Posts Tagged somatosensory

[ARTICLE] Sensory retraining of the leg after stroke: systematic review and meta-analysis – Full Text

This systematic review aimed to investigate the effects of interventions intended for retraining leg somatosensory function on somatosensory impairment, and secondary outcomes of balance and gait, after stroke.

Databases searched from inception to 16 January 2019 included Cochrane Library, PubMed, MEDLINE, CINAHL, EMBASE, PEDro, PsycINFO, and Scopus. Reference lists of relevant publications were also manually searched.

All types of quantitative studies incorporating interventions that intended to improve somatosensory function in the leg post stroke were retrieved. The Quality Assessment Tool for Quantitative Studies was used for quality appraisal. Standardised mean differences were calculated and meta-analyses were performed using preconstructed Microsoft Excel spreadsheets.

The search yielded 16 studies, comprising 430 participants, using a diverse range of interventions. In total, 10 of the included studies were rated weak in quality, 6 were rated moderate, and none was rated strong. Study quality was predominantly affected by high risk of selection bias, lack of blinding, and the use of somatosensory measures that have not been psychometrically evaluated. A significant heterogeneous positive summary effect size (SES) was found for somatosensory outcomes (SES: 0.52; 95% confidence interval (CI): 0.04 to 1.01; I2 = 74.48%), which included joint position sense, light touch, and two-point discrimination. There was also a significant heterogeneous positive SES for Berg Balance Scale scores (SES: 0.62; 95% CI: 0.10 to 1.14; I2 = 59.05%). Gait SES, mainly of gait velocity, was not significant.

This review suggests that interventions used for retraining leg somatosensory impairment after stroke significantly improved somatosensory function and balance but not gait.

 

Somatosensory impairment is common after stroke, occurring in up to 89% of stroke survivors.1Proprioception and tactile somatosensation are more impaired in the leg than in the arm post stroke,2 with the frequency increasing with increasing level of weakness and stroke severity.2,3 Leg somatosensory impairment also has a significant impact on independence in daily activities3 and activity participation in stroke survivors,4 as well as predicts longer hospital stays and lower frequency of home discharges.5

Leg somatosensory impairment negatively influences balance and gait. Post-stroke plantar tactile deficits correlate with lower balance scores and greater postural sway in standing.6 Tactile and proprioceptive feedback provide critical information about weight borne through the limb.7 Accordingly, tactile and proprioceptive somatosensory deficits may hinder paretic limb load detection ability, potentially leading to reduced weight-bearing and contributing to balance impairment and falls post stroke.8 Indeed, stroke survivors with somatosensory impairment have a higher falls incidence compared to those without somatosensory impairment.3 In addition to reduced balance, impaired load detection may also contribute to gait asymmetry, particularly in the push-off phase.8 In addition, leg proprioception influences variance in stride length, gait velocity,9 and walking endurance in stroke survivors.10 In fact, leg somatosensory impairment has been shown to be the third most important independent factor for reduced gait velocity in stroke survivors.11

Two systematic reviews have previously investigated the effects of interventions for retraining somatosensory function after stroke.12,13 In the first review, published more than a decade ago, only four of the 14 included studies targeted the leg,12 while the second only included studies of the arm.13 Nevertheless, both reviews reported that there were insufficient data to determine the effectiveness of these interventions. A third systematic review evaluating the effectiveness of proprioceptive training14 only included 16 studies with stroke-specific populations, of which only two specifically addressed the leg. From these three reviews, the effects of interventions for post-stroke leg somatosensory impairment remain unclear. In addition, the first review12 was critiqued for including studies with participants without somatosensory impairment, and that did not report somatosensory outcomes.15 Therefore, a targeted systematic review, addressing the limitations of previous reviews, is required to elucidate the effects of interventions for post-stroke leg somatosensory impairment.

