute differences between the LL. Corticospinal neuroplastic adaptations associated with chronic unilateral AT may explain the preserved quasi-symmetric LL motor control strategy observed during natural and fast walking among adults with chronic unilateral AT.

Efficacy of robotic exoskeleton for gait rehabilitation in patients with subacute stroke : a systematic review

BACKGROUND

Stroke is the most common cause of disability in Western Countries. It can lead to loss of mobility, capability to walk and ultimately loss of independence in activities of daily living (ADL). Several rehabilitative approaches have been proposed in these years. Robot-assisted gait rehabilitation (RAGT) plays a crucial role to perform a repetitive, intensive, and task-oriented treatment in stroke survivors. However, there are still few data on its role in subacute stroke patients.

AIM

The aim of the present study was to assess the efficacy of RAGT for gait recovery in subacute stroke survivors.

DESIGN

Systematic review with meta-analysis.

SETTING

The setting of the study included Units of Rehabilitation.

POPULATION

The analyzed population was represented by subacute stroke patients.

METHODS

PubMed, Scopus, Web of Science, CENTRAL, and PEDro were systematically searched until January 18, 2021, to identify randomized controlled trials (RCTs) presenting: stroke survivors in subacute phase (≤6 months) as participants; exoskeleton robots devices as intervention; conventional rehabilitation as a comparator; gait assessment, through qualitative scales, quantitative gait scales or quantitative parameters, as outcome measures. We also performed a meta-analysis of the mean difference in the functional ambulation category (FAC) via the random effect method.

RESULTS

Out of 3188 records, 14 RCTs were analyzed in this systematic review. The 14 studies have been published in the last 14 years (from 2006 to 2021) and included 576 stroke survivors, of which 306 received RAGT, and 270 underwent conventional rehabilitation. Lokomat robotic system was the most investigated robotic exoskeleton by the RCTs included (N.=9), albeit the meta-analysis demonstrated a non-significant difference of -0.09 in FAC (95% CI: -0.22.0.03) between Lokomat and conventional therapy. According to the PEDro scale, 11 (78.5%) were classified as good-quality studies, two as fair-quality studies (14.3%), and one as poor-quality study (7.1%).

CONCLUSIONS

Taken together, these findings showed that RAGT might have a potential role in gait recovery in subacute stroke survivors. However, further RCTs comparing the efficacy of RAGT with conventional physical therapy are still warranted in the neurorehabilitation field.

CLINICAL REHABILITATION IMPACT

This systematic review provides information on the efficacy of RAGT in allowing subacute stroke patients to perform high-intensity gait training with a lower physical burden on PRM professionals.

Primitive muscle synergies reflect different modes of coordination in upper limb motions

The motor system relies on the recruitment of motor modules to perform various movements. Muscle synergies are the modules used by the central nervous system to simplify the control of complex motor tasks. In this paper, we aim to explore the primitive synergies to reflect different modes of coordination in upper limb motions. Muscle synergies and corresponding activation coefficients were extracted via non-negative matrix factorization from the electromyography signals of three basic and four complex upper limb motions in sagittal plane and coronal plane. Similarities of muscle synergies and activation coefficients between different tasks and different subjects were compared. Moreover, we used network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. The results showed that the combination of different sets of primitive muscle synergies can achieve complex motions in different planes. The muscle synergy network topology differed significantly between different tasks. We also demonstrated the potential of this study for the understanding of human motor control mechanism and implications for neurorehabilitation.

Effects of an exoskeleton-assisted gait training on post-stroke lower-limb muscle coordination

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).

Processing Surface EMG Signals for Exoskeleton Motion Control

The surface electromyography (sEMG) signal has been used for volitional control of robotic assistive devices. There are still challenges in improving system performance accuracy and signal processing to remove systematic noise. This study presents procedures and a pilot validation of the EMG-driven speed-control of exoskeleton and integrated treadmill with a goal to provide better interaction between a user and the system. The gait cycle duration (GCD) was extracted from sEMG signals using the autocorrelation algorithm and Bayesian fusion algorithm. GCDs of various walking speeds were then programmed to control the motion speed of exoskeleton robotic system. The performance and efficiency of this sEMG-controlled robotic assistive ambulation system was tested and validated among 6 healthy volunteers. The results demonstrated that the autocorrelation algorithm extracted the GCD from individual muscle contraction. The GCDs of individual muscles had variability between different walking steps under a designated walking speed. Bayesian fusion algorithms processed the GCDs of multiple muscles yielding a final GCD with the least variance. The fused GCD effectively controlled the motion speeds of exoskeleton and treadmill. The higher amplitude of EMG signals with shorter GCD was found during a faster walking speed. The algorithms using fused GCDs and gait stride length yielded trajectory joint motion tracks in a shape of sine curve waveform. The joint angles of the exoskeleton measured by a decoder mounted on the hip turned out to be in sine waveforms. The hip joint motion track of the exoskeleton matched the angles projected by trajectory curve generated by computer algorithms based on the fused GCDs with high agreement. The EMG-driven speed-control provided the human-machine inter-limb coordination mechanisms for an intuitive speed control of the exoskeleton-treadmill system at the user's intents. Potentially the whole system can be used for gait rehabilitation of incomplete spinal cord hemispheric stroke patients as goal-directed and task-oriented training tool.