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[ARTICLE] Compliant lower limb exoskeletons: a comprehensive review on mechanical design principles – Full Text

Abstract

Exoskeleton technology has made significant advances during the last decade, resulting in a considerable variety of solutions for gait assistance and rehabilitation. The mechanical design of these devices is a crucial aspect that affects the efficiency and effectiveness of their interaction with the user. Recent developments have pointed towards compliant mechanisms and structures, due to their promising potential in terms of adaptability, safety, efficiency, and comfort. However, there still remain challenges to be solved before compliant lower limb exoskeletons can be deployed in real scenarios. In this review, we analysed 52 lower limb wearable exoskeletons, focusing on three main aspects of compliance: actuation, structure, and interface attachment components. We highlighted the drawbacks and advantages of the different solutions, and suggested a number of promising research lines. We also created and made available a set of data sheets that contain the technical characteristics of the reviewed devices, with the aim of providing researchers and end-users with an updated overview on the existing solutions.

Background

Robotic wearable exoskeletons1 have potential impact in several application domains, like industry [1], space [2] and healthcare [3]. In the healthcare sector, this technology is expected to contribute by reducing the clinical costs associated with the assistance and rehabilitation of people with neurological and age-related disorders [3456]. Research in this area is clearly shifting toward the inclusion of compliant elements (i.e. actuators, structure2, etc.) as a way to overcome the main drawbacks of rigid exoskeletons, in terms of adaptability, comfort, safety and efficiency [7].

Currently, there is a large variety of designs of lower limb compliant exoskeletons aimed at gait rehabilitation or assistance. However, there is a lack of detailed information about the mechanical components of these devices, which has been largely overlooked by previous reviews (e.g. [789]). These variety and lack of information makes it difficult for developers to identify which design choices are most important for a specific application, user’s need or pathology. For this reason, we aimed to bring together available literature into a comprehensive review focused on existing lower limb wearable exoskeletons that contain compliant elements in their design.

In this work, we refer to ‘compliant exoskeleton’ as a system that includes compliant properties derived from non-rigid actuation system and/or structure. Our review focused on three particular aspects: the actuation technology, the structure of the exoskeleton and the interface attachment components3.

We have gathered the mechanical and actuation characteristics of 52 devices into standardized data sheets (available at Additional file 1), to facilitate the process of comparison of the different solutions under a unified and homogeneous perspective. We consider that such a comprehensive summary will be vital to researchers and developers in search for an updated design reference.

Methodology

We applied the following search query on the Scopus database: TITLE-ABS-KEY(“actuat*” AND (“complian*” OR “elastic*” OR “soft”) AND (“exoskeleton*” OR “rehabilitat*” OR “orthotic*” OR “orthos*” OR (“wearable” AND “robot*”)) OR “exosuit” OR “exo-suit”), which returned 1131 studies. We excluded: publications focusing on upper limb robots; non-actuated compliant exoskeletons; solutions where compliance was achieved through control; studies that did not report any mechanical information on the robot; and studies not related to either assistance or rehabilitation. The above process resulted in a total of 105 publications, which covered 52 different lower limb exoskeletons.

To simplify and structure the information, we classified the compliant exoskeletons according to the mechanical component that results in their intrinsic compliant performance: (i) exoskeletons with compliant actuators (i.e. series elastic, variable stiffness and pneumatic actuators) and rigid structure; (ii) exoskeletons with soft structure (soft exoskeletons4) and rigid actuators; (iii) exoskeletons with compliant actuators and soft structure. The review describes the different design choices of the exoskeletons, i.e. actuation system, structure and interfacing attachment components to connect the actuators with the human body.

A glossary with the most commonly used terms in this article has been added at the end of the document. Some definitions have been readapted from the literature.

Results

As shown in Fig. 1, 85% of the reviewed articles (corresponding to 44 exoskeletons) used compliant actuators and a rigid structure. Soft exoskeletons represent 11% of the reviewed articles (6 exoskeletons). Two exoskeletons (4%) belong to the intersection of previous groups, this is, exoskeletons integrating both soft structure and compliant actuation5. We refer to the latter as “fully compliant exoskeletons”.

