Posts Tagged Postural Control

[Abstract] Ergometer training in stroke rehabilitation: systematic review and meta-analysis

Abstract

Objective

Ergometer training is routinely used in stroke rehabilitation. How robust is the evidence of its effects?

Data source

The PubMed database and PEDro database were reviewed prior to 22/01/2019.

Study selection

Randomized controlled trials investigating the effects of ergometer training on stroke recovery were selected.

Data extraction

Two reviewers independently selected the studies, performed independent data extraction, and assessed the risk of bias.

Data synthesis

A total of 28 studies (including 1115 stroke subjects) were included. The data indicates that

(1) ergometer training leads to a significant improvement of walking ability, cardiorespiratory fitness, motor function and muscular force of lower limbs, balance and postural control, spasticity, cognitive abilities, as well as the brain’s resistance to damage and degeneration,

(2) neuromuscular functional electrical stimulation assisted ergometer training is more efficient than ergometer training alone,

(3) high-intensity ergometer training is more efficient that low-intensity ergometer training, and

(4) ergometer training is more efficient than other therapies in supporting cardiorespiratory fitness, independence in activities of daily living, and balance and postural control, but less efficient in improving walking ability.

Conclusion

Ergometer training can support motor recovery after stroke. However, current data is insufficient for evidence-based rehabilitation. More data is required about the effects of ergometer training on cognitive abilities, emotional status, and quality of life in stroke subjects.

via Ergometer training in stroke rehabilitation: systematic review and meta-analysis – Archives of Physical Medicine and Rehabilitation

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[ARTICLE] Robot-Assisted Stair Climbing Training on Postural Control and Sensory Integration Processes in Chronic Post-stroke Patients: A Randomized Controlled Clinical Trial – Full Text

Background: Postural control disturbances are one of the important causes of disability in stroke patients affecting balance and mobility. The impairment of sensory input integration from visual, somatosensory and vestibular systems contributes to postural control disorders in post-stroke patients. Robot-assisted gait training may be considered a valuable tool in improving gait and postural control abnormalities.

Objective: The primary aim of the study was to compare the effects of robot-assisted stair climbing training against sensory integration balance training on static and dynamic balance in chronic stroke patients. The secondary aims were to compare the training effects on sensory integration processes and mobility.

Methods: This single-blind, randomized, controlled trial involved 32 chronic stroke outpatients with postural instability. The experimental group (EG, n = 16) received robot-assisted stair climbing training. The control group (n = 16) received sensory integration balance training. Training protocols lasted for 5 weeks (50 min/session, two sessions/week). Before, after, and at 1-month follow-up, a blinded rater evaluated patients using a comprehensive test battery. Primary outcome: Berg Balance Scale (BBS). Secondary outcomes:10-meter walking test, 6-min walking test, Dynamic gait index (DGI), stair climbing test (SCT) up and down, the Time Up and Go, and length of sway and sway area of the Center of Pressure (CoP) assessed using the stabilometric assessment.

Results: There was a non-significant main effect of group on primary and secondary outcomes. A significant Time × Group interaction was measured on 6-min walking test (p = 0.013) and on posturographic outcomes (p = 0.005). Post hoc within-group analysis showed only in the EG a significant reduction of sway area and the CoP length on compliant surface in the eyes-closed and dome conditions.

Conclusion: Postural control disorders in patients with chronic stroke may be ameliorated by robot-assisted stair climbing training and sensory integration balance training. The robot-assisted stair climbing training contributed to improving sensorimotor integration processes on compliant surfaces. Clinical trial registration (NCT03566901).

Introduction

Postural control disturbances are one of the leading causes of disability in stroke patients, leading to problems with transferring, maintaining body position, mobility, and walking (Bruni et al., 2018). Therefore, the recovery of postural control is one of the main goals of post-stroke patients. Various and mixed components (i.e., weakness, joint limitation, alteration of tone, loss of movement coordination and sensory organization components) can affect postural control. Indeed, the challenge is to determine the relative weight placed on each of these factors and their interaction to plan specific rehabilitation programs (Bonan et al., 2004).

