[Abstract + References] The effects of ankle-foot orthoses on walking speed in patients with stroke: a systematic review and meta-analysis of randomized controlled trials

Abstract

Objective:

The aim of this study was to evaluate the effects of ankle-foot orthoses on speed walking in patients with stroke.

Data sources:

PubMed, Embase, Web of Science, Scopus, CENTRAL, PEDro, RehabData, RECAL, and ProQuest were searched from inception until 30 September 2019.

Review methods:

This study was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline statement. Risk of bias assessment was performed using the Cochrane Risk of Bias Tool. Begg’s test and Egger’s regression method were used to assess the publication bias. Trim and fill analysis was also used to adjust any potential publication bias. Sensitivity analysis was performed to evaluate the effect of individual studies. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria.

Results:

Overall, 14 studies were included with a total of 1186 participants. A small-to-moderate and non-significant improvement in favor of the ankle-foot orthosis versus without ankle-foot orthosis (standardized mean difference (SMD) = 0.41, 95% confidence interval = −0.15 to 0.96), similar effects of ankle-foot orthosis and functional electrical stimulation (SMD = 0.00, 95% confidence interval = −0.16 to 0.16), and a small and non-significant improvement in favor of ankle-foot orthosis versus another type of ankle-foot orthosis (SMD = 0.22, 95% confidence interval = −0.05 to 0.49) in walking speed were found. However, the quality of evidence for all comparisons was low or very low.

Conclusion:

Despite reported positive effects in some studies, there is no firm evidence of any benefit of ankle-foot orthoses on walking speed.

References

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Via https://journals.sagepub.com/doi/abs/10.1177/0269215519887784

[ARTICLE] Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people – Full Text

Abstract

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.

Background

Safe and independent locomotion represents a fundamental motor function for humans that is essential for self-contained living and good quality of life [1,2,3,4,5]. Locomotion requires the ability to coordinate a number of different muscles acting on different joints [6,7,8], which are guided by cortical and subcortical brain structures within the locomotor network [9]. Structural and functional changes within the locomotor network are often accompanied by gait and balance impairments which are frequently considered to be the most significant concerns in individuals suffering from brain injuries or neurological diseases [5, 10, 11]. Reduced walking speeds and step lengths [12] as well as non-optimal amount of gait variability [13,14,15] are common symptoms associated with gait impairments that increase the risk of falling [16].

In addition to manual-assisted therapy, robotic neurorehabilitation has often been applied in recent years [17, 18] because it provides early, intensive, task-specific and multi-sensory training which is thought to be effective for balance and gait recovery [17, 19, 20]. Depending on the severity of the disease, movements can be completely guided or assisted, tailored to individual needs [17], using either stationary robotic systems or wearable powered exoskeletons.

Previous studies investigated the effectiveness of robot-assisted gait training (RAGT) in patients suffering from stroke [21, 22], multiple sclerosis [23,24,25,26], Parkinson’s disease [27, 28], traumatic brain injury [29] or spinal cord injury [30,31,32]. Positive effects of RAGT on walking speed [33, 34], leg muscle force [23] step length, and gait symmetry [29, 35] were reported. However, the results of different studies are difficult to summarize due to the lack of consistency in protocols and settings of robotic-assisted treatments (e.g., amount and frequency of training sessions, amount and type of provided robotic support) as well as fragmentary knowledge of the effects on functional brain reorganization, motor recovery and their relation [36, 37]. Therefore, it is currently a huge challenge to draw guidelines for robotic rehabilitation protocols [22, 36,37,38]. To design prologned personalized training protocols in robotic rehabilitation to maximize individual treatment effects [37], it is crucial to increase the understanding of changes in locomotor patterns [39] and brain signals [40] underlying RAGT and how they are related [36, 41].

A series of studies investigated the effects of robotic assistance (RA) on biomechanical gait patterns in healthy people [39, 42,43,44]. On one side, altered gait patterns were reported during robot-assisted walking (RAW) compared to unassisted walking (UAW), in particular, substantially higher muscle activity in the quadriceps, gluteus and adductor longus leg muscles and lower muscle activity in the gastrocnemius and tibialis anterior ankle muscles [39, 42] as well as reduced  lower-body joint angles due to the little medial-lateral hip movements [45,46,47]. On the other side, similar muscle activation patterns were observed during RAW compared to UAW [44, 48, 49], indicating that robotic devices allow physiological muscle activation patterns during gait [48]. However, it is hypothesized that the ability to execute a physiological gait pattern depends on how the training parameters such as body weight support (BWS), guidance force (GF) or kinematic restrictions in the robotic devices are set [44, 48, 50]. For example, Aurich-Schuler et al. [48] reported that the movements of the trunk and pelvis are more similar to UAW on a treadmill when the pelvis is not fixed during RAW, indicating that differences in musle activity and kinematic gait characteristics between RAW and UAW are due to the reduction in degrees of freedom that user’s experience while walking in the robotic device [45]. In line with this, a clinical concern that is often raised with respect to RAW is the lack of gait variability [45, 48, 50]. It is assumed that since the robotic systems are often operated with 100% GF, which means that the devices attempt to force a particular gait pattern regardless of the user’s intentions, the user lacks the ability to vary and adapt his gait patterns [45]. Contrary to this, Hidler et al. [45] observed differences in kinematic gait patterns between subsequent steps during RAW, as demonstrated by variability in relative knee and hip movements. Nevertheless, Gizzi et al. [49] showed that the muscular activity during RAW was clearly more stereotyped and similar among individuals compared to UAW. They concluded that RAW provides a therapeutic approach to restore and improve walking that is more repeatable and standardized than approaches based on exercising during UAW [49].

