Posts Tagged walking

[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 [34]. The ankle plantarflexors are responsible for up to 50% of the total positive work needed to maintain forward gait [56]; therefore, weakness of the paretic plantarflexors is especially debilitating, and as a result, the paretic ankle is often a specific target of stroke rehabilitation [78910]. 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 [78] and healthy controls [11121314]. 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 [1718], step length symmetries [1719], and greater walking economies [1719]. 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 [78]. 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 (mparticipant) is constant across speeds, treadmill speed (V) is measured in real-time, the speed gain (Gspeed) is constant for all subjects and across speeds, the adaptive gain (Gadp) is constant for a gait cycle and calculated anew for each gait cycle, and the force-gated and normalized EMG (EMGGRFgated) is a continuously changing variable.

τexo (t)=mparticipant×V×Gspeed×Gadp×EMGGRFgatedτexo (t)=mparticipant×V×Gspeed×Gadp×EMGGRFgated
(1)
Fig. 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

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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

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[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

image: photo of 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

image: illustration of 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

image: graph of walking adaptability components

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

image: photo of patient on body-weight supported treadmill

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

image: photo of patient on body-weight supported treadmill

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

image: photo of patient using Lokomat

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

image: photo of patient using LocoHelp

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

image: photo of 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

image: photo of patient using 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

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[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

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[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

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[Abstract] Mobility Function and Recovery After Stroke: Preliminary Insights From Sympathetic Nervous System Activity

Background and Purpose: Poststroke hemiparesis increases the perceived challenge of walking. Perceived challenge is commonly measured by self-report, which is susceptible to measurement bias. A promising approach to objectively assess perceived challenge is measuring sympathetic nervous system (SNS) activity with skin conductance to detect the physiological stress response. We investigated the feasibility of using skin conductance measurements to detect task-related differences in the challenge posed by complex walking tasks in adults poststroke.

Methods: Adults poststroke (n = 31) and healthy young adults (n = 8) performed walkingtasks including typical walkingwalking in dim lighting, walking over obstacles, and dual-task walking. Measures of skin conductance and spatiotemporal gait parameters were recorded. Continuous decomposition analysis was conducted to assess changes in skin conductance level (ΔSCL) and skin conductance response (ΔSCR). A subset of participants poststroke also underwent a 12-week rehabilitation intervention.

Results: SNS activity measured by skin conductance (both ΔSCL and ΔSCR) was significantly greater for the obstacles task and dual-task walking than for typical walkingin the stroke group. Participants also exhibited “cautious” gait behaviors of slower speed, shorter step length, and wider step width during the challenging tasks. Following the rehabilitation intervention, SNS activity decreased significantly for the obstacles task and dual-task walking.

Discussion and Conclusions: SNS activity measured by skin conductance is a feasible approach for quantifying task-related differences in the perceived challenge of walkingtasks in people poststroke. Furthermore, reduced SNS activity during walking following a rehabilitation intervention suggests a beneficial reduction in the physiological stress response evoked by complex walking tasks.

Video Abstract available for more insights from the authors (See Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A234).

via Mobility Function and Recovery After Stroke: Preliminary In… : Journal of Neurologic Physical Therapy

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[Abstract] Validity and reproducibility of the Functional Gait Assessment in persons after stroke

Abstract

To evaluate construct validity and reproducibility of the Functional Gait Assessment (FGA) for measuring walking balance capacity in persons after stroke.

Cross-sectional study.

Inpatient and outpatient rehabilitation center.

Fifty-two persons post-stroke (median (25% and 75% percentiles)) time post-stroke 6 (5–10) weeks) with independent walking ability (mean gait speed 1.1 ± .4 m/s).

Subjects completed a standardized FGA twice within one to eight days by the same investigator. Validity was evaluated by testing hypotheses on the association with two timed walking tests, Berg Balance Scale, and the mobility domain of the Stroke Impact Scale using correlation coefficients (r), and with Functional Ambulation Categories using the Kruskal–Wallis test. Reproducibility of FGA scores was assessed with intraclass correlation coefficient and standard error of measurement.