Fig. 1
Fig. 1

Classification of the 52 lower limb exoskeletons according to their compliant mechanical component

 

Continue —>  Compliant lower limb exoskeletons: a comprehensive review on mechanical design principles | Journal of NeuroEngineering and Rehabilitation | Full Text

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[NEWS] Anti-Tremor Function is One of this Mouse Adapter’s Cool Features

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AMAneo BTi

Inclusive Technology releases the AMAneo BTi, an adapter designed to enable people with disabilities to operate an iPad or iPhone directly with any mouse or assistive mouse, including track ball, joystick, head mouse, thumb mouse, and more.

Previously, the most common iPad or iPhone operation method was using Switch Control of the iOS.

However, to use this adapter, simply plug in the mouse and connect it to the iPhone, iPad, or iPad Mini using Bluetooth. A touch pointer then automatically appears on the device’s screen enabling full control over the iPad. There are no additional apps to install, according to a media release from UK-based Inclusive Technology. Its US distributor is located in Waxhaw, NC.

Other interaction options include click and drag, auto click and click delay. Two switch ports are also provided, enabling the option of controlling the left and right mouse button with two external switches.

Additional features include instant access to Apple’s AssistiveTouch Menu, which gives users access to several iPad controls such as volume control and the Home button, as well as an innovative anti-tremor function to filter out any shaking of the hand or head and ensure that the on-screen cursor moves smoothly, according to a media release.

The AMAneo BTi charges using a Micro USB and lasts for up to 20 hours of operation.

[Source: Inclusive Technology]

 

via Anti-Tremor Function is One of this Mouse Adapter’s Cool Features – Rehab Managment

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[ARTICLE] Diffusion Tensor Imaging Biomarkers to Predict Motor Outcomes in Stroke: A Narrative Review – Full Text

Stroke is a leading cause of disability worldwide. Motor impairments occur in most of the patients with stroke in the acute phase and contribute substantially to disability. Diffusion tensor imaging (DTI) biomarkers such as fractional anisotropy (FA) measured at an early phase after stroke have emerged as potential predictors of motor recovery. In this narrative review, we: (1) review key concepts of diffusion MRI (dMRI); (2) present an overview of state-of-art methodological aspects of data collection, analysis and reporting; and (3) critically review challenges of DTI in stroke as well as results of studies that investigated the correlation between DTI metrics within the corticospinal tract and motor outcomes at different stages after stroke. We reviewed studies published between January, 2008 and December, 2018, that reported correlations between DTI metrics collected within the first 24 h (hyperacute), 2–7 days (acute), and >7–90 days (early subacute) after stroke. Nineteen studies were included. Our review shows that there is no consensus about gold standards for DTI data collection or processing. We found great methodological differences across studies that evaluated DTI metrics within the corticospinal tract. Despite heterogeneity in stroke lesions and analysis approaches, the majority of studies reported significant correlations between DTI biomarkers and motor impairments. It remains to be determined whether DTI results could enhance the predictive value of motor disability models based on clinical and neurophysiological variables.

Introduction

Stroke is the second cause of death and the third leading cause of loss of DALYs (Disability-Adjusted Life Years) worldwide. Despite substantial advances in prevention and treatment, the global burden of this condition remains massive (1). In ischemic stroke (IS; 80–85% of the cases), hypoperfusion leads to cell death and tissue loss while in hemorrhagic stroke (HS), primary injury derives from hematoma formation and secondary injury, from a cascade of events resulting in edema and cellular death (2). In IS, cytotoxic edema is a result of glucose and oxygen deprivation, leading to a failure of ion pumps in the cell membranes and consequently to collapse of osmotic regulation, when water shifts from the extracellular to the intracellular compartment (3). In HS, heme degradation products are the primary cytotoxic event and secondarily, an inflammatory process based on degradation of the hematoma takes place (4).

