Posts Tagged therapy

[ARTICLE] Pilot testing of the spring operated wearable enhancer for arm rehabilitation (SpringWear) – Full Text

Abstract

Background

Robotic devices for neurorehabilitation of movement impairments in persons with stroke have been studied extensively. However, the vast majority of these devices only allow practice of stereotyped components of simulated functional tasks in the clinic. Previously we developed SpringWear, a wearable, spring operated, upper extremity exoskeleton capable of assisting movements during real-life functional activities, potentially in the home. SpringWear assists shoulder flexion, elbow extension and forearm supination/pronation. The assistance profiles were designed to approximate the torque required to move the joint passively through its range. These three assisted DOF are combined with two passive shoulder DOF, allowing complex multi-joint movement patterns.

Methods

We performed a cross-sectional study to assess changes in movement patterns when assisted by SpringWear. Thirteen persons with chronic stroke performed range of motion (ROM) and functional tasks, including pick and place tasks with various objects. Sensors on the device measured rotation at all 5 DOF and a kinematic model calculated position of the wrist relative to the shoulder. Within subject t-tests were used to determine changes with assistance from SpringWear.

Results

Maximum shoulder flexion, elbow extension and forearm pronation/supination angles increased significantly during both ROM and functional tasks (p < 0.002). Elbow flexion/extension ROM also increased significantly (p < 0.001). When the subjects volitionally held up the arm against gravity, extension at the index finger proximal interphalangeal joint increased significantly (p = 0.033) when assisted by SpringWear. The forward reach workspace increased 19% (p = 0.002). Nine subjects could not complete the functional tasks unassisted and only one showed improvement on task completion with SpringWear.

Conclusions

SpringWear increased the usable workspace during reaching movements, but there was no consistent improvement in the ability to complete functional tasks. Assistance levels at the shoulder were increased only until the shoulder could be voluntarily held at 90 degrees of flexion. A higher level of assistance may have yielded better results. Also combining SpringWear with HandSOME, an exoskeleton for assisting hand opening, may yield the most dramatic improvements in functional task performance. These low-cost devices can potentially reduce effort and improve performance during task practice, increasing adherence to home training programs for rehabilitation.

Background

There are 800,000 new strokes in the United States each year [1]. Many survivors experience debilitating motor impairments in the upper extremity that negatively affect functional capacity and quality of life. Impairments can include weakness [2] and lack of coordination between different muscle groups [3]. Fifty percent of stroke survivors older than 64 have persistent hemiparesis at six months post-stroke and 26% are dependent in activities of daily living (ADL) [1]. Unfortunately, a very high level of upper extremity motor control may be needed before the impaired limb is actually incorporated into ADL. Stroke patients often appear to have adequate movement ability when observed in the laboratory, but don’t use the limb with the expected regularity [4].

Neurorehabilitation of these impairments is possible with task-specific repetitive movement practice that incorporates high repetition, volitional effort, and successful completion of tasks to prevent frustration and maintain motivation [5]. Robotics has been studied extensively as a means of assisting movements with forces applied to the limb, allowing completion of movements that would otherwise be impossible to complete unassisted. A recent meta-analysis of 34 studies including 1160 subjects found that robotic devices produced larger gains in arm function, strength and ADL ability than comparison interventions [6]. However, authors concluded the advantages of robotic therapy may not be clinically relevant. The vast majority of these studies involved patients traveling to the clinic on a regimented schedule to practice components of tasks. Home-based approaches may be more effective in increasing the amount of limb use, in particular devices that can assist movements while subjects perform real-world ADL.

Many robotic treatments involve providing partial support of the arm against gravity to enable practice of reaching within a larger workspace [78]. This approach is motivated by research that has shown that many stroke patients have an abnormal synergy whereby elevation of the shoulder against gravity impairs the ability to extend the elbow [91011]. More recently, work has shown an abnormal coupling of proximal and distal arm muscles, such that activation level of proximal muscles and level of arm support can affect control of hand and wrist muscles [1213]. However current robotic approaches that provide gravity compensation do not allow practice of tasks in real-world environments, such as in the home, while standing or when performing bimanual tasks. Also, the provision of gravity support may not completely overcome distal weakness in elbow extension and forearm supination [14]. Additionally, many robotic paradigms rely on repetitive performance of components of functional tasks, for example, planar reaching movements. This contradicts motor learning studies that suggest retention and generalization of skills requires task variability [151617].