In addition to biomechanical gait changes, insights into brain activity and intervention-related changes in brain activity that relate to gait responses, will contribute to the optimization of therapy interventions [41, 51]. Whereas the application of functional magnetic resonance imaging (fMRI), considered as gold standard for the assessment of activity in cortical and subcortical structures, is restricted due to the vulnerability for movement artifacts and the range of motion in the scanner [52], functional near infrared spectroscopy (fNIRS) is affordable and easily implementable in a portable system, less susceptible to motion artifacts, thus facilitation a wider range of application with special cohorts (e.g., children, patients) and in everyday environments (e.g., during a therapeutic session of RAW or UAW) [53, 54]. Although with lower resolution compared to fMRI [55], fNIRS also relies on the principle of neurovascular coupling and allows the indirect evaluation of cortical activation [56, 57] based on hemodynamic changes which are analogous to the blood-oxygenation-level-dependent responses measured by fMRI [56]. Despite limited depth sensitivity, which restricts the measurement of brain activity to cortical layers, it is a promising tool to investigate the contribution of cortical areas to the neuromotor control of gross motor skills, such as walking [53]. Regarding the cortical correlates of walking, numerous studies identified either increaesed oxygenated hemoglobin (Hboxy) concentration changes in the sensorimotor cortex (SMC) by using fNIRS [53, 57,58,59] or suppressed alpha and beta power in sensorimotor areas by using electroencephalography (EEG) [60,61,62] demonstrating that motor cortex and corticospinal tract contribute directly to the muscle activity of locomotion [63]. However, brain activity during RAW [36, 61, 64,65,66,67,68], especially in patients [69, 70] or by using fNIRS [68, 69], is rarely studied [71].

Analyzing the effects of RA on brain activity in healthy volunteers, Knaepen et al. [36] reported significantly suppressed alpha and beta rhythms in the right sensory cortex during UAW compared to RAW with 100% GF and 0% BWS. Thus, significantly larger involvement of the SMC during UAW compared to RAW were concluded [36]. In contrast, increases of Hboxy were observed in motor areas during RAW compared UAW, leading to the conclusion that RA facilitated increased cortical activation within locomotor control systems [68]. Furthermore, Simis et al. [69] demonstrated the feasibility of fNIRS to evaluate the real-time activation of the primary motor cortex (M1) in both hemispheres during RAW in patients suffering from spinal cord injury. Two out of three patients exhibited enhanced M1 activation during RAW compared with standing which indicate the enhanced involvement of motor cortical areas in walking with RA [69].

To summarize, previous studies mostly focused the effects of RA on either gait characteristics or brain activity. Combined measurements investigating the effects of RA on both biomechanical and hemodynamic patterns might help for a better understanding of the neurophysiological mechanisms underlying gait and gait disorders as well as the effectiveness of robotic rehabilitation on motor recovery [37, 71]. Up to now, no consensus exists regarding how robotic devices should be designed, controlled or adjusted (i.e., device settings, such as the level of support) for synergistic interactions with the human body to achieve optimal neurorehabilitation [37, 72]. Therefore, further research concerning behavioral and neurophysiological mechanisms underlying RAW as well as the modulatory effect of RAGT on neuroplasticy and gait recovery are required giving the fact that such knowledge is of clinical relevance for the development of gait rehabilitation strategies.

Consequently, the central purpose of this study was to investigate both gait characteristics and hemodynamic activity during RAW to identify RAW-related changes in brain activity and their relationship to gait responses. Assuming that sensorimotor areas play a pivotal role within the cortical network of automatic gait [9, 53] and that RA affects gait and brain patterns in young, healthy volunteers [39, 42, 45, 68], we hypothesized that RA result in both altered gait and brain activity patterns. Based on previous studies, more stereotypical gait characteristics with less inter- and intraindividual variability are expected during RAW due to 100% GF and the fixed pelvis compared to UAW [45, 48], wheares brain activity in SMC can be either decreased [36] or increased [68].

Methods

This study was performed in accordance with the Declaration of Helsinki. Experimental procedures were performed in accordance with the recommendations of the Deutsche Gesellschaft für Psychologie and were approved by the ethical committee of the Medical Association Hessen in Frankfurt (Germany). The participants were informed about all relevant study-related contents and gave their written consent prior to the initiation of the experiment.

Participants

Twelve healthy subjects (9 female, 3 male; aged 25 ± 4 years), without any gait pathologies and free of extremity injuries, were recruited to participate in this study. All participants were right-handed, according to the Edinburg handedness-scale [73], without any neurological or psychological disorders and with normal or corrected-to-normal vision. All participants were requested to disclose pre-existing neurological and psychological conditions, medical conditions, drug intake, and alcohol or caffeine intake during the preceding week.

Experimental equipment

The Lokomat (Hocoma AG, Volketswil, Switzerland) is a robotic gait-orthosis, consisting of a motorized treadmill and a BWS system. Two robotic actuators can guide the knee and hip joints of participants to match pre-programmed gait patterns, which were derived from average joint trajectories of healthy walkers, using a GF ranging from 0 to 100% [74, 75] (Fig. 1a). Kinematic trajectories can be adjusted to each individual’s size and step preferences [45]. The BWS was adjusted to 30% body weight for each participant, and the control mode was set to provide 100% guidance [64].

Montage and Setup. a Participant during robot-assisted walking (RAW), with functional near-infrared spectroscopy (fNIRS) montage. b fNIRS montage; S = Sources; D = Detectors c Classification of regions of interest (ROI): supplementary motor area/premotor cortex  (SMA/PMC) and sensorimotor cortex (SMC) 

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Continue —-> Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people | Journal of NeuroEngineering and Rehabilitation | Full Text

[Abstract] Improving Walking Ability in People With Neurologic Conditions: A Theoretical Framework for Biomechanics-Driven Exercise Prescription.

Abstract

The purpose of this paper is to discuss how knowledge of the biomechanics of walking can be used to inform the prescription of resistance exercises for people with mobility limitations. Muscle weakness is a key physical impairment that limits walking in commonly occurring neurologic conditions such as cerebral palsy, traumatic brain injury, and stroke. Few randomized trials to date have shown conclusively that strength training improves walking in people living with these conditions. This appears to be because

(1) the most important muscle groups for forward propulsion when walking have not been targeted for strengthening, and

(2) strength training protocols have focused on slow and heavy resistance exercises, which do not improve the fast muscle contractions required for walking.