It is of interest to clinicians and researchers to evaluate the effects of leg somatosensory retraining on factors that may ultimately influence activity and participation, as this could change practice. Therefore, this systematic review aimed to examine the effects of post-stroke leg somatosensory retraining on somatosensory impairment, balance, gait, motor impairment, and leg function.[…]

 

Continue —> Sensory retraining of the leg after stroke: systematic review and meta-analysis – Fenny SF Chia, Suzanne Kuys, Nancy Low Choy, 2019

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[Abstract + References] Brain Computer Interfaces in Rehabilitation Medicine – PM&R

Abstract

One innovation currently influencing physical medicine and rehabilitation is brain–computer interface (BCI) technology. BCI systems used for motor control record neural activity associated with thoughts, perceptions, and motor intent; decode brain signals into commands for output devices; and perform the user’s intended action through an output device. BCI systems used for sensory augmentation transduce environmental stimuli into neural signals interpretable by the central nervous system. Both types of systems have potential for reducing disability by facilitating a user’s interaction with the environment. Investigational BCI systems are being used in the rehabilitation setting both as neuroprostheses to replace lost function and as potential plasticity-enhancing therapy tools aimed at accelerating neurorecovery. Populations benefitting from motor and somatosensory BCI systems include those with spinal cord injury, motor neuron disease, limb amputation, and stroke. This article discusses the basic components of BCI for rehabilitation, including recording systems and locations, signal processing and translation algorithms, and external devices controlled through BCI commands. An overview of applications in motor and sensory restoration is provided, along with ethical questions and user perspectives regarding BCI technology.

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via Brain Computer Interfaces in Rehabilitation Medicine – PM&R

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[BLOG POST] The Brain’s Sensational Juggling Act

(Credit: Shutterstock)

You’re bombarded with sensory information every day — sights, sounds, smells, touches and tastes. A constant barrage that your brain has to manage, deciding which information to trust or which sense to use as a backup when another fails. Understanding how the brain evaluates and juggles all this input could be the key to designing better therapies for patients recovering from stroke, nerve injuries, or other conditions. It could also help engineers build more realistic virtual experiences for everyone from gamers to fighter pilots to medical patients.

Now, some researchers are using virtual reality (VR) and even robots to learn how the brain pulls off this juggling act.

Do You Believe Your Eyes?

At the University of Reading in the U.K., psychologist Peter Scarfe and his team are currently exploring how the brain combines information from touch, vision, and proprioception – our sense of where our body is positioned – to form a clear idea of where objects are in space.

Generally, the brain goes with whichever sense is more reliable at the time. For instance, in a dark room, touch and proprioception trump vision. But when there’s plenty of light, you’re more likely to believe your eyes. Part of what Scarfe’s crew hopes to eventually unravel is how the brain combines information from both senses and whether that combination is more accurate than touch or sight alone. Does the brain trust input from one sense and ignore the other, does it split the difference between the two, or does it do something more complex?

To find out, the team is using a VR headset and a robot called Haptic Master.

While volunteers wear the VR headset, they see four virtual balls – three in a triangle formation and one in the center. They can also reach out and touch four real spheres that appear in the same place as the ones they see in VR: the three in the triangle formation are just plastic and never move, but the fourth is actually a ball bearing at the end of Haptic Master’s robot arm. Researchers use the robot to move this fourth ball between repetitions of the test. Think of the three-ball-triangle as a flat plane in space. The participant has to decide whether the fourth ball is higher or lower than the level of that triangle.

It’s a task that requires the brain to weigh and combine information from multiple senses to decide where the fourth ball is in relation to the other three. Participants get visual cues about the ball’s location through the VR headset, but they also use their haptic sense – the combination of touch and proprioception – to feel where the ball is in space.

The VR setup makes it easier to control the visual input and make sure volunteers aren’t using other cues, like the location of the robot arm or other objects in the room, to make their decisions.

Collectively, volunteers have performed this task hundreds of times. Adams and his colleagues are looking at how accurate the results are when the participant used only their eyes, only their haptic sense, or both senses at once. The team is then comparing those results to several computer models, each predicting how a person would estimate the ball’s position if their brain combined the sensory information in different ways.

So far, the team needs more data to learn which model best describes how the brain combines sensory cues. But they say that their results, and those of others working in the field, could one day help design more accurate haptic feedback, which could make interacting with objects in virtual reality feel more realistic.