Diffusion MRI (dMRI) is a powerful diagnostic tool in acute IS (5) and is widely used in clinical practice (6). dMRI sequences are sensitive to water displacement. Acute infarcts appear hyperintense on diffusion-weighted imaging (DWI) reflecting the decrease in the apparent diffusion coefficient of water molecules. DWI can be acquired and interpreted over a few minutes. It provides key information for eligibility to reperfusion therapies from 6 to 24 h after onset of symptoms (DAWN study) (7) and in wake-up strokes (8). A search on MEDLINE using the terms “stroke” and “diffusion MRI” yielded 1 article in 1991 and 279, in 2018. Diffusion tensor imaging (DTI) involves more complex post-processing, mathematical modeling of the DW signal (9) and provides measures associated with white matter (WM) microstructural properties (10).

Stroke can directly injure WM tracts and also lead to Wallerian degeneration, the anterograde distal degeneration of injured axons accompanied by demyelination (11). DTI metrics have been studied as biomarkers of recovery or responsiveness to rehabilitation interventions (1214). The bulk of DTI studies addressed specifically the corticospinal tract (CST), crucial for motor performance or recovery (1215), and frequently affected by stroke lesions. Paresis occurs in the majority of the subjects in the acute phase and contributes substantially to disability (16). It is thus understandable that the CST is in the spotlight of research in the field.

Two meta-analyses included from six to eight studies and reported strong correlations between DTI metrics and upper-limb motor recovery in IS and HS (1718). In both meta-analyses, heterogeneity between the studies was moderate. In addition, the quality of the evidence of DTI as a predictor of motor recovery was considered only moderate by a systematic review of potential biomarkers (19). The main limitations of the reviewed studies were the lack of cross-validation and evaluation of minimal clinically important differences for motor outcomes as well as the small sample sizes. Heterogeneity in DTI data collection and analysis strategies may also contribute to inconsistencies and hinder comparisons between studies.

In this narrative review, first we review the key concepts of dMRI. Second, we present an overview of state-of-art methodological practices in DTI processing. Third, we critically review challenges of DTI in stroke and results of studies that investigated the correlation between DTI metrics in the CST and motor outcomes at different stages after stroke, according to recommendations of the Stroke Recovery and Rehabilitation Roundtable taskforce (20).

Concepts of Diffusion MRI

Different MRI paradigms address WM qualitatively and quantitatively (i.e., volume, contrast as signal hyperintensities), but only dMRI allows indirect inferences about WM microstructure by providing information about the underlying organization of the tissue. In regions of little restriction of water displacement (such as the ventricles), water molecules tend to move almost freely (randomly). On the other hand, within tracts, the environment tends to be organized within sets of axons aligned in parallel orientation. Water movement usually follows a specific orientation near axons compactly organized and constrained by the myelin packing (21).

The diffusion tensor is the most commonly used mathematical modeling of the diffusion signal and can be decomposed into its eigenvalues (λ) and eigenvectors (ε), required to characterize the signal of water displacement within a voxel. Each eigenvector represents an axis of dominant diffusion with the magnitude of diffusion determined by the corresponding eigenvalues. If the diffusion is isotropic (the same along each orientation), then the eigenvalues have approximately the same magnitude (λ1 ≈ λ2 ≈ λ3), which can be depicted by a sphere. By contrast, if there is a preferential orientation of the diffusion, then the first eigenvalue is bigger than the other two, which can be visualized typically by an ellipsoid (λ1 >> λ2, λ3) (Figure 1).

FIGURE 1

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Figure 1. Model of the tensor showing the eingenvalues. Diffusivities are depicted in FA representation (λll—parallel or axial diffusivity—AD, λperpendicular or radial diffusivity—RD).

Hence, the tensor calculation is typically based on a 3 × 3 symmetric matrix, in which the eigenvalues derived from each combination of directions provide different metrics. At least one b0 (non-diffusion-weighted) and 6 non-collinear directions of diffusion-weighted acquisitions are required to minimally describe water displacement with DTI (10). Generally, the more directions, the better.