In previous work we developed a wearable passively actuated hand exoskeleton (HandSOME) that increases finger ROM and function [1819]. However, some subjects were found to be inappropriate for HandSOME because of proximal weakness, and while the HandSOME enabled adequate range of motion at the fingers, some subjects had difficulty supinating the forearm enough to properly grasp certain objects. Furthermore, finger extension ability would degrade as the arm was lifted against gravity. This motivated the development of a wearable arm exoskeleton called the spring-operated wearable enhancer (SpringWear). Springs apply an angle-dependent torque to the joints, with the goal of increasing ROM, repertoire of possible movements, task variability and success in completing tasks.

Overall, the goal was to enable effective use of the impaired limb in the home environment, thereby allowing patients a highly variable, but meaningful task practice. SpringWear can also reduce effort in task completion promoting greater adherence to home practice schedules. At the shoulder, SpringWear provides partial gravity compensation, which reduces the muscle forces at the shoulder needed to lift the arm. With proper selection of assistance level, the initiation and control of movements are still under patient control but less effort is needed and a larger ROM can be achieved. At the elbow, patients often can flex the joint, but have limited extension, so extension torques are applied to increase elbow extension range. A similar strategy is used to assist forearm supination/pronation. In order to benefit from SpringWear, patients should have some active movement at the joints, but for profoundly weak patients, this approach will not be effective. In these patients, powered exoskeletons may be needed, since they can move the limb throughout a larger workspace than spring powered devices. However, powered devices are much more expensive and complicated to integrate into a wearable device and compact designs are often high impedance, requiring sensors to infer the patient’s intended movement trajectory, which may be difficult in very low level patients.

In this study, chronic stroke patients performed a number of tasks with and without assistance from the SpringWear, and the kinematics of the movements were compared. If successful, SpringWear combined with HandSOME, may provide an inexpensive home-based intervention for a wide range of severe to moderately impaired stroke patients.

Methods

SpringWear design

An upper limb exoskeleton, in general, needs to be adaptable to different segment lengths and have a high number of DOFs in order to allow realistic movement practice with many anatomical joint axes involved [20]. With five DOFs, SpringWear was designed to provide assistance to forearm supination/pronation, elbow extension, shoulder flexion, while providing passive joints for shoulder horizontal abduction/adduction and internal/external rotation to allow realistic upper limb movements (Fig. 1). The design uses rubber bands or bungee cords as springs to provide the assistance. These profiles can be customized for each subject by adjusting the stiffness of the springs, which is dependent on impairment level.

 

Fig. 1 Full Assembly of SpringWear with back splint. Double-headed arrows represents five degrees of freedom. Assistance was applied at shoulder FE, elbow FE, and supination/pronation

[…]

Continue —> Pilot testing of the spring operated wearable enhancer for arm rehabilitation (SpringWear) | Journal of NeuroEngineering and Rehabilitation | Full Text

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[ARTICLE] Classification of Traumatic Brain Injury for Targeted Therapies – Full Text

Abstract

The heterogeneity of traumatic brain injury (TBI) is considered one of the most significant barriers to finding effective therapeutic interventions. In October, 2007, the National Institute of Neurological Disorders and Stroke, with support from the Brain Injury Association of America, the Defense and Veterans Brain Injury Center, and the National Institute of Disability and Rehabilitation Research, convened a workshop to outline the steps needed to develop a reliable, efficient and valid classification system for TBI that could be used to link specific patterns of brain and neurovascular injury with appropriate therapeutic interventions. Currently, the Glasgow Coma Scale (GCS) is the primary selection criterion for inclusion in most TBI clinical trials. While the GCS is extremely useful in the clinical management and prognosis of TBI, it does not provide specific information about the pathophysiologic mechanisms which are responsible for neurological deficits and targeted by interventions. On the premise that brain injuries with similar pathoanatomic features are likely to share common pathophysiologic mechanisms, participants proposed that a new, multidimensional classification system should be developed for TBI clinical trials. It was agreed that preclinical models were vital in establishing pathophysiologic mechanisms relevant to specific pathoanatomic types of TBI and verifying that a given therapeutic approach improves outcome in these targeted TBI types. In a clinical trial, patients with the targeted pathoanatomic injury type would be selected using an initial diagnostic entry criterion, including their severity of injury. Coexisting brain injury types would be identified and multivariate prognostic modeling used for refinement of inclusion/exclusion criteria and patient stratification. Outcome assessment would utilize endpoints relevant to the targeted injury type. Advantages and disadvantages of currently available diagnostic, monitoring, and assessment tools were discussed. Recommendations were made for enhancing the utility of available or emerging tools in order to facilitate implementation of a pathoanatomic classification approach for clinical trials.