We propose a theoretical framework to improve exercise prescription by integrating the biomechanics of walking with the principles of strength training outlined by the American College of Sports Medicine to prescribe exercises that are specific to improving the task of walking. The high angular velocities that occur in the lower limb joints during walking indicate that resistance exercises targeting power generation would be most appropriate. Therefore, we propose the prescription of plyometric and ballistic resistance exercise, applied using the American College of Sports Medicine guidelines for task specificity, once people with neurologic conditions are ambulating, to improve walking outcomes. This new theoretical framework for resistance training ensures that exercise prescription matches how the muscles work during walking.

via Improving Walking Ability in People With Neurologic Conditions: A Theoretical Framework for Biomechanics-Driven Exercise Prescription. – PubMed – NCBI

[BLOG POST] Detailed Voice Guidance In Google Maps Makes Walking For Blind People Much Easier

People with vision impairment who are also Google Maps users are in for a nice surprise! Starting October 10, which was also World Sight Day, Google announced a new update to Google Maps that will provide more detailed voice guidance and verbal announcements while walking from point A to point B.

This feature will provide a lot more confidence to blind people while navigating busy streets and areas. While walking, Google Maps will proactively tell the user if they are on the correct route, the direction the person is walking in, distance from the next turn, etc. If a person misses their turn, Google Maps will announce that it is re-routing the person. Through this detailed voice guidance, people with vision impairment can not only navigate in a “screen free” way with ease,  they can also explore places they have not been to before.

Currently, this feature is rolled out in the US and Japan in English and Japanese respectively on iOS and Android. Roll out for other languages is on the way.

Watch the following video to learn more about voice guidance in maps.

Detailed voice guidance can be turned on by going to Settings, Navigation (under walking Options)

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Source: Google

via Detailed Voice Guidance In Google Maps Makes Walking For Blind People Much Easier – Assistive Technology Blog

[WEB PAGE] Aerobic Exercise Aids Post-Stroke Walking, Endurance Improvements

 

Stroke survivors who completed group-based aerobic exercise programs similar in design and duration to cardiac rehabilitation programs significantly improved their aerobic endurance and walking ability, according to a recent study.

The study was published in Journal of the American Heart Association, the Open Access Journal of the American Heart Association/American Stroke Association.

Stroke remains the leading cause of disability in the US, and physical therapy is often prescribed to improve physical impairments after stroke. Most current rehabilitation care following stroke has little to no focus on aerobic fitness, and when continued rehabilitation activity is suggested patients often fail to keep active without any support or guidance, according to an analysis of 19 published studies to assess the impact of aerobic exercise programs on endurance and walking ability after stroke.

“The physical therapy we currently provide to patients after a stroke focuses more on improving the ability to move and move well rather than on increasing how far and long you can move,” says Elizabeth Regan, DPT, study lead author, and PhD candidate in Exercise Science at the University of South Carolina, in a media release from the American Heart Association.

“It doesn’t matter how well you can walk if your endurance level keeps you at home.”

The study included nearly 500 adults (average ages between 54-71) who completed aerobic exercise programs similar in structure to cardiac rehabilitation. Participants attended two to three sessions per week for about three months. Of nearly two dozen different exercise groups, walking was the most common type of activity, followed by stationary cycling and then mixed mode aerobic exercise. Physical abilities were tested before and after the intervention.

Looking at results by activity type, researchers found:

• Mixed aerobic activity provides the best result (four treatment groups) followed by walking (12 treatment groups).
• Cycling or recumbent stepping (machine that allows stepping while in seated position) while still significant was the least effective (seven treatment groups).
• Overall, participants significantly improved their endurance level and walking speed.
• On average, participants walked almost half the size of a football field farther during a six-minute walking test. Participants with mild movement impairments benefited the most.

“These benefits were realized regardless of how long it had been since their stroke,” Regan comments, in the release. “Our analysis included stroke survivors across a wide range, from less than six months to greater than a year since their stroke, and the benefits were seen whether they started an aerobic exercise program one month or one year after having a stroke.”

“Cardiac rehab programs may be a viable option for patients after a stroke who have health risks and endurance losses similar to traditional cardiac rehab participants,” states Stacy Fritz, PhD, PT, the study’s co-author and associate professor of exercise science in the Physical Therapy Program at the University of South Carolina.

“Almost every hospital has a cardiac rehab program, so it’s an existing platform that could be used for stroke survivors. Funneling patients with stroke into these existing programs may be an easy, cost-effective solution with long-term benefits.”

While this study suggests group-based aerobic exercise programs improve health and endurance in stroke survivors, no control group analysis was performed for results comparison. Limited follow-up data were available to determine whether the health benefits persisted.

[Source(s): American Heart Association, Science Daily]

 

via Aerobic Exercise Aids Post-Stroke Walking, Endurance Improvements – Rehab Managment

[Abstract] Physiological Responses and Perceived Exertion During Robot-Assisted and Body Weight–Supported Gait After Stroke

Abstract

Introduction. Physiological responses are rarely considered during walking after stroke and if considered, only during a short period (3-6 minutes). The aims of this study were to examine physiological responses during 30-minute robot-assisted and body weight–supported treadmill and overground walking and compare intensities with exercise guidelines.

Methods. A total of 14 ambulatory stroke survivors (age: 61 ± 9 years; time after stroke: 2.8 ± 2.8 months) participated in 3 separate randomized walking trials. Patients walked overground, on a treadmill, and in the Lokomat (60% robotic guidance) for 30 minutes at matched speeds (2.0 ± 0.5 km/h) and matched levels of body weight support (BWS; 41% ± 16%). Breath-by-breath gas analysis, heart rate, and perceived exertion were assessed continuously.

Results. Net oxygen consumption, net carbon dioxide production, net heart rate, and net minute ventilation were about half as high during robot-assisted gait as during body weight–supported treadmill and overground walking (P < .05). Net minute ventilation, net breathing frequency, and net perceived exertion significantly increased between 6 and 30 minutes (respectively, 1.8 L/min, 2 breaths/min, and 3.8 units). During Lokomat walking, exercise intensity was significantly below exercise recommendations; during body weight–supported overground and treadmill walking, minimum thresholds were reached (except for percentage of heart rate reserve during treadmill walking).

Conclusion. In ambulatory stroke survivors, the oxygen and cardiorespiratory demand during robot-assisted gait at constant workload are considerably lower than during overground and treadmill walking at matched speeds and levels of body weight support. Future studies should examine how robotic devices can be Future studies should examine how robotic devices can be exploited to induce aerobic exercise.