The most widely used DTI metrics are: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). FA describes the degree of anisotropy (represented as an ellipsoid), a value between 0 (isotropic) and 1 (the most anisotropic). Anisotropy tends to increase in the presence of highly oriented fibers (Figure 1). The biggest value is supposed to be found in the center of the tracts. In particular, for CST analysis in stroke or other focal brain lesions, FA results can be reported as ratios between FA extracted from the ipsilesional and the contralesional hemispheres (rFA = FA ipsilesional/FA contralesional). Alternatively, asymmetry in FA can be described (aFA = (FA ipsilesional – FA contralesional)/(FA ipsilesional + FA contralesional).

MD describes the magnitude of diffusion and the biggest value is supposed to be found in the ventricles. RD represents the average diffusivity perpendicular to the first eigenvector and AD is the first eigenvalue (λ1) representing the diffusivity along the dominant diffusion direction.

Many studies have focused exclusively on FA. The proper interpretation of FA often demands knowledge about results of the other three DTI metrics (22). Changes in anisotropy may reflect several biological underpinnings, such as axonal packing density, axonal diameter, myelinization, neurite density, and orientation distribution (2123). FA can be decreased in conditions that injure the WM but also when multiple crossing fibers are present in the voxel. In case of partial volume effects, both FA and MD may be altered (2425).[…]

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https://www.frontiersin.org/articles/10.3389/fneur.2019.00445/full

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[WEB SITE] Formula 1 Creates World’s Lightest Wheelchair

When we talk about traveling with a wheelchair, the most important thing that comes to mind is the space and weight of the wheelchair.

Keeping this in mind, a Swiss company has recently partnered with Formula One, a renowned race car organization.

The co-venture will be creating the world’s lightest wheelchair. Küschall, the wheelchair manufacturing company, is focusing on utilizing aerospace materials and redefining the rules of creating a wheelchair, and working with Formula 1 will help them ensure an ultimate driving experience.

The superstar wheelchair, created by the project leader and industrial designer Küschall Andre Fangueiro, is expected to weigh only 1.5 kg. It happens to be 30% lighter and 20% more powerful compared to wheelchairs used normally (classic carbon models). 

Considering graphene is 200 times more powerful and stronger than steel, the chair is built using the same material. The material is also known to be 10 times tougher than a diamond. However, the seat is super flexible and light in weight, which is amazing.

The bound is made up of hexagonal lattice and it is a single layer of carbon atoms.

The company released a press release and noted, “Superb power transfer through the entire frame will mean the Superstar responds rapidly with every movement, combined with impressive road dampening properties, the Superstar will provide an effortless glide anywhere you go,” – Kval.com

The X shape of the geometry will result in the performance boost. As of now, the details of release date, production, and cost of the product haven’t revealed, but we are excited about this new concept combat design where users can utilize its high performance and comfort.

We will keep you updated for upcoming announcements on the same.

Image credit: https://kval.com/news/offbeat/design-company-teams-up-with-formula-1-to-create-worlds-lightest-wheelchair

More about formula, one, wheelchair, superstar

Formula 1 Creates World’s Lightest Wheelchair – Rolling Without Limits: Your mobility may be limited. Your voice, boundless.

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[REVIEW ARTICLE] Blood Biomarkers for Traumatic Brain Injury: A Quantitative Assessment of Diagnostic and Prognostic Accuracy – Full Text

Blood biomarkers have been explored for their potential to provide objective measures in the assessment of traumatic brain injury (TBI). However, it is not clear which biomarkers are best for diagnosis and prognosis in different severities of TBI. Here, we compare existing studies on the discriminative abilities of serum biomarkers for four commonly studied clinical situations: detecting concussion, predicting intracranial damage after mild TBI (mTBI), predicting delayed recovery after mTBI, and predicting adverse outcome after severe TBI (sTBI). We conducted a literature search of publications on biomarkers in TBI published up until July 2018. Operating characteristics were pooled for each biomarker for comparison. For detecting concussion, 4 biomarker panels and creatine kinase B type had excellent discriminative ability. For detecting intracranial injury and the need for a head CT scan after mTBI, 2 biomarker panels, and hyperphosphorylated tau had excellent operating characteristics. For predicting delayed recovery after mTBI, top candidates included calpain-derived αII-spectrin N-terminal fragment, tau A, neurofilament light, and ghrelin. For predicting adverse outcome following sTBI, no biomarker had excellent performance, but several had good performance, including markers of coagulation and inflammation, structural proteins in the brain, and proteins involved in homeostasis. The highest-performing biomarkers in each of these categories may provide insight into the pathophysiologies underlying mild and severe TBI. With further study, these biomarkers have the potential to be used alongside clinical and radiological data to improve TBI diagnostics, prognostics, and evidence-based medical management.