On Shaky Footing

Anat Lubetzky, a physical therapy researcher at New York University, is also turning to VR. She uses the burgeoning technology to study how our brains weigh different sensory input to help us when things get shaky — specifically, if people rely on their sense of proprioception or their vision to keep their balance.

Conventional wisdom in sports medicine says that standing on an uneven surface is a good proprioception workout for patients in rehabilitation after an injury. That’s because it forces your somatosensory system, the nerves involved in proprioception, to work harder. So if your balance is suffering because of nerve damage, trying to stabilize yourself while standing on an uneven surface, like a bosu ball, should help.

But Lubetzky’s results tell a different story.

In the lab, Lubetzky’s subjects strap on VR headsets and stand on either a solid floor or an unsteady surface, like a wobble board. She projects some very subtly moving dots onto the VR display and uses a pressure pad on the floor to measure how participants’ bodies sway.

It turns out, when people stand on an unstable surface, they’re more likely to sway in time with the moving dots. But on a stable surface, they seem to pay less attention to the dots.

So rather than working their somatosensory systems harder, it seems people use their vision to look for a fixed reference point to help keep them balanced. In other words, the brain switches from a less reliable sense to a more reliable one, a process called sensory weighting.

Ultimately, Lubetzky hopes her VR setup could help measure how much a patient with somatosensory system damage relies on their vision. This knowledge, in turn, could help measure the severity of the problem so doctors can design a better treatment plan.

As VR gets more realistic and more immersive – partly thanks to experiments like these – it could offer researchers an even more refined tool for picking apart what’s going on in the brain.

Says Lubetzky, “It’s been a pretty amazing revolution.”

Source: The Brain’s Sensational Juggling Act – D-brief

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[ARTICLE] Biomarkers of stroke recovery: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable – Full Text

In practical terms, biomarkers should improve our ability to predict long-term outcomes after stroke across multiple domains. This is beneficial for: (a) patients, caregivers and clinicians; (b) planning subsequent clinical pathways and goal setting; and (c) identifying whom and when to target, and in some instances at which dose, with interventions for promoting stroke recovery.2 This last point is particularly important as methods for accurate prediction of long-term outcome would allow clinical trials of restorative and rehabilitation interventions to be stratified based on the potential for neurobiological recovery in a way that is currently not possible when trials are performed in the absence of valid biomarkers. Unpredictable outcomes after stroke, particularly in those who present with the most severe impairment3 mean that clinical trials of rehabilitation interventions need hundreds of patients to be appropriately powered. Use of biomarkers would allow incorporation of accurate information about the underlying impairment, and thus the size of these intervention trials could be considerably reduced,4 with obvious benefits. These principles are no different in the context of stroke recovery as compared to general medical research.5

Interventions fall into two broad mechanistic categories: (1) behavioural interventions that take advantage of experience and learning-dependent plasticity (e.g. motor, sensory, cognitive, and speech and language therapy), and (2) treatments that enhance the potential for experience and learning-dependent plasticity to maximise the effects of behavioural interventions (e.g. pharmacotherapy or non-invasive brain stimulation).6 To identify in whom and when to intervene, we need biomarkers that reflect the underlying biological mechanisms being targeted therapeutically.

Our goal is to provide a consensus statement regarding the evidence for SRBs that are helpful in outcome prediction and therefore identifying subgroups for stratification to be used in trials.7 We focused on SRBs that can investigate the structure or function of the brain (Table 1). Four functional domains (motor, somatosensation, cognition, and language (Table 2)) were considered according to recovery phase post stroke (hyperacute: <24 h; acute: 1 to 7 days; early subacute: 1 week to 3 months; late subacute: 3 months to 6 months; chronic: > 6 months8). For each functional domain, we provide recommendations for biomarkers that either are: (1) ready to guide stratification of subgroups of patients for clinical trials and/or to predict outcome, or (2) are a developmental priority (Table 3). Finally, we provide an example of how inclusion of a clinical trial-ready biomarker might have benefitted a recent phase III trial. As there is generally limited evidence at this time for blood or genetic biomarkers, we do not discuss these, but recommend they are a developmental priority.912 We also recognize that many other functional domains exist, but focus here on the four that have the most developed science. […]