Subjects scored a median of 22 out of 30 points at the first FGA. Moderate to high significant correlations (r .61–.83) and significant differences in FGA median scores between the Functional Ambulation Categories were found. Eight hypotheses (80%) could be confirmed. Inter-rater, intra-rater, and test–retest reliability of the total scores were excellent. The standard error of measurement and minimal detectable change were 2 and 6 points, respectively. No relevant ceiling effect was observed.

The FGA demonstrated good measurement properties in persons after stroke and yielded no ceiling effect in contrast to other capacity measures. In clinical practice, a measurement error of 6 points should be taken into account in interpreting changes in walking balance.

via Validity and reproducibility of the Functional Gait Assessment in persons after stroke – Maijke Van Bloemendaal, Walter Bout, Sicco A Bus, Frans Nollet, Alexander CH Geurts, Anita Beelen, 2018

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[Abstract + References] Experimental Human Walking and Virtual Simulation of Rehabilitation on Plane and Inclined Treadmill – Conference paper

Abstract

The paper presents the results of the authors concerning the experimental human walking and numerical simulation of human rehabilitation on a treadmill. Using Biometrics data acquisition system based on electrogoniometers, experimental measurements for ankle, knee and hip joints of right and left legs during walking on plane and inclined treadmill are performed. The human legs motion assistance for rehabilitation is proposed with an attached exoskeleton. The numerical simulation of a virtual mannequin walking with the attached exoskeleton on a plane and inclined treadmill is performed, using ADAMS virtual environment. A comparison between human experimental measurements and numerical simulations of a virtual mannequin with exoskeleton is presented.

 

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via Experimental Human Walking and Virtual Simulation of Rehabilitation on Plane and Inclined Treadmill | SpringerLink

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[Abstract] Effects of mirror therapy on walking ability, balance and lower limb motor recovery after stroke: a systematic review and meta-analysis of randomized controlled trials

To investigate the effects of mirror therapy on walking ability, balance and lower limb motor recovery in patients with stroke.

MEDLINE, EMBASE, Web of Science, CENTRAL, PEDro Database, CNKI, VIP, Wan Fang, ClinicalTrials.gov, Current controlled trials and Open Grey were searched for randomized controlled trials that investigated the effects of mirror therapy on lower limb function through January 2018. The primary outcomes included were walking speed, mobility and balance function. Secondary outcomes included lower limb motor recovery, spasticity and range of motion. Quality assessments were performed with the PEDro scale.

A total of 13 studies (n = 572) met the inclusion criteria. A meta-analysis demonstrated a significant effect of mirror therapy on walking speed (mean difference (MD) 0.1 m/s, 95% confidence interval (CI): 0.08 to 0.12, P < 0.00001), balance function (standard mean difference (SMD) 0.66, 95% CI: 0.43 to 0.88, P < 0.00001), lower limb motor recovery (SMD 0.83, 95% CI: 0.62 to 1.05, P < 0.00001) and passive range of motion of ankle dorsiflexion (MD 2.07°, 95% CI: 082 to 3.32, P = 0.001), without improving mobility (SMD 0.43, 95% CI: −0.12 to 0.98, P = 0.12) or spasticity of ankle muscles (MD −0.14, 95% CI: −0.43 to 0.15, P = 0.35).

The systematic review demonstrates that the use of mirror therapy in addition to some form of rehabilitation appears promising for some areas of lower limb function, but there is not enough evidence yet to suggest when and how to approach this therapy.

 

via Effects of mirror therapy on walking ability, balance and lower limb motor recovery after stroke: a systematic review and meta-analysis of randomized controlled trials – Yi Li, Qingchuan Wei, Wei Gou, Chengqi He, 2018

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[Abstract] Effects of an Exercise Protocol for Improving Handgrip Strength and Walking Speed on Cognitive Function in Patients with Chronic Stroke