Introduction

Traumatic brain injury (TBI) is a common cause of disability and mortality in the US (1) and worldwide (2). Pathological responses to TBI in the CNS include structural and metabolic changes, as well as excitotoxicity, neuroinflammation, and cell death (34). Fluid biomarkers that may track these injury and inflammatory processes have been explored for their potential to provide objective measures in TBI assessment. However, at present there are limited clinical guidelines available regarding the use of biomarkers in both the diagnosis of TBI and outcome prediction following TBI. To inform future guideline formulation, it is critical to distinguish between different clinical situations for biomarker use in TBI, such as detection of concussion, prediction of positive and negative head computed tomography (CT) findings, and prediction of outcome for different TBI severities. This allows for comparisons to determine which biomarkers may be used most appropriately to characterize different aspects of TBI.

The identification of TBI severity has become a contentious issue. Currently, inclusion in TBI clinical trials is primarily based on the Glasgow Coma Scale (GCS), which stratifies patients into categories of mild, moderate, and severe TBI. The GCS assesses consciousness and provides prognostic information, but it does not inform the underlying pathologies that may be targeted for therapy (56). Furthermore, brain damage and persistent neurological symptoms can occur across the spectrum of TBI severity, limiting the use of GCS-determined injury severity to inform clinical management. Biomarkers in TBI have the potential to provide objective and quantitative information regarding the pathophysiologic mechanisms underlying observed neurological deficits. Such information may be more appropriate for guiding management than initial assessments of severity alone. Since the existing literature primarily focuses on applications of biomarkers in either suspected concussion, mild TBI (mTBI), or severe TBI (sTBI), we will discuss biomarker usage in these contexts.

Concussion is a clinical syndrome involving alteration in mental function induced by head rotational acceleration. This may be due to direct impact or unrestrained rapid head movements, such as in automotive crashes. Although there are over 30 official definitions of concussion, none include the underlying pathology. Missing from the literature have been objective measures to not only identify the underlying pathology associated with the given clinical symptoms, but also to indicate prognosis in long-term survival. Indeed, current practices in forming an opinion of concussion involve symptom reports, neurocognitive testing, and balance testing, all of which have elements of subjectivity and questionable reliability (7). While such information generally reflects functional status, it does not identify any underlying processes that may have prognostic or therapeutic consequences. Furthermore, because patients with concussion typically present with negative head CT findings, there is a potential role for blood-based biomarkers to provide objective information regarding the presence of concussion, based on an underlying pathology. This information could inform management decisions regarding resumption of activities for both athletes and non-athletes alike.

Blood-based biomarkers have utility far beyond a simple detection of concussion by elucidating specific aspects of the injury that could drive individual patient management. For example, biomarkers may aid in determining whether a mTBI patient presenting to the emergency department requires a CT scan to identify intracranial pathology. The clinical outcome for a missed epidural hematoma in which the patient is either discharged or admitted for routine observation is catastrophic; 25% are left severely impaired or dead (8). The Canadian CT Head Rule (9) and related clinical decision instruments achieve high sensitivities in predicting the need for CT scans in mild TBI cases. However, they do this at specificities of only 30–50% (10). Adding a blood biomarker to clinical evaluation may be useful to improve specificity without sacrificing sensitivity, as recently suggested (11). In addition, given concern about radiation exposure from head CT scans in concussion cases, particularly in pediatric populations, identification of patients who would be best assessed with neuroimaging is crucial. Thus, the use of both sensitive and specific biomarkers may serve as cost-effective tools to aid in acute assessment, especially in the absence of risk factors for intracranial injury (12). S-100B, an astroglial protein, has been the most extensively studied biomarker for TBI thus far and has been incorporated into some clinical guidelines for CT scans (1314). However, S-100B is not CNS-specific (1516) and has shown inconsistent predictive capacity in the outcome of mild TBI (1718). Given that several other promising biomarkers have also been investigated in this context, it is important to evaluate and compare the discriminative abilities of S-100B with other candidate blood-based biomarkers for future use.