 

via Physiological Responses and Perceived Exertion During Robot-Assisted and Body Weight–Supported Gait After Stroke – Nina Lefeber, Emma De Keersmaecker, Stieven Henderix, Marc Michielsen, Eric Kerckhofs, Eva Swinnen, 2018

[ARTICLE] Mechanics and energetics of post-stroke walking aided by a powered ankle exoskeleton with speed-adaptive myoelectric control – Full Text

Abstract

Background

Ankle exoskeletons offer a promising opportunity to offset mechanical deficits after stroke by applying the needed torque at the paretic ankle. Because joint torque is related to gait speed, it is important to consider the user’s gait speed when determining the magnitude of assistive joint torque. We developed and tested a novel exoskeleton controller for delivering propulsive assistance which modulates exoskeleton torque magnitude based on both soleus muscle activity and walking speed. The purpose of this research is to assess the impact of the resulting exoskeleton assistance on post-stroke walking performance across a range of walking speeds.

Methods

Six participants with stroke walked with and without assistance applied to a powered ankle exoskeleton on the paretic limb. Walking speed started at 60% of their comfortable overground speed and was increased each minute (n00, n01, n02, etc.). We measured lower limb joint and limb powers, metabolic cost of transport, paretic and non-paretic limb propulsion, and trailing limb angle.

Results

Exoskeleton assistance increased with walking speed, verifying the speed-adaptive nature of the controller. Both paretic ankle joint power and total limb power increased significantly with exoskeleton assistance at six walking speeds (n00, n01, n02, n03, n04, n05). Despite these joint- and limb-level benefits associated with exoskeleton assistance, no subject averaged metabolic benefits were evident when compared to the unassisted condition. Both paretic trailing limb angle and integrated anterior paretic ground reaction forces were reduced with assistance applied as compared to no assistance at four speeds (n00, n01, n02, n03).

Conclusions

Our results suggest that despite appropriate scaling of ankle assistance by the exoskeleton controller, suboptimal limb posture limited the conversion of exoskeleton assistance into forward propulsion. Future studies could include biofeedback or verbal cues to guide users into limb configurations that encourage the conversion of mechanical power at the ankle to forward propulsion.

Trial registration

N/A.

Background

Walking after a stroke is more metabolically expensive, leading to rapid exhaustion, limited mobility, and reduced physical activity [1]. Hemiparetic walking is slow and asymmetric compared to unimpaired gait. Preferred walking speeds following stroke range between < 0.2 m s^− 1 and ~ 0.8 m s^− 1 [2] compared to ~ 1.4 m s^− 1 in unimpaired adults, and large interlimb asymmetry has been documented in ankle joint power output [3, 4]. The ankle plantarflexors are responsible for up to 50% of the total positive work needed to maintain forward gait [5, 6]; therefore, weakness of the paretic plantarflexors is especially debilitating, and as a result, the paretic ankle is often a specific target of stroke rehabilitation [7, 8, 9, 10]. In recent years, ankle exoskeletons have emerged as a technology capable of improving ankle power output by applying torque at the ankle joint during walking in clinical populations [7, 8] and healthy controls [11, 12, 13, 14]. Myoelectric exoskeletons offer a user-controlled approach to stroke rehabilitation by measuring and adapting to changes in the user’s soleus electromyography (EMG) when generating torque profiles applied at the ankle [15]. For example, a proportional myoelectric ankle exoskeleton was shown to increase the paretic plantarflexion moment for persons post-stroke walking at 75% of their comfortable overground (OVG) speed [8]; despite these improvements, assistance did not reduce the metabolic cost of walking or improve percent paretic propulsion. The authors suggested exoskeleton performance could be limited because the walking speed was restricted to a pace at which exoskeleton assistance was not needed.

Exoskeleton design for improved function following a stroke would benefit from understanding the interaction among exoskeleton assistance, changes in walking speed, and measured walking performance. Increases in walking speed post-stroke are associated with improvements in forward propulsion and propulsion symmetry [16], trailing limb posture [17, 18], step length symmetries [17, 19], and greater walking economies [17, 19]. This suggests that assistive technologies need to account for variability in walking speeds to further improve post-stroke walking outcomes. However, research to date has evaluated exoskeleton performance at only one walking speed, typically set to either the participant’s comfortable OVG speed or a speed below this value [7, 8]. At constant speeds, ankle exoskeletons have been shown to improve total ankle power in both healthy controls [11] and persons post-stroke [8], suggesting the joint powers and joint power symmetries could be improved by exoskeleton technology. Additionally, an exosuit applying assistance to the ankle was able to improve paretic propulsion and metabolic cost in persons post-stroke walking at their comfortable OVG speed [7]. Assessing the impact of exoskeleton assistance on walking performance across a range of speeds is the next logical step toward developing exoskeleton intervention strategies targeted at improving walking performance and quality of life for millions of persons post-stroke.

In order to assess the impact of exoskeleton assistance across a range of walking speeds in persons post-stroke, we developed a novel, speed-adaptive exoskeleton controller that automatically modulates the magnitude of ankle torque with changes in walking speed and soleus EMG. We hypothesized that: 1) Our novel speed-adaptive controller will scale exoskeleton assistance with increases in walking speed as intended. 2) Exoskeleton assistance will lead to increases in total average net paretic ankle power and limb power at all walking speeds. 3) Exoskeleton assistance will lead to metabolic benefits associated with improved paretic average net ankle and limb powers.

Methods

Exoskeleton hardware

We implemented an exoskeleton emulator comprised of a powerful off-board actuation and control system, a flexible Bowden cable transmission, and a lightweight exoskeleton end effector [20]. The exoskeleton end effector includes shank and foot carbon fiber components custom fitted to participants and hinged at the ankle. The desired exoskeleton torque profile was applied by a benchtop motor (Baldor Electric Co, USA) to the carbon-fiber ankle exoskeleton through a Bowden-cable transmission system. An inline tensile load cell (DCE-2500 N, LCM Systems, Newport, UK) was used to confirm the force transmitted by the exoskeleton emulator during exoskeleton assistance.