The two functional goals of postural control are postural orientation and equilibrium. The former involves the active alignment of the trunk and head to gravity, the base of support, visual surround and an internal reference. The latter involves the coordination of movement strategies to stabilize the center of body mass during self-initiated and externally triggered stability perturbations. Postural control during static and dynamic conditions requires a complex interaction between musculoskeletal and neural systems (Horak, 2006). Musculoskeletal components include biomechanical constraints such as the joint range of motion, muscle properties and limits of stability (Horak, 2006). Neural components include sensory and perceptual processes, motor processes involved in organizing muscles into neuromuscular synergies, and higher-level processes essential to plan and execute actions requiring postural control (Shumway-Cook and Woollacott, 2012). A disorder in any of these systems may affect postural control during static (in quite stance) and dynamic (gait) tasks and increase the risk of falling (Horak, 2006).

Literature emphasized the role of impairments of sensory input integration from visual, somatosensory and vestibular systems in leading to postural control disorders in post-stroke patients (Bonan et al., 2004Smania et al., 2008). Healthy persons rely on somatosensory (70%), vision (10%) and vestibular (20%) information when standing on a firm base of support in a well-lit environment (Peterka, 2002). Conversely, in quite stance on an unstable surface, they increase sensory weighting to vestibular and vision information as they decrease their dependence on surface somatosensory inputs for postural orientation (Peterka, 2002). Bonan et al. (2004) investigate whether post-stroke postural control disturbances may be caused by the inability to select the pertinent somatosensory, vestibular or visual information. Forty patients with hemiplegia after a single hemisphere chronic stroke (at least 12 months) performed computerized dynamic posturography to assess the patient’s ability to use sensory inputs separately and to suppress inaccurate inputs in case of sensory conflict. Six sensory conditions were assessed by an equilibrium score, as a measure of body stability. Results show that patients with hemiplegia seem to rely mostly on visual input. In conditions of altered somatosensory information, with visual deprivation or visuo-vestibular conflict, the patient’s performance was significantly lower than healthy subjects. The mechanism of this excessive visual reliance remains unclear. However, higher-level inability to select the appropriate sensory input rather than to elementary sensory impairment has been advocated as a potential mechanism of action (Bonan et al., 2004).

Sensory strategies and sensory reweighting processes are essential to generate effective movement strategies (ankle, hip, and stepping strategies) which can be resolved through feed-back or feed-forward postural adjustments. The cerebral cortex shapes these postural responses both directly via corticospinal loops and indirectly via the brainstem centers (Jacobs and Horak, 2007). Moreover, the cerebellar- and basal ganglia-cortical loop is responsible for adapting postural responses according to prior experience and for optimizing postural responses, respectively (Jacobs and Horak, 2007).

Rehabilitation is the cornerstone in the management of postural control disorders in post-stroke patients (Pollock et al., 2014). To date, no one physical rehabilitation approach can be considered more effective than any other approach (Pollock et al., 2014). Specific treatments should be chosen according to the individual requirements and the evidence available for that specific treatment. Moreover, it appears to be most beneficial a mixture of different treatment for an individual patient (Pollock et al., 2014). Considering that, rehabilitation involving repetitive, high intensity, task-specific exercises is the pathway for restoring motor function after stroke (Mehrholz et al., 2013Lo et al., 2017) robotic assistive devices for gait training have been progressively being used in neurorehabilitation to Sung et al. (2017). In the current literature, three primary evidence have been reported.

Firstly, a recent literature review highlights that robot-assisted gait training is advantageous as add-on therapy in stroke rehabilitation, as it adds special therapeutic effects that could not be afforded by conventional therapy alone (Morone et al., 2017Sung et al., 2017). Specifically, robot-assisted gait training was beneficial for improving motor recovery, gait function, and postural control in post-stroke patients (Morone et al., 2017Sung et al., 2017). Stroke patients who received physiotherapy treatment in combination with robotic devices were more likely to reach better outcomes compared to patients who received conventional training alone (Bruni et al., 2018).

Second, the systematic review by Swinnen et al. (2014) supported the use of robot-assisted gait therapy to improve postural control in subacute and chronic stroke patients. A wide variability among studies was reported about the robotic-device system and the therapy doses (3–5 times per week, 3–10 weeks, 12–25 sessions). However, significant improvements (Cohen’s d = 0.01 to 3.01) in postural control scores measured with the Berg Balance Scale (BBS), the Tinetti test, postural sway tests, and the Timed Up and Go (TUG) test were found after robot-assisted gait training. Interestingly, in five studies an end-effector device (gait trainer) was used (Peurala et al., 2005Tong et al., 2006Dias et al., 2007Ng et al., 2008Conesa et al., 2012). In two study, the exoskeleton was used (Hidler et al., 2009Westlake and Patten, 2009). In one study, a single joint wearable knee orthosis was used (Wong et al., 2012). Because the limited number of studies available and methodological differences among them, more specific randomized controlled trial in specific populations are necessary to draw stronger conclusions (Swinnen et al., 2014).