Introduction

Traumatic brain injury (TBI) remains a major cause of death and disability. Although much has been learned about the molecular and cellular mechanisms of TBI in the past 20 years, these advances have failed to translate into a successful clinical trial, and thus there has been no significant improvement in treatment. Among the numerous barriers to finding effective interventions to improve outcomes after TBI, the heterogeneity of the injury and identification and classification of patients most likely to benefit from the treatment are considered some of the most significant challenges (Doppenberg et al., 2004; Marshall, 2000; Narayan et al., 2002).

The type of classification one develops depends on the available data and the purpose of the classification system. An etiological classification describes the factors to change in order to prevent the condition. A symptom classificationdescribes the clinical manifestation of the problem to be solved. A prognostic classification describes the factors associated with outcome, and a pathoanatomic classification describes the abnormality to be targeted by the treatment. Most diseases were originally classified on the basis of the clinical picture using a symptom-based classification system. Beginning in the 18th century, autopsies became more routine, and an increasing number of disease conditions were classified by their pathoanatomic lesions. With improvement of diagnostic tools, modern disease classification in most fields of medicine uses a mixture of anatomically, physiologically, metabolically, immunologically, and genetically defined parameters.

Currently, the primary selection criterion for inclusion in a TBI clinical trial is the Glasgow Coma Scale (GCS), a clinical scale that assesses the level of consciousness after TBI. Patients are typically divided into the broad categories of mild, moderate, and severe injury. While the GCS has proved to be extremely useful in the clinical management and prognosis of TBI, it does not provide specific information about the pathophysiologic mechanisms responsible for the neurological deficits. This is clearly demonstrated in Figure 1, in which all six patients are classified as having a severe TBI. Given the heterogeneity of the pathoanatomic features depicted in these computed tomography (CT) scans, it is difficult to see how a therapy targeted simply for severe TBI could effectively treat all of these different types of injury. Many tools such as CT scans and magnetic resonance imaging (MRI) already exist to help differentiate the multiple types of brain injury and variety of host factors and other confounders that might influence the yield of clinical trials. In addition, newer advances in neuroimaging, biomarkers, and bioinformatics may increase the effectiveness of clinical trials by helping to classify patients into groups most likely to benefit from specific treatments.

 

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Heterogeneity of severe traumatic brain injury (TBI). Computed tomography (CT) scans of six different patients with severe TBI, defined as a Glasgow Coma Scale score of <8, highlighting the significant heterogeneity of pathological findings. CT scans represent patients with epidural hematomas (EDH), contusions and parenchymal hematomas (Contusion/Hematoma), diffuse axonal injury (DAI), subdural hematoma (SDH), subarachnoid hemorrhage and intraventricular hemorrhage (SAH/IVH), and diffuse brain swelling (Diffuse Swelling).

Continue —>  Classification of Traumatic Brain Injury for Targeted Therapies

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[Abstract] Interventions for Improving Upper Limb Function after Stroke – Cochrane Database Syst Rev.

Abstract

Impairment of the upper limbs is quite frequent after stroke, making rehabilitation an essential step towards clinical recovery and patient empowerment. This review aimed to synthetize existing evidence regarding interventions for upper limb function improvement after Stroke and to assess which would bring some benefit. The Cochrane Database of Systematic Reviews, the Database of Reviews of Effects and PROSPERO databases were searched until June 2013 and 40 reviews have been included, covering 503 studies, 18 078 participants and 18 interventions, as well asdifferent doses and settings of interventions. The main results were:

  1. Information currently available is insufficient to assess effectiveness of each intervention and to enable comparison of interventions;
  2. Transcranial direct current stimulation brings no benefit for outcomes of activities of daily living;
  3. Moderate-quality evidence showed a beneficial effect of constraint-induced movement therapy, mental practice, mirror therapy, interventions for sensory impairment, virtual reality and repetitive task practice;
  4. Unilateral arm training may be more effective than bilateral arm training;
  5. Moderate-quality evidence showed a beneficial effect of robotics on measures of impairment and ADLs;
  6. There is no evidence of benefit or harm for technics such as repetitive transcranial magnetic stimulation, music therapy, pharmacological interventions, electrical stimulation and other therapies.