Speed-adaptive proportional myoelectric exoskeleton controller

Our exoskeleton controller alters the timing and magnitude of assistance with the user’s soleus EMG signal and walking speed (Fig. 1). The exoskeleton torque is determined from Eq. 1, in which participant mass (m_participant) is constant across speeds, treadmill speed (V) is measured in real-time, the speed gain (G_speed) is constant for all subjects and across speeds, the adaptive gain (G_adp) is constant for a gait cycle and calculated anew for each gait cycle, and the force-gated and normalized EMG (EMG_GRFgated) is a continuously changing variable.

τexo (t)=mparticipant×V×Gspeed×Gadp×EMGGRFgatedτexo (t)=mparticipant×V×Gspeed×Gadp×EMGGRFgated

(1)

Fig. 1

Novel speed-adaptive myoelectric exoskeleton controller measures and adapts to users’ soleus EMG signal as well as their walking speed in order to generate the exoskeleton torque profile. Raw soleus EMG signal is filtered and rectified to create an EMG envelope, and the created EMG envelope is then gated by anterior GRFs to ensure assistance is only applied during forward propulsion. The adaptive EMG gain is calculated as a moving average of peak force-gated EMG from the last five paretic gait cycles. The pre-speed gain control signal is the product of the force-gated EMG and the adaptive EMG gain. The speed gain is determined using real-time walking speed and computed as 25% of the maximum biological plantarflexion torque at that given walking speed. Exoskeleton torque is the result of multiplying the speed gain with the pre-speed gain control signal

[…]

Continue —> Mechanics and energetics of post-stroke walking aided by a powered ankle exoskeleton with speed-adaptive myoelectric control | Journal of NeuroEngineering and Rehabilitation | Full Text

[WEB SITE] Regaining the Ability to Walk – Stroke: Emergency Care and Rehabilitation

Regaining the Ability to Walk

Because an acquired neurologic injury (such as a stroke) affects both sensory and motor function, walking can be severely affected. Sensory changes, weakness, and spasticity affect movement strategies, which alter a person’s ability to successfully respond to losses of balance. A stroke affects how much and how often a person walks and also affects walking adaptability—the ability to adapt to different conditions during ambulation—as well as endurance. Gait training generally starts as soon as possible following a stroke, using manual techniques, task-specific training, strengthening, and, when available, body weight-assisted treadmill training and robotic devices.

Gait Training

An example of over-ground gait training.

Movement Strategies Altered by Stroke

A movement strategy or synergy is a flexible, repeatable pattern of movement that can be quickly and automatically accessed by the central nervous system. Movement strategies allow us to store and reuse patterns of movement that have been successful in the past. Strategies are efficient, automatic movement patterns that evolve over time. Each time a loss of balance threatens, the nervous system draws on these pre-programmed movement strategies to ensure the maintenance of balance.Movement strategies used by the nervous system to respond to perturbations are diminished following a stroke.

Ankle Sway

The ankle strategy is used in response to small perturbations is also called ankle sway. Source: Lauren Robertson.

 

The ankle strategy—also called ankle sway—is used in response to small perturbations or losses of balance. When a small loss of balance occurs—as when standing on a moving bus—the foot acts as a lever to maintain balance by making continuous automatic adjustments to the movement of the bus. When a small balance adjustment is needed, muscles close to the floor (anterior tibialis and gastrocnemius) activate first and flow upward in a distal to proximal pattern.

When a perturbation is too large to be successfully handled by the ankle strategy, the hip strategy is needed. When the hip strategyis used, movement is centered about the hip and ankle muscles (anterior tibialis and gastrocnemius) are almost silent. The muscles in the trunk activate first as activation flows downward to the legs in a proximal to distal pattern. So, if the bus stops suddenly and the body bends forward, the low back and hamstrings will contract in that order to return the body to upright.

If the perturbation is strong and your center of gravity moves well past your base of support, it is necessary to take a forward or backward step to regain balance. This is referred to as a stepping strategy. Studies have shown age-related changes in stepping in older adults. Compared to younger people, older adults initiate the stepping strategy in response to smaller losses of balance and tend to take several small steps rather than one larger step (Maki & McIlroy, 2006).

Arm movements have a considerable role in balance control and are part of the strategies discussed above. The upper limbs start to react at the very beginning of a disruption of balance and continue to be active as the body attempts to regain control. By automatically reaching and grasping for support, the arms perform a protective function. In the case of a small perturbation, upper limb movements can prevent a fall by shifting the center of gravity away from the imbalance.

When upper extremity paresis or spasticity is present, post stroke subjects exhibit poor protective reactions during a perturbation of balance. They demonstrate a deficit in anticipatory and reactive postural adjustments. These impairments of the affected upper limbs limit a person’s ability to recover from perturbations during functional tasks such as walking (Arya et al., 2014).

Even in the absence of a neurologic disorder, age-related changes affect upper extremity reaction time when balance is disrupted. Older adults reach for support surfaces more readily than younger adults but the reach-reaction time is slower. Increased tendency to reach for support and a slowing of these reactions have been found to be predictive of falling in daily activities (Maki & McIlroy, 2006).

Comparing Reflexes, Automatic Reactions, and Volitional Movement Reflexes Think for a moment that you are cooking dinner and accidentally touch a scalding hot fry pan. You feel the heat and withdraw instantaneously. You aren’t thinking “I better take my hand off the hot pan before it burns me”—your reflexes take care of that for you. The withdrawal is almost instantaneous because your nervous system senses danger and reflexively withdraws. Automatic Reactions This type of reaction is used in movement strategies; they are slower than reflexes but faster than volitional movement. They are fast enough to help us respond to losses of balance without having to think. Volitional Movement This type of movement requires thought and is relatively slow compared to reflexive and automatic movement. Using our brains to think about movement isn’t very practical when we need something done really fast—by the time your brain warns you to bend your waist, step forward, or grab onto something when the bus stops abruptly, it’s already too late to regain balance. Activity Stand up next to your chair. Make sure you are standing on a flat, firm surface. Now close your eyes. Notice that your body sways a little—you are using the ankle strategy to stay balanced. Notice also that after a short amount of time you sway less—that means your nervous system is adjusting. Often, following a stroke, a person looses the ability to use the ankle strategy. This can have a profound impact on balance. Stand up again. Ask someone to give you a little nudge from behind. Try not to take a step. If it was a truly small nudge you will likely bend at the waist to try to regain your balance. This is an example of the hip strategy. Now ask your partner to give you a slightly bigger nudge from behind. If the nudge is big enough you’ll have to take a step. This is the stepping strategy. We use these strategies automatically, all day long, without effort. Someone who has had a stroke can’t access these strategies as quickly as you can. If faced with a nudge from a passerby, or a bus starting/stopping, or a walk on uneven ground, the inability to adjust quickly may result in a fall.