Continue —> Biomarkers of stroke recovery: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation RoundtableInternational Journal of Stroke – Lara A Boyd, Kathryn S Hayward, Nick S Ward, Cathy M Stinear, Charlotte Rosso, Rebecca J Fisher, Alexandre R Carter, Alex P Leff, David A Copland, Leeanne M Carey, Leonardo G Cohen, D Michele Basso, Jane M Maguire, Steven C Cramer, 2017

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[Dissertation] Brain Mechanism for Enhanced Hand Function with Remote Sensory Stimulation – Full Text PDF

ABSTRACT

BRAIN MECHANISM FOR ENHANCED HAND FUNCTION WITH REMOTE SENSORY STIMULATION

by

Kishor Lakshmi Narayanan

The University of Wisconsin-Milwaukee, 2016

Under the Supervision of Professor Mohammad Habibur Rahman

The neurological bases for remote vibration enhanced sensory feedback and motor function are yet poorly understood. The purpose of this dissertation was to identify and examine the effect of vibration on finger tactile sensation in healthy adults and how imperceptible random vibration applied to the wrist changes cortical activity for fingertip sensation and precision grip. In a series of studies on healthy adults, white-noise vibration was applied to one of four locations (dorsum hand by the second knuckle, thenar and hypothenar areas, and volar wrist) at one of four intensities (zero, 60%, 80%, and 120% of the sensory threshold for each vibration location), while the fingertip sensation, the smallest vibratory signal that could be perceived on the thumb and index fingertip pads, was assessed. Vibration intensities significantly affected the fingertip sensation (p<.01) in a similar manner for all four vibration locations. Specifically, vibration at 60% of the sensory threshold improved the thumb and index fingertip tactile sensation (p<.01), while vibration at 120% of the sensory threshold degraded the thumb and index fingertip tactile sensation (p<.01) and the 80% vibration did not significantly change the fingertip sensation (p>.01), all compared with the zero vibration condition. The next step was to examine the cortical activity for this vibration-enhanced fingertip sensation. We measured somatosensory evoked potentials to assess peak-to-peak response to light touch of the index fingertip with applied wrist vibration versus without. We observed increased peak-to-peak somatosensory evoked potentials with wrist vibration, especially with increased amplitude of the later component for the somatosensory, motor, and premotor cortex with wrist vibration. These findings corroborate an enhanced cortical-level sensory response motivated by vibration. It is possible that the cortical modulation observed here is the result of the establishment of transient networks for improved perception. Finally, we examined the effect of imperceptible vibration applied to the wrist on cortical control for precision grip. We measured β-band power to assess peak-to-peak response while subjects performed precision pinch with wrist vibration versus without. We observed increased peak-to-peak β-band power amplitude with wrist vibration, especially with event-related synchronization for the prefrontal, sensorimotor, motor, premotor, and supplementary motor areas with vibration. The enhanced motor function may possibly be a result of higher recalibration following movement and faster motor learning.

Full Text PDF

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[ARTICLE] Virtual reality training improves balance function

Virtual reality is a new technology that simulates a three-dimensional virtual world on a computer and enables the generation of visual, audio, and haptic feedback for the full immersion of users. Users can interact with and observe objects in three-dimensional visual space without limitation. At present, virtual reality training has been widely used in rehabilitation therapy for balance dysfunction. This paper summarizes related articles and other articles suggesting that virtual reality training can improve balance dysfunction in patients after neurological diseases. When patients perform virtual reality training, the prefrontal, parietal cortical areas and other motor cortical networks are activated. These activations may be involved in the reconstruction of neurons in the cerebral cortex. Growing evidence from clinical studies reveals that virtual reality training improves the neurological function of patients with spinal cord injury, cerebral palsy and other neurological impairments. These findings suggest that virtual reality training can activate the cerebral cortex and improve the spatial orientation capacity of patients, thus facilitating the cortex to control balance and increase motion function.

via Virtual reality training improves balance function Mao Y, Chen P, Li L, Huang D – Neural Regen Res.

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