Currently available evidence is insufficient and of low quality, not supporting clear clinical decisions. High-quality studies are still needed.

 

via [Analysis of the Cochrane Review: Interventions for Improving Upper Limb Function after Stroke. Cochrane Database Syst Rev. 2014,11:CD010820]. – PubMed – NCBI

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[ARTICLE] Classification of Traumatic Brain Injury for Targeted Therapies. Journal of Neurotrauma – Full Text

Abstract

The heterogeneity of traumatic brain injury (TBI) is considered one of the most significant barriers to finding effective therapeutic interventions. In October, 2007, the National Institute of Neurological Disorders and Stroke, with support from the Brain Injury Association of America, the Defense and Veterans Brain Injury Center, and the National Institute of Disability and Rehabilitation Research, convened a workshop to outline the steps needed to develop a reliable, efficient and valid classification system for TBI that could be used to link specific patterns of brain and neurovascular injury with appropriate therapeutic interventions. Currently, the Glasgow Coma Scale (GCS) is the primary selection criterion for inclusion in most TBI clinical trials. While the GCS is extremely useful in the clinical management and prognosis of TBI, it does not provide specific information about the pathophysiologic mechanisms which are responsible for neurological deficits and targeted by interventions. On the premise that brain injuries with similar pathoanatomic features are likely to share common pathophysiologic mechanisms, participants proposed that a new, multidimensional classification system should be developed for TBI clinical trials. It was agreed that preclinical models were vital in establishing pathophysiologic mechanisms relevant to specific pathoanatomic types of TBI and verifying that a given therapeutic approach improves outcome in these targeted TBI types. In a clinical trial, patients with the targeted pathoanatomic injury type would be selected using an initial diagnostic entry criterion, including their severity of injury. Coexisting brain injury types would be identified and multivariate prognostic modeling used for refinement of inclusion/exclusion criteria and patient stratification. Outcome assessment would utilize endpoints relevant to the targeted injury type. Advantages and disadvantages of currently available diagnostic, monitoring, and assessment tools were discussed. Recommendations were made for enhancing the utility of available or emerging tools in order to facilitate implementation of a pathoanatomic classification approach for clinical trials.

Introduction

Traumatic brain injury (TBI) remains a major cause of death and disability. Although much has been learned about the molecular and cellular mechanisms of TBI in the past 20 years, these advances have failed to translate into a successful clinical trial, and thus there has been no significant improvement in treatment. Among the numerous barriers to finding effective interventions to improve outcomes after TBI, the heterogeneity of the injury and identification and classification of patients most likely to benefit from the treatment are considered some of the most significant challenges (Doppenberg et al., 2004; Marshall, 2000; Narayan et al., 2002).

The type of classification one develops depends on the available data and the purpose of the classification system. An etiological classification describes the factors to change in order to prevent the condition. A symptom classificationdescribes the clinical manifestation of the problem to be solved. A prognostic classification describes the factors associated with outcome, and a pathoanatomic classification describes the abnormality to be targeted by the treatment. Most diseases were originally classified on the basis of the clinical picture using a symptom-based classification system. Beginning in the 18th century, autopsies became more routine, and an increasing number of disease conditions were classified by their pathoanatomic lesions. With improvement of diagnostic tools, modern disease classification in most fields of medicine uses a mixture of anatomically, physiologically, metabolically, immunologically, and genetically defined parameters.

Currently, the primary selection criterion for inclusion in a TBI clinical trial is the Glasgow Coma Scale (GCS), a clinical scale that assesses the level of consciousness after TBI. Patients are typically divided into the broad categories of mild, moderate, and severe injury. While the GCS has proved to be extremely useful in the clinical management and prognosis of TBI, it does not provide specific information about the pathophysiologic mechanisms responsible for the neurological deficits. This is clearly demonstrated in Figure 1, in which all six patients are classified as having a severe TBI. Given the heterogeneity of the pathoanatomic features depicted in these computed tomography (CT) scans, it is difficult to see how a therapy targeted simply for severe TBI could effectively treat all of these different types of injury. Many tools such as CT scans and magnetic resonance imaging (MRI) already exist to help differentiate the multiple types of brain injury and variety of host factors and other confounders that might influence the yield of clinical trials. In addition, newer advances in neuroimaging, biomarkers, and bioinformatics may increase the effectiveness of clinical trials by helping to classify patients into groups most likely to benefit from specific treatments. […]

 

Continue —> Classification of Traumatic Brain Injury for Targeted Therapies

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[Poster] Collaboration of Music and Physical Therapy: Case Study for Treatment of Patient with Chronic Stroke

To evaluate the change in gait speed pre- and post-treatment. To evaluate the change in quality of life pre- and post-treatment. To evaluate the change in outcome measures pre- and post-treatment.