Importance of Walking Early and Often

Regaining the ability to walk following a stroke is of paramount importance to patients and caregivers alike; improving balance and walking leads to greater independence and improves general well-being.

In the first week following a stroke, only one-third of patients are able to walk without assistance. In the following weeks, walking ability generally improves. At 3 weeks, or at hospital discharge, more than half of stroke survivors can walk unaided. By 6 months, more than 80% are able to walk independently without physical assistance from another person (Balasubramanian et al., 2014).

Following a stroke, walking can take a lot of energy; impaired muscle function, weakness, and poor cardiovascular conditioning can double the amount of energy expended. The high energy cost of walking can affect a person’s ability to participate in daily activities and lead to a vicious cycle where physical activity is avoided. For example, in one study, stroke patients walked 50% of the daily amount of matched sedentary adults and used 75% of their VO2 peak for walking at a submaximal rate (Danielsson et al., 2011).

Walking may improve more rapidly when patients are involved in setting specific goals. The results of several motor learning studies in which the person’s attention was focused on the outcome of an action rather than the action itself produced more effective performance than focusing on the quality of the movement (Carr & Shepherd, 2011).

In the hospital, an early goal for walking might be to walk to the next appointment, or to walk at least part of the way, rather than being transported in a wheelchair. Each day the patient should be encouraged to select a distance to walk independently and safely. Initially, this may be only a few steps. The goal is to walk the chosen distance a certain number of times a day, increasing distance as soon as possible, and keeping a record of progress, which gives the patient a specific focus (Carr & Shepherd, 2011).

Walking Adaptability, Stepping, and Postural Control

Walking is greatly dependent upon our ability to adapt to varying environmental conditions and tasks. Walking from the bedroom to the bathroom with a walker requires a different level of attention and adaptability than walking across a busy street carrying a bag of groceries. Even walking and talking can be a challenge for post stroke patients.

Over time, up to 85% of individuals with a stroke regain independent walking ability, but at discharge from inpatient rehab only about 7% can manage steps and inclines or walk the speeds and distances required to walk competently in the community. Limited ability to adjust to changes in the task and environment means a person either avoids walking in complex situations (a safety strategy) or has a heightened risk of falls when required to walk under these challenging conditions (Balasubramanian et al., 2014).

Despite its importance, assessment of walking adaptability has received relatively little attention. Frequently used assessments of walking ability after stroke involve walking short distances (such as the Timed Up and Go test) and examination of isolated limb movements (such as the Fugl-Meyer Assessment). Although valuable, these assessments do not take into account the skills needed to re-engage in safe and independent ambulation in the home and community. Comprehensive assessments and specific interventions are needed to improve walking adaptability (Balasubramanian et al., 2014).

In addition to the ability to adapt to different conditions and tasks, walking adaptability has two other requirements: (1) stepping, and (2) postural control (Shumway-Cook & Woollocott, 2012). Stepping involves the ability to generate and maintain a rhythmic, alternating gait pattern as well as the ability to start and stop. Postural control involves both the musculoskeletal and nervous systems.

To walk effectively, the central nervous system must:

1. Generate the basic stepping pattern of rhythmic reciprocal limb movements while supporting the body against gravity and propelling it forward.
2. Maintain control of posture (equilibrium) to keep the center of mass over a constantly moving base of support and maintain the body upright in space.
3. Adapt to environmental circumstance or changes in the behavioral goal (Balasubramanian et al., 2014).

Walking Adaptability

Source: Balasubramanian et al., 2014.

 

These components are especially necessary for complex tasks. For example, walking adaptability is crucial on uneven ground or cluttered terrains and when the task requires walking and turning or negotiating a curved path. There are endless combinations of task goals and environmental circumstances that must be considered to comprehensively capture walking adaptability (Balasubramanian et al., 2014).

Walking adaptability is very important for community ambulation. Patla and Shumway-Cook have described “dimensions” that affect a person’s ability to adapt while walking. These are external demands that must be met for successful community mobility:

• Distance (distance walked)
• Temporal factors (time needed to cross a busy street or crosswalk, ability to maintain the same speed as those around them)
• Ambient conditions (rain, heat, snow, etc.)
• Physical load (packages carried, number of doors that need to be opened)
• Terrain (stairs, curbs, slopes, uneven ground, grass, elevators, obstacles)
• Attentional demands (distractions in the environment, noise, cars, crowds, talking)
• Postural transitions (stopping, reaching, backing up, turning head, change direction)
• Traffic density (number of people within arm’s reach, unexpected collisions and near collisions with other people) (Shumway-Cook et al., 2002)

Improving Endurance for Walking

It is evident that many patients are discharged from inpatient rehabilitation severely deconditioned, meaning that their energy levels are too low for active participation in daily life. Physicians, therapists, and nursing staff responsible for rehabilitation practice should address this issue not only during inpatient rehabilitation but also after discharge by promoting and supporting community-based exercise opportunities. During inpatient rehabilitation, group sessions should be frequent and need to include specific aerobic training. Physical therapy must take advantage of the training aids available, including exercise equipment such as treadmills, and of new developments in computerized feedback systems, robotics, and electromechanical trainers.

Janet Carr and Roberta Sheperd
University of Sydney, Australia

Although many people affected by stroke have regained some ability to walk by the time they are discharged from rehab, many have low endurance, which limits their ability to perform household tasks or even to walk short distances. After a stroke, walking requires a much higher level of energy expenditure, and upon discharge many stroke patients are not necessarily functionalwalkers (Carr & Sheperd, 2011).