Finally, technological and scientific development has led to the implementation of robotic devices specifically designed to overcome the motor limitation in different tasks. With this perspective, the robot-assisted end-effector-based stair climbing (RASC) is a promising approach to facilitate task-specific activity and cardiovascular stress (Hesse et al., 20102012Tomelleri et al., 2011Stoller et al., 20142016Mazzoleni et al., 2017).

To date, no studies have been performed on the effects of RASC training in improving postural control and sensory integration processes in chronic post-stroke patients.

The primary aim of the study was to compare the effects of robot-assisted stair climbing training against sensory integration balance training on static and dynamic balance in chronic stroke patients. The secondary aims were to compare the training effects on sensory integration processes and mobility. The hypothesis was that the task-specific and repetitive robot-assisted stairs climbing training might act as sensory integration balance training, improving postural control because sensorimotor integration processes are essential for balance and walking.[…]

 

Continue —->  Frontiers | Robot-Assisted Stair Climbing Training on Postural Control and Sensory Integration Processes in Chronic Post-stroke Patients: A Randomized Controlled Clinical Trial | Neuroscience

Figure 1. The G-EO system used in the Robot-Assisted Stair-Climbing Training (Written informed consent was obtained from the individual pictured, for the publication of this image).

 

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[Abstract] Functional Balance and Postural Control Improvements in Patients with Stroke after Non-Invasive Brain Stimulation: A Meta-Analysis

Highlights

  • NIBS improved deficits in functional balance and postural control post stroke.
  • The treatment effects on postural imbalance were significant following rTMS.
  • The improvements after rTMS appeared in acute, subacute, and chronic patients.
  • A higher number of rTMS sessions significantly increased the treatment effects.

Abstract

Objectives

The postural imbalance post stroke limits individual’s walking abilities as well as increase the risk of falling. We investigated the short-term treatment effects of non-invasive brain stimulation (NIBS) on functional balance and postural control in patients with stroke.

Data Sources

We started the search via PubMed and ISI’s Web of Science on March 1, 2019 and concluded the search on April 30, 2019.

Study Selection

The meta-analysis included studies that used either repetitive transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS) for the recovery of functional balance and postural control post stroke. All included studies used either randomized control trial or crossover designs with a sham control group.

Data Extraction

Three researchers independently performed data extraction and assessing methodological quality and publication bias. We calculated overall and individual effect sizes using random effects meta-analysis models.

Data Synthesis

The random effects meta-analysis model on the 18 qualified studies identified the significant positive effects relating to NIBS in terms of functional balance and postural control post stroke. The moderator variable analyses revealed that these treatment effects were only significant in rTMS across acute/subacute and chronic stroke patients whereas tDCS did not show any significant therapeutic effects. The meta-regression analysis showed that a higher number of rTMS sessions was significantly associated with more improvements in functional balance and postural control post stroke.

Conclusions

Our systematic review and meta-analysis confirmed that NIBS may be an effective option for restoring functional balance and postural control for patients with stroke.

via Functional Balance and Postural Control Improvements in Patients with Stroke after Non-Invasive Brain Stimulation: A Meta-Analysis – Archives of Physical Medicine and Rehabilitation

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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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[ARTICLE] The effect of virtual reality-based balance training on motor learning and postural control in healthy adults: a randomized preliminary study – Full Text

Abstract

Background

Adults with sedentary lifestyles seem to face a higher risk of falling in their later years. Several causes, such as impairment of strength, coordination, and cognitive function, influence worsening health conditions, including balancing ability. Many modalities can be applied to improve the balance function and prevent falling. Several studies have also recorded the effects of balance training in elderly adults for fall prevention. Accordingly, the aim of this study is to define the effect of virtual reality-based balance training on motor learning and postural control abilities in healthy adults.