First page of article

via Collaboration of Music and Physical Therapy: Case Study for Treatment of Patient with Chronic Stroke – Archives of Physical Medicine and Rehabilitation

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[ARTICLE] SITAR: a system for independent task-oriented assessment and rehabilitation

Over recent years, task-oriented training has emerged as a dominant approach in neurorehabilitation. This article presents a novel, sensor-based system for independent task-oriented assessment and rehabilitation (SITAR) of the upper limb.

The SITAR is an ecosystem of interactive devices including a touch and force–sensitive tabletop and a set of intelligent objects enabling functional interaction. In contrast to most existing sensor-based systems, SITAR provides natural training of visuomotor coordination through collocated visual and haptic workspaces alongside multimodal feedback, facilitating learning and its transfer to real tasks. We illustrate the possibilities offered by the SITAR for sensorimotor assessment and therapy through pilot assessment and usability studies.

The pilot data from the assessment study demonstrates how the system can be used to assess different aspects of upper limb reaching, pick-and-place and sensory tactile resolution tasks. The pilot usability study indicates that patients are able to train arm-reaching movements independently using the SITAR with minimal involvement of the therapist and that they were motivated to pursue the SITAR-based therapy.

SITAR is a versatile, non-robotic tool that can be used to implement a range of therapeutic exercises and assessments for different types of patients, which is particularly well-suited for task-oriented training.

The increasing demand for intense, task-specific neurorehabilitation following neurological conditions such as stroke and spinal cord injury has stimulated extensive research into rehabilitation technology over the last two decades.1,2 In particular, robotic devices have been developed to deliver a high dose of engaging repetitive therapy in a controlled manner, decrease the therapist’s workload and facilitate learning. Current evidence from clinical interventions using these rehabilitation robots generally show results comparable to intensity-matched, conventional, one-to-one training with a therapist.35 Assuming the correct movements are being trained, the primary factor driving this recovery appears to be the intensity of voluntary practice during robotic therapy rather than any other factor such as physical assistance required.6,7 Moreover, most existing robotic devices to train the upper limb (UL) tend to be bulky and expensive, raising further questions on the use of complex, motorised systems for neurorehabilitation.

Recently, simpler, non-actuated devices, equipped with sensors to measure patients’ movement or interaction, have been designed to provide performance feedback, motivation and coaching during training.812 Research in haptics13,14 and human motor control15,16 has shown how visual, auditory and haptic feedback can be used to induce learning of a skill in a virtual or real dynamic environment. For example, simple force sensors (or even electromyography) can be used to infer motion control17and provide feedback on the required and actual performances, which can allow subjects to learn a desired task. Therefore, an appropriate therapy regime using passive devices that provide essential and engaging feedback can enhance learning of improved arm and hand use.

Such passive sensor-based systems can be used for both impairment-based training (e.g. gripAble18) and task-oriented training (ToT) (e.g. AutoCITE8,9, ReJoyce11). ToT views the patient as an active problem-solver, focusing rehabilitation on the acquisition of skills for performance of meaningful and relevant tasks rather than on isolated remediation of impairments.19,20 ToT has proven to be beneficial for participants and is currently considered as a dominant and effective approach for training.20,21

Sensor-based systems are ideal for delivering task-oriented therapy in an automated and engaging fashion. For instance, the AutoCITE system is a workstation containing various instrumented devices for training some of the tasks used in constraint-induced movement therapy.8 The ReJoyce uses a passive manipulandum with a composite instrumented object having various functionally shaped components to allow sensing and training of gross and fine hand functions.11 Timmermans et al.22reported how stroke survivors can carry out ToT by using objects on a tabletop with inertial measurement units (IMU) to record their movement. However, this system does not include force sensors, critical in assessing motor function.