Functional walking is assessed using tests of speed, distance, and time. Minimal criteria for successful community walking include an independent walking velocity of 0.8 m/s or greater (about 2.6 feet/second), the ability to negotiate uneven terrain and curbs, and the physical endurance to walk 500 meters or more. In a review of 109 people discharged from physical therapy, only 7% achieved the minimum level. Cardiorespiratory fitness training can address both the efficiency with which people affected by stroke can walk and the distance they are able to achieve (Carr & Sheperd, 2011).

The loss of independent ambulation outdoors has been identified as one of the most debilitating consequences of stroke. Among stroke survivors 1 year after stroke, the most striking area of difficulty was low endurance measured by the distance walked in a 6-minute walk test. Those subjects able to complete this test were able to walk on average only 250 meters (820 feet) compared to the age-predicted distance of >600 meters (almost 2,000 feet), equivalent to 40% of their predicted ability and not far enough for a reasonable and active lifestyle. The detrimental effect of low exercise capacity and muscle endurance on functional mobility and on resistance to fatigue is likely to increase after discharge if follow-up physical activity and exercise programs are not available (Carr & Sheperd, 2011).

In 2002 the American Thoracic Society (ATS) published guidelines for the 6-minute walk test with the objective of standardizing the protocol to encourage its further application and to allow direct comparisons among different studies and populations. The American Thoracic Society guidelines include test indications and contraindications, safety measures, and a step-by-step protocol as well as assistance with clinical interpretation (Dunn et al., 2015).

Key components of the protocol include the test location, walkway length, measurements, and instructions. According to the American Thoracic Society protocol, the test should be performed on a flat, enclosed (indoor) walkway 30 m (just under 100 feet) in length. This protocol requires 180° turns at either end of the walkway and additional space for turning. The guidelines advise that shorter walkway lengths require more directional changes and can reduce the distances achieved. The influence of directional changes may be amplified in the stroke population, who characteristically have impaired balance, asymmetric gait patterns, and altered responses for turn preparation. Conversely, reducing the number of directional changes may increase the distance achieved (Dunn et al., 2015).

Body Weight-Supported Treadmill Training

Body weight-supported treadmill training (BWSTT) is an increasingly being used to encourage early walking following a stroke. It is a rehabilitation technique in which patients walk on a treadmill with their body weight partly supported. Body weight-supported treadmill training augments walking by enabling repetitive practice of gait (Takeuchi & Izumi, 2013).

In patients who have experienced a stroke, partial unloading of the lower extremities by the body weight-support system results in straighter trunk and knee alignment during the loading phase of walking. It can also improve swing1 asymmetry, stride length, and walking speed, and allows a patient to practice nearly normal gait patterns and avoid developing compensatory walking habits, such as hip hiking and circumduction2 (Takeuchi & Izumi, 2013).

¹Swing phase of gait: during walking, the swing phase begins as the toe lifts of the ground, continues as the knee bends and the leg moves forward, and ends when the heel come in contact with the ground.

²Circumduction: a gait abnormality in which the leg is swung around and forward in a semi-circle. The hip is often hiked up to create enough room for the leg to swing forward.

Locomotor Training

Locomotor Training Program (LTP). Source: Duncan et al., 2007.

Another example of a body-weight supported treadmill. Source: NIH, 2011.

Treadmill walking allows for independent and semi-supervised practice, for those with more ability, as well as improving aerobic capacity and increasing walking speed and endurance. The very early practice of assisted over-ground and harness-supported treadmill walking is probably critical to good post-discharge functional capacity in terms of both performance and energy levels (Carr & Shepherd, 2011).

The Locomotor Experience Applied Post Stroke (LEAPS) trial—the largest stroke rehabilitation study ever conducted in the United States—set out to compare the effectiveness of the body weight-supported treadmill training with walking practice. Participants started at two different stages—two months post stroke (early locomotor training) and six months post stroke (late locomotor training). The locomotor training was also compared to a home exercise program managed by a physical therapist, which was aimed at enhancing flexibility, range of motion, strength, and balance as a way to improve walking. The primary measure was improvement in walking at 1 year after the stroke (NINDS, 2011).

In the LEAPS trial, stroke patients who had physical therapy at home improved their ability to walk just as well as those who were treated in a training program that requires the use of a body weight-supported treadmill device followed by walking practice. The study, funded by the NIH, also found that patients continued to improve up to 1 year after stroke—defying conventional wisdom that recovery occurs early and tops out at 6 months. In fact, even patients who started rehabilitation as late as 6 months after stroke were able to improve their walking (NINDS, 2011).

“We were pleased to see that stroke patients who had a home physical therapy exercise program improved just as well as those who did the locomotor training,” said Pamela W. Duncan, principal investigator of LEAPS and professor at Duke University School of Medicine. “The home physical therapy program is more convenient and pragmatic. Usual care should incorporate more intensive exercise programs that are easily accessible to patients to improve walking, function, and quality of life.”

Robotic Gait Training Devices

Several lower-limb rehabilitation robots have been developed to restore mobility of the affected limbs. These systems can be grouped according to the rehabilitation principle they follow:

• Treadmill gait trainers
• Foot-plate-based gait trainers
• Over-ground gait trainers
• Stationary gait trainers
• Ankle rehabilitation systems
  • Stationary systems
  • Active foot orthoses (Díaz et al., 2011)

The Lokomat System

Source: Diaz et al., 2011.

 

Many robotic systems have been developed aiming to automate and improve body weight-assisted treadmill trainers as a means for reducing therapist labor. Usually these systems are based on exoskeleton type robots in combination with a treadmill. One such system—the Lokomat—consists of a robotic gait orthosis and an advanced body weight-support system, combined with a treadmill. It uses computer-controlled motors (drives) that are integrated in the gait orthosis at each hip and knee joint. The drives are precisely synchronized with the speed of the treadmill to ensure a precise match between the speed of the gait orthosis and the treadmill (Díaz et al., 2011).

The LocoHelp System

The LokoHelp gait trainer “Pedago.” Source: Diaz et al., 2011.