Methods

For this study, ten subjects were randomly allocated into either the conventional exercise (CON) or the virtual reality (VR) group. The CON group underwent physical balance training, while the VR group used the virtual reality system 4 weeks. In the VR group, the scores from three game modes were utilized to describe the effect of motor learning and define the learning curves that were derived with the power law function. Wilcoxon Signed Ranks Test was performed to analyze the postural control in five standing tasks, and data were collected with the help of a force plate.

Results

The average score was used to describe the effect of motor learning by deriving the mathematical models for determining the learning curve. Additionally, the models were classified into two exponential functions that relied on the aim and requirement skills. A negative exponential function was observed in the game mode, which requires the cognitive-motor function. In contrast, a positive exponential function was found in the game with use of only the motor skill. Moreover, this curve and its model were also used to describe the effect of learning in the long term and the ratio of difficulty in each game. In the balance performance, there was a significant decrease in the center of pressure parameters in the VR group, while in the CON group, there was a significant increase in the parameters during some foot placements, especially in the medio-lateral direction.

Conclusion

The proposed VR-based training relies on the effect of motor learning in long-term training though different kinds of task training. In postural analysis, both exercise programs are emphasized to improve the balance ability in healthy adults. However, the virtual reality system can promote better outcomes to improve postural control post exercising.

Trial registration Retrospectively registered on 25 April 2018. Trial number TCTR20180430005

Electronic supplementary material

The online version of this article (10.1186/s12938-018-0550-0) contains supplementary material, which is available to authorized users.

Background

The incidence of falls can occur in people of all ages and is not exclusively restricted to the elderly population []. Although the causes of falls are different for each age group, the decline in balance ability is a major factor for the high risk of falls. In older people, the decline in balance ability may occur due to physiological deterioration, pathological factors, problems of ambulation, and endurance reduction []. In addition, the physical activity level of children and middle-aged adults has decreased due to the development of technology, which has resulted in restriction of movement. This has led to the worsening of health conditions due to the deterioration of the neurotransmitter system [] and muscle mass and strength [], giving rise to chronic diseases [] as well as cognitive decline [], which may induce a higher risk of falls in the future. People who suffer from these tend to get injured easily, which results in worsening of self-efficacy and functional dysfunction, even though they are disturbed by a small disturbance []. Increasing physical activity, such as exercise, has a positive effect on several aspects, including postural stability and falling prevention [].

Exercising is important, as it improves humans’ individual or systematic system, which is related to balance performance []. Exercises employ help prevent physiological deterioration by increasing strength and endurance of the body. For example, challenging the sensory system during postural tasks can enhance balance ability by reweighting the functional sensory inputs []. However, significant differences have been observed among various exercise programs, and some exercises have little effect on the balance function []. Balance exercise programs may be made ineffective because of several reasons. First, various physiological systems are used to achieve the postural task []. Second, the activities, which require balancing ability, can be achieved by coordinating between motor skills and cognitive activities []. Moreover, the training program with clinical guidelines is more effective than the program without any instruction []. Therefore, a combination of the exercise approach and the feedback during training process is used to improve the body’s functional ability, including balance performance [].

Using the gaming with the biofeedback system, such as the virtual reality (VR) system, is widely used for rehabilitation []. It is due to the fact that the VR system can make the treatment more interesting, reduce the difficulty of rehabilitation, and increase safety []. One advantage of VR-based training is that this technology allows altering the neural organization, encouraging neuroplastic changes in neurological patients [], reducing the fear of falling, and transferring into the real-world task through motor learning []. However, some VR-based balance training requires a specific balance platform, including Wii Fit balance board, to supply the sensory feedback information that may be restricted during the training process due to the requirement of a specific movement []. For this reason, popular sensors, e.g., the Microsoft Kinect sensor, have been used to show improvement in balance ability in several studies. This is due to the fact that Kinect sensor provides three-dimensional positions without using markers. These positions are used as input for the VR-system to improve balance function and reduce the fear of falling in older adults [].

In several studies, there were significant differences in clinical balance measures among participants who had trained with the help of conventional balance exercises, including the VR system []. Additionally, most studies focused on their applications in improving balance for patients with neurological disorders [] or elderly people []. Therefore, the aim of this study is to investigate the effects of VR-based balance training in healthy adults through motor learning and postural control. The questions included in the proposed study are (a) how does the VR-based balance exercise rely on the effect of motor learning? (b) how do the different exercise modalities influence the impairment of balance ability through comparison of balance performance before and after exercise? We hypothesize that the VR system affects postural control through motor learning. In addition, both balance exercise programs influence the postural control, but the balance performance in the VR-based balance exercise is better than the outcome of the conventional exercise.