In all these systems, subjects perform tasks such as reach or object manipulation at the tabletop level, while receiving visual feedback from a monitor placed in front of them. This dislocation of the visual and haptic workspaces may affect the transfer of skills learned in this virtual environment to real-world tasks. Furthermore, there is little work on using these systems for the quantitative task-oriented assessment of functional tasks. One exception to this is the ReJoyce arm and hand function test (RAHFT)23 to quantitatively assess arm and hand function. However, the RAHFT primarily focuses on range-of-movement in different arm and hand functions and does not assess the movement quality, which is essential for skilled action.2428

To address these limitations, this article introduces a novel, sensor-based System for Independent Task-Oriented Assessment and Rehabilitation (SITAR). The SITAR consists of an ecosystem of different modular devices capable of interacting with each other to provide an engaging interface with appropriate real-world context for both training and assessment of UL. The current realisation of the SITAR is an interactive tabletop with visual display as well as touch and force sensing capabilities and a set of intelligent objects. This system provides direct interaction with collocation of visual and haptic workspaces and a rich multisensory feedback through a mixed reality environment for neurorehabilitation.

The primary aim of this study is to present the SITAR concept, the current realisation of the system, together with preliminary data demonstrating the SITAR’s capabilities for UL assessment and training. The following section introduces the SITAR concept, providing the motivation and rationale for its design and specifications. Subsequently, we describe the current realisation of the SITAR, its different components and their capabilities. Finally, preliminary data from two pilot clinical studies are presented, which demonstrate the SITAR’s functionalities for ToT and assessment of the UL. […]

Continue —> SITAR: a system for independent task-oriented assessment and rehabilitation Journal of Rehabilitation and Assistive Technologies Engineering – Asif Hussain, Sivakumar Balasubramanian, Nick Roach, Julius Klein, Nathanael Jarrassé, Michael Mace, Ann David, Sarah Guy, Etienne Burdet, 2017

Figure 1. The SITAR concept with (a) the interactive table-top alongside some examples of intelligent objects developed including (b) iJar to train bimanual control, (c) iPen for drawing, and (d) iBox for manipulation and pick-and-place.

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[WEB SITE] Is Clinical Virtual Reality the Future of Therapy?

Image courtesy of Pixabay.

As the meteors came down from the sky, my heart thudded in my chest. There was only one way I could save the town below: Reach out into the air, make a fist, and in doing so, set off an explosion. And then another. And another. How else can one be expected to defend a village?

This was the task given to me by Alex Miller, a computer scientist creating virtual realities for the neurology department at the University of Pennsylvania. Under the guidance of Dr. Branch Coslett, Miller’s lab is making programs for stroke victims trying to regain the use of a limb, amputees trying to lose phantom limb pain, and other people with mysterious, hard-to-heal conditions of the body and brain.

Missile Command. Image courtesy of Alex Miller, University of Pennsylvania.

But in the meantime, I’m strapped into an Oculus Rift VR headset, with a Leap Motion tracking system attached to the front of it. The Leap Motion is, well, magical: it scans the area in front of it, registers where my hands are, and then projects those hands into the game. The experience is profoundly immersive: when I move my head left or right, the view in the game moves accordingly, and if I open my hand or close my wrist, the same happens in-game, in real-time. There are many possible medical applications: the game is recording all of my movements, creating what would be a hyper-detailed tracking of rehab progress over time, and if Miller so chose, my in-game left hand could be a representation of my real-life right hand—a fun trick for an able-bodied person, but if I had lost my left hand, my brain seeing an intact left hand in game could actually ease phantom limb pain.

Just a few minutes earlier, Miller was strapping sensors to my thighs and knees. I’m in yet another world, and with my virtual feet underneath me. I’m on a platform in a desert, it’s twilight, and I have a puzzle to solve: make it from my spawning point to a glowing goal across the way. There are any number of pits I need to avoid falling into, and in classic game fashion, the solution is to push crates into them. Seated in my chair, I make a slow, dragging step to move forward, and sweep my foot left or right to turn. The sensors strapped to me are set up so that if you had lost your leg below—or above—the knee, the electronic signals sent by the muscles would be detected, and you’d make those same movements in the game. So even for a body that is injured in real life, it can be intact in the game, and neurologically speaking, it doesn’t make that much of a difference.