 

The LokoHelp is another device developed for improving gait after brain injury. The LokoHelp is placed in the middle of the treadmill surface, parallel to the walking direction and fixed to the front of the treadmill with a simple clamp. It also provides a body weight-support system. Clinical trials have shown that the system improves the gait ability of the patient in the same way as the manual locomotor training; however, the LokoHelp required less therapeutic assistance and thus therapist discomfort is reduced. This fact is a general conclusion for almost all robotic systems to date (Díaz et al., 2011).

The KineAssist

Source: Diaz et al., 2011.

 

Over-ground gait trainers consist of robots that assist the patient in walking over ground. These trainers allow patients to move under their own control rather than moving them through predetermined movement patterns. The KineAssist is one robotic device used for gait and balance training. It consists of a custom-designed torso and pelvis harness attached to a mobile robotic base. The robot is controlled according to the forces detected from the subject by the load cells located in the pelvic harness (Díaz et al., 2011).

The ReWalk Robotic Suit

Source: Diaz et al., 2011.

ReWalk is a wearable, motorized quasi-robotic suit that can be used for therapeutic activities. ReWalk uses a light, wearable brace support suit that integrates motors at the joints, rechargeable batteries, an array of sensors, and a computer-based control system. Upper-body movements of the user are detected and used to initiate and maintain walking processes (Díaz et al., 2011).

The capacity of robots to deliver high-intensity and repeatable training make them potentially valuable tools to provide high-quality treatment at a lower cost and effort. These systems can also be used at home to allow patients to perform therapies independently, not replacing the therapist but supporting the therapy program. However, despite the attractiveness of robotic devices, clinical studies still show little evidence for the superior effectiveness of robotic therapy compared to current therapy practices, although robotics have been shown to reduce therapist effort, time, and costs (Díaz et al., 2011).

via Regaining the Ability to Walk | Stroke: Emergency Care and Rehabilitation

[Abstract] A randomized controlled trial of a walking training with simultaneous cognitive demand (dual‐task) in chronic stroke

Abstract

Background and purpose

The aim was to evaluate the tolerability of, adherence to and efficacy of a community walking training programme with simultaneous cognitive demand (dual‐task) compared to a control walking training programme without cognitive distraction.

Methods

Adult stroke survivors at least 6 months after stroke with a visibly obvious gait abnormality or reduced 2‐min walk distance were included in a two‐arm parallel randomized controlled trial of complex intervention with blinded assessments. Participants received a 10 week, bi‐weekly, 30 min treadmill programme at an aerobic training intensity (55%–85% heart rate maximum), either with or without simultaneous cognitive demands. Outcome was measured at 0, 11 and 22 weeks. The primary assessment involved 2‐min walk tests with and without cognitive distraction to investigate the dual‐task effect on walking and cognition; secondary results were the Short Form Health Survey 36, EuroQol‐5D‐5L, the Physical Activity Scale for the Elderly (PASE) and step activity.

Results

Fifty stroke patients were included; 43 received allocated training and 45 completed all assessments. The experimental group (n = 26) increased their mean (SD) 2‐min walking distance from 90.7 (8.2) to 103.5 (8.2) m, compared with 86.7 (8.5) to 92.8 (8.6) m in the control group, and their PASE score from 74.3 (9.1) to 89.9 (9.4), compared with 94.7 (9.4) to 77.3 (9.9) in the control group. Statistically, only the change in the PASE differed between the groups (P = 0.029), with the dual‐task group improving more. There were no differences in other measures.

Conclusions

Walking with specific additional cognitive distraction (dual‐task training) might increase activity more over 12 weeks, but the data are not conclusive.

 

via A randomized controlled trial of a walking training with simultaneous cognitive demand (dual‐task) in chronic stroke – Meester – – European Journal of Neurology – Wiley Online Library

[Abstract] Gait rehabilitation using functional electrical stimulation induces changes in ankle muscle coordination in stroke survivors: a preliminary study

Background: Previous studies have demonstrated that post-stroke gait rehabilitation combining functional electrical stimulation applied to the ankle muscles during fast treadmill walking (FastFES) improves gait biomechanics and clinical walking function. However, there is considerable inter-individual variability in response to FastFES. Although FastFES aims to sculpt ankle muscle coordination, whether changes in ankle muscle activity underlie observed gait improvements is unknown. The aim of this study was to investigate three cases illustrating how FastFES modulates ankle muscle recruitment during walking.

Methods: We conducted a preliminary case series study on three individuals (53-70y; 2M; 35-60 months post-stroke; 19-22 lower extremity Fugl-Meyer) who participated in 18 sessions of FastFES (3 sessions/week; ClinicalTrials.gov: NCT01668602). Clinical walking function (speed, six-minute walk test, and Timed-Up-and-Go test), gait biomechanics (paretic propulsion and ankle angle at initial-contact), and plantarflexor (soleus) / dorsiflexor (tibialis anterior) muscle recruitment were assessed pre- and post-FastFES while walking without stimulation.
Results: Two participants (R1, R2) were categorized as responders based on improvements in clinical walking function. Consistent with heterogeneity of clinical and biomechanical changes commonly observed following gait rehabilitation, how muscle activity was altered with FastFES differed between responders.R1 exhibited improved plantarflexor recruitment during stance accompanied by increased paretic propulsion. R2 exhibited improved dorsiflexor recruitment during swing accompanied by improved paretic ankle angle at initial-contact. In contrast, the third participant (NR1), classified as a non-responder, demonstrated increased ankle muscle activity during inappropriate phases of the gait cycle. Across all participants, there was a positive relationship between increased walking speeds after FastFES and reduced SOL/TA muscle coactivation.
Conclusion: Our preliminary case series study is the first to demonstrate that improvements in ankle plantarflexor and dorsiflexor muscle recruitment (muscles targeted by FastFES) accompanied improvements in gait biomechanics and walking function following FastFES in individuals post-stroke. Our results also suggest that inducing more appropriate (i.e., reduced) ankle plantar/dorsi-flexor muscle coactivation may be an important neuromuscular mechanism underlying improvements in gait function after FastFES training, suggesting that pre-treatment ankle muscle status could be used for inclusion into FastFES. The findings of this case-series study, albeit preliminary, provide the rationale and foundations for larger-sample studies using similar methodology.

 

via Frontiers | Gait rehabilitation using functional electrical stimulation induces changes in ankle muscle coordination in stroke survivors: a preliminary study | Neurology