Methods

Participants

The experiment in this study was designed as the pilot study. Community-dwelling healthy adults around the area of Mahidol University were recruited for the study. The inclusion criteria were (a) 40–60 years of age, (b) no history of injuries or diseases that influence balance function, (c) no intake of medications that affect postural control system, at least 12 h prior to the experiment, (d) no alcohol consumption 12 h prior to the experiment. The exclusion criteria were (a) individuals with dependent ambulation, (b) individuals who cannot communicate in the Thai language, and (c) individuals who have any disease that affects balance function.

Prior to data collection, all participants signed informed consent, which was approved by the Mahidol University Central Institutional Review Board (MU-IRB: 2014/112.1508). Demographic data and health information of the participants were obtained, following which they were randomly categorized into two groups, the virtual reality exercise (VR) group and the conventional balance exercise (CON) group, by blindly drawing a sealed piece of paper. The VR group (n = 5) received the dual-task virtual-reality balance training system (DTVRBT), while the CON group (n = 5) was assigned the conventional balance exercise.

Protocol

The experimental protocol comprised three steps: the pre-test of balance performance, the balance training session, and the post-test for the evaluation of the balance ability after training. In the study, five standing tasks, including standing unsupported with eyes open (EO) and close (EC) conditions, standing with both feet together, tandem, and one-leg stance were evaluated. Results of balance evaluation in each task were collected for 10 s/trial, with three trials, and the testing focused on the dominant leg in tandem and the one-leg stance. The total of time duration for data analysis was 30 s. In this study, the MatScan® model 3150 (Massachusetts, USA) was used to assess the center-of-pressure (CoP) in the anterior–posterior (AP) and medio-lateral (ML) directions with the sampling rate was 64 Hz. The data of each subject was exported with the Sway Analysis Module (SAM™). The training session started after 1 week of completion of the pre-test, and the post-test was performed within 1 week of finishing the training session. All participants received twelve 45-min sessions of training in the DTVRBT or the conventional balance exercise program. Moreover, three sessions were held per week for a period of 4 weeks. The same physical therapist conducted the training for both groups.

Dual-task virtual reality balance training system

The DTVRBT consists of a laptop and the Kinect sensor (Washington, USA) as shown in Fig. Fig.1.1. This sensor can construct 3D images from the functional integration of two components, an RGB camera and an infrared sensor []. The 3D information from this sensor allows users to interact with the object in the virtual environment. In this study, the virtual environment was created with the Unity3D® version 5.3.2. (San Francisco, USA).

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Fig. 1
The process of interaction in the virtual environment by the Kinect sensor

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[Abstract] Stabilometric analysis of the effect of postural insoles on static balance in patients with hemiparesis: A randomized, controlled, clinical trial

Summary

Background

Stroke is one of the main causes of disability among adults.

Objective

The aim of the present study was to analyze the effect of postural insoles on static balance in individuals with stroke.

Methods

Twenty-four strokes survivors with hemiparesis were recruited from the rehabilitation clinics of the university and randomly allocated to two groups: experimental and control group. The subjects were analyzed for stabilometry, immediately following insole placement and after three months of insole usage, with eyes open and eyes closed.

Results

A significant difference was found immediately after postural insole placement regarding anteroposterior range of movement (p < 0.05). Moreover, significant reductions were found in the inter-group analysis after three months of insole usage.

Conclusion

Based on the present findings, postural insoles combined with conventional physical therapy offer significant benefits regarding static postural control among stroke victims after three months of use, as demonstrated by computerized stabilometry.

via Stabilometric analysis of the effect of postural insoles on static balance in patients with hemiparesis: A randomized, controlled, clinical trial – Journal of Bodywork and Movement Therapies

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[BROCHURE] Utilization of Postural Control Training to Improve Gait Symmetry and Walking Ability in a Patient Following a Lacunar Stroke: A Case Report

With consideration of the many unique factors contributing to the patient as a whole, physical therapy interventions addressed the patient’s own mobility goals to allow him to participate more fully in his environment and have a greater overall quality of life.

To outline physical therapy rehabilitation that utilized postural control training, task-oriented training, and visual feedback to improve walking ability and functional capacity in a patient following a lacunar stroke

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