“That’s the killer use case of virtual reality,” Miller explains. The brain is surprisingly easy to fool, and it will believe that the hands and feet in a game are your own, with potentially huge medical consequences. “It’s really about illusion,” he says: you manipulate what a patient sees in their virtual self and their virtual world, and their brains will literally incorporate these things into the body image. While still early, results indicate that using the Penn neurology games does indeed reduce the intensity of phantom limb pain.

Kicking around virtual boxes. Image courtesy of Alex Miller, University of Pennsylvania.

The idea of virtual reality has been around for decades. The French dramatist Antonin Artaud coined “la realite virtuelle” in 1938 to describe the temporary world created by theatre. The 1960s saw the Sensorama, an arcade cabinet that played 3D movies along with stereo sound, wind and smells on head-mounted displays. Movies like TronThe Lawnmower Man and The Matrix all help make VR a household term. And the 1990s saw a boom in VR arcades, with game console manufacturers making early bids, too—shoutout to Nintendo’s Virtual Boy. The first examples of medical VR started showing up then, too—like a demo of gastrointestinal surgery. But, according to many researchers Thrive Global spoke to, we’ve entered a new era of VR in just the past few years.

With the Oculus, the HTC Vive, and other VR setups becoming available, the price of setting up a VR lab has cratered: Betty Mohler, a researcher at the Max Planck Institute for Biological Cybernetics, tells Thrive Global the cost has fallen a hundredfold. And it’s getting even cheaper, as low-cost options like the Google Daydream start rolling out. “With affordable, high-quality virtual reality devices hitting the market for the first time, the future seems suddenly imminent,” Oxford psychiatrist and VR specialist Daniel Freeman tells Thrive Global. “VR could become the method of choice for psychological treatment — out with the couch, on with the headset.”

It’s a potential that the investors have seen, most famously with Facebook’s $3 billionpurchase of Oculus in 2014. More recently, with the growing hype surrounding MindMaze, a VR startup out of Switzerland with a valuation already north of $1 billion. The company’s stroke rehab treatments were introduced into European hospitals in 2013, and the company announced entry into the US market this year. Since VR is so stimulating, patients are more likely to do their rehab, and according to one company report, a full 100 percent of patients forgot they were in the hospital while doing their VR rehab.

VR is simultaneously neurological and psychological: it has applications with disorders of the body, like phantom limb pain, and conditions of the mind, like PTSD, anxiety, and paranoia. Unlike any other technology before it, VR gives the user a direct sense of embodiment, what University of Barcelona pioneer Mel Slater refers to as “presence.” It’s not just another medium in a long line of media: virtual reality directly accesses people’s sense of self—these hands are mine, my own brain thought, as I pawed at the meteors. Rather than flatly watching, you’re immersed in the virtual world.

The thing about conventional “talk” therapy is that all the therapist and the client can really do is remember and imagine: you might get tips about how to keep your family from driving you crazy the next time Thanksgiving rolls around, but your shrink can’t place you at the dinner table. That all changes with virtual reality: with the right software, a therapist can put you in the places you have come to fear the most. People with arachnophobia get anxious around spiders, those with paranoia are afraid of social situations, and people with PTSD get triggered by cues linked to their trauma.

“Difficulties interacting in the world are at the heart of mental health issues,” Freeman, the Oxford psychiatrist, explains. With VR, you can repeatedly experience those feared situations—at a just-tolerable dose—and learn to overcome them. “The beauty of VR is that individuals know that a computer environment is not real, but their minds and bodies behave as if it is real,” he adds, which allows people to more easily face fearful situations, and then experiment with how to approach them. “This learning then transfers to the real world,” he says.

His lab has done lots of research around paranoia, a condition that affects around 1 or 2 percent of the population. In a 2016 paper in the British Journal of Psychiatry, Freeman and his team dropped people with paranoia into public situations, like standing in an elevator or commuting on a subway car. The subjects wore headsets and could walk around a room, rather than using a controller. Every time the patient entered one of these levels, they’d encounter more people in that space. After doing just 30 minutes of VR, about half of the patients no longer felt severe paranoia at the end of their testing day, and when they went into real social situations, they felt less distressed.[…]

Visit site —> Is Clinical Virtual Reality the Future of Therapy? | Thrive Global

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[Abstract+References] XOOM: An End-User Development Tool for Web-Based Wearable Immersive Virtual Tours