BACKGROUND: Handgrip strength and walking speed predict and influence cognitive function. We aimed to investigate an exercise protocol for improving handgrip strength and walking speed, applied to patients with chronic stroke who had cognitive function disorder.
MATERIAL AND METHODS: Twenty-nine patients with cognitive function disorder participated in this study, and were randomly divided into one of two groups: exercise group (n=14) and control group (n=15). Both groups underwent conventional physical therapy for 60 minutes per day. Additionally, the exercise group followed an exercise protocol for handgrip using the hand exerciser, power web exerciser, Digi-Flex (15 minutes); and treadmill-based weight loading training on their less-affected leg (15 minutes) using a sandbag for 30 minutes, three times per day, for six weeks. Outcomes, including cognitive function and gait ability, were measured before and after the training.
RESULTS: The Korean version of Montreal Cognitive Assessment (K-MoCA), Stroop test (both simple and interference), Trail Making-B, Timed Up and Go, and 10-Meter Walk tests (p<0.05) yielded improved results for the exercise group compared with the control group. Importantly, the K-MoCA, Timed Up and Go, and 10-Meter Walk test results were significantly different between the two groups (p<0.05).
CONCLUSIONS: The exercise protocol for improving handgrip strength and walking speed had positive effects on cognitive function in patients with chronic stroke.

Link to Full Text Download —> Get your full text copy in PDF | Medical Science Monitor

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[WEB SITE] Monthly cycles of brain activity linked to seizures in patients with epilepsy

January 8, 2018
UC San Francisco neurologists have discovered monthly cycles of brain activity linked to seizures in patients with epilepsy. The finding, published online January 8 in Nature Communications, suggests it may soon be possible for clinicians to identify when patients are at highest risk for seizures, allowing patients to plan around these brief but potentially dangerous events.

“One of the most disabling aspects of having epilepsy is the seeming randomness of seizures,” said study senior author Vikram Rao, MD, PhD, an assistant professor of neurology at UCSF and member of the UCSF Weill Institute for Neurosciences. “If your neurologist can’t tell you if your next seizure is a minute from now or a year from now, you live your life in a state of constant uncertainty, like walking on eggshells. The exciting thing here is that we may soon be able to empower patients by letting them know when they are at high risk and when they can worry less.”

Epilepsy is a chronic disease characterized by recurrent seizures — brief storms of electrical activity in the brain that can cause convulsions, hallucinations, or loss of consciousness. Epilepsy researchers around the world have been working for decades to identify patterns of electrical activity in the brain that signal an oncoming seizure, but with limited success. In part, Rao says, this is because technology has limited the field to recording brain activity for days to weeks at most, and in artificial inpatient settings.

At UCSF Rao has pioneered the use of an implanted brain stimulation device that can quickly halt seizures by precisely stimulating a patient’s brain as a seizure begins. This device, called the NeuroPace RNS® System, has also made it possible for Rao’s team to record seizure-related brain activity for many months or even years in patients as they go about their normal lives. Using this data, the researchers have begun to show that seizures are less random than they appear. They have identified patterns of electrical discharges in the brain that they term “brain irritability” that are associated with higher likelihood of having a seizure.

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The new study, based on recordings from the brains of 37 patients fitted with NeuroPace implants, confirmed previous clinical and research observations of daily cycles in patients’ seizure risk, explaining why many patients tend to experience seizures at the same time of day. But the study also revealed that brain irritability rises and falls in much longer cycles lasting weeks or even months, and that seizures are more likely to occur during the rising phase of these longer cycles, just before the peak. The lengths of these long cycles differ from person to person but are highly stable over many years in individual patients, the researchers found.

The researchers show in the paper that when the highest-risk parts of a patient’s daily and long-term cycles of brain irritability overlap, seizures are nearly seven times more likely to occur than when the two cycles are mismatched.

Rao’s team is now using this data to develop a new approach to forecasting patients’ seizure risk, which could allow patients to avoid potentially dangerous activities such as swimming or driving when their seizure risk is highest, and to potentially take steps (such as additional medication doses) to reduce their seizure risk, similar to how people with asthma know to take extra care to bring their inhalers when pollen levels are high.

“I like to compare it to a weather forecast,” Rao said. “In the past, the field has focused on predicting the exact moment a seizure will occur, which is like predicting when lightning will strike. That’s pretty hard. It may be more useful to be able tell people there is a 5 percent chance of a thunderstorm this week, but a 90 percent chance next week. That kind of information lets you prepare.”

Source:
https://www.ucsf.edu/

via Monthly cycles of brain activity linked to seizures in patients with epilepsy

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