Abstract

XOOM is a novel interactive tool that allows non ICT-specialists to create web-based applications of Wearable Immersive Virtual Reality (WIVR) technology that use 360° realistic videos as interactive virtual tours. These applications are interesting for various domains that range from gaming, entertainment, cultural heritage, and tourism to education, professional training, therapy and rehabilitation. 360° interactive videos are displayed on smart-phones placed on head-mounted VR viewers. Users explore the virtual environment and interact with active elements through head direction and movements. The virtual scenarios can be seen also on external displays (e.g., TV monitors or projections) to enable other users to participate in the experience, and to control the VR space if needed, e.g., for education, training or therapy purposes. XOOM provides the functionality to create applications of this kind, import 360° videos, concatenate them, and superimpose active elements on the virtual scenes, so that the resulting environment is more interactive and is customized to the requirement of a specific domain and user target. XOOM also supports automatic data gathering and visualizations (e.g., through heat-maps) of the users’ experience, which can be inspected for analytics purposes, as well as for user evaluation (e.g., in education, training, or therapy contexts). The paper describes the design and implementation of XOOM, and reports a case study in the therapeutic context.

Source: XOOM: An End-User Development Tool for Web-Based Wearable Immersive Virtual Tours | SpringerLink

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[ARTICLE] Stroke research at the crossroads – where are we heading? – Full Text HTML

Summary

Stroke causes 5.7 million deaths annually. This ranks stroke as the second most common cause of death and, additionally, it is a major cause of disability. Because of an ageing population, stroke incidence and costs will greatly increase in the future. This makes stroke an ongoing social and economic burden, in contrast to the only very limited therapeutic options.

In the last decade vast sums were spent on translational research focused on neuroprotective strategies in the acute phase of ischaemic stroke. A plethora of candidate agents were tested in experimental models and preclinical studies, but none was proven effective in clinical trials. This gave rise to discussions about the possible reasons for this failure, ending up mainly with criticism of methodological aspects of the preclinical and clinical studies, or of the relevance of animal studies in drug development. Indeed, the question could rather be whether neuroprotection is the right target for successful stroke treatment. In this context, a paradigm change can currently be observed: the focus of experimental and translational stroke research is shifting from early neuroprotection to delayed mechanisms such as stroke-associated comorbidities, regeneration and plasticity.

In this review we highlight a few recently emerging fields in translational stroke research. One such topic is the crosstalk between immunity and the injured brain as key pathomechanism in stroke. On one hand, innate and adaptive immune cells play an important role in the fate of injured brain tissue after stroke; on the other, peripheral immune alterations are critically involved in post-stroke comorbidities.

Another emerging research area is the analysis of mechanisms involved in regeneration and neuronal plasticity after stroke. Here, we discuss the current understanding of basic mechanisms involved after brain injury, clinical imaging approaches and therapeutic strategies to promote regeneration in stroke patients.

Continue —> SMW – Swiss Medical Weekly – Stroke research at the crossroads – where are we heading?

Figure 1 Multiphasic brain interactions after stroke and opportunities for treatment. Previous neuroprotective strategies targeted pathological mechanisms in a very narrow window of opportunity in the (hyper-) acute phase after stroke (orange). Recently, the focus of translational stroke research has shifted towards understanding pathological processes in the subacute and chronic phase such as neuroinflammation and neuroregeneration (green). These targets have the potential for novel therapeutic approaches which are suitable for a larger population of stroke patients then neuroprotective agents or thrombolysis.

 

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[Abstract] General Concepts: Therapies for Rehabilitation and Recovery

Abstract

Stroke rehabilitation is critical to dealing with a growing burden of stroke-related disability. The most important prognostic factors predicting stroke recovery are stroke severity, age of the stroke survivor, and access to rehabilitation. Neuroplasticity with associated neurological recovery is an important concept which emphasizes the importance of stroke rehabilitation. Optimal rehabilitation outcomes are reported when rehabilitation takes place in specialized interdisciplinary stroke rehabilitation units, when rehab is initiated early and when therapy is of sufficient intensity. Outpatient rehabilitation therapy has been shown to further improve outcomes. In the future, stroke rehabilitation outcomes will improve even further through better adherence to clinical practice guidelines and the increasing use of new technologies. There is a developing evidence base supporting long-term rehabilitation management of stroke, a concept which in the past has received little in the way of resources or attention.

Source: General Concepts: Therapies for Rehabilitation and Recovery – Springer

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