Blood biomarkers also have the potential to help predict unfavorable outcomes across the spectrum of TBI severity. Outcome predication is difficult; in mTBI, existing prognostic models performed poorly in an external validation study (19). Identifying biomarkers that best predict delayed recovery or persistent neurological symptoms following mTBI would help with the direction of resources toward patients who may benefit most from additional rehabilitation or prolonged observation. In sTBI, poorer outcome has often been associated with a low GCS score (20). However, factors such as intoxication or endotracheal intubation may make it difficult to assess GCS reliably in the acute setting (2122). The addition of laboratory parameters to head CT and admission characteristics have improved prognostic models (23). Thus, prognostic biomarkers in sTBI could help determine whether patients are likely to benefit from intensive treatment. Several candidate biomarkers that correlate with various pathologies of mild and severe TBI have been studied (24), but their relative prognostic abilities remain unclear.

Existing reviews on biomarkers in TBI have provided valuable insight into the pathologic correlates of biomarkers, as well as how biomarkers may be used for diagnosis and prognosis (2531). However, there has been no previous quantitative comparison of the literature regarding biomarkers’ discriminative abilities in specific clinical situations. Here, we compare existing studies on the discriminative abilities of serum biomarkers for four commonly studied clinical situations: detecting concussion, predicting intracranial damage after mTBI, predicting delayed recovery after mTBI, and predicting adverse outcome after sTBI.[…]

 

Continue —-> Frontiers | Blood Biomarkers for Traumatic Brain Injury: A Quantitative Assessment of Diagnostic and Prognostic Accuracy | Neurology

Figure 2. Anatomical locations of potential TBI biomarkers. The biomarkers included in this schematic all rated as “good” (AUC=0.800.89) or better for any of the four clinical situations studied (detecting concussion, predicting intracranial damage after concussion, predicting delayed recovery after concussion, and predicting adverse outcome after severe TBI). Biomarkers with a pooled AUC <0.8 are not shown. 1Also found in adipose tissue; 2synthesized in cells of stomach and pancreas; may regulate HPA axis; 3found mostly in pons; 4also found extracellularly; 5lectin pathway of the complement system; 6also found in endothelial cells. BBB, blood brain barrier. ECM, Extracellular matrix. Image licensed under Creative Commons Attribution-ShareAlike 4.0 International license. https://creativecommons.org/licenses/by-sa/4.0/deed.en. See Supplementary Material for image credits and licensing.

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[WEB PAGE] When Will There Ever be a Cure for Epilepsy?

The three-pound organ that serves as command central for the human organism is certainly a marvel, just by virtue of the fact that the brain can appreciate its own awesomeness, even if it hasn’t quite perfected the flying car or even self-driving cars. Yet. Companies developing brain-computer interface technology are enabling humans to do things like send commands to computers by just flexing a bit of muscle. Still, there is much we don’t know about ourselves, no matter how much telepsychiatry we do. And that applies especially to medical conditions that affect the brain like epilepsy, a neurological condition for which there is no cure.

What is Epilepsy?

While most of us are probably familiar with some Hollywood-ized version of epilepsy in which someone starts flailing around after being hit by strobe lights on the disco floor, the reality is that epilepsy refers to a large group of neurological disorders that generally involve chronic, spontaneous seizures that vary greatly in how they manifest. The causes of epilepsy are also all over the place, from traumatic brain injuries and stroke to viral and bacterial infections to genetics.

A new set of classifications for epilepsy came out in 2017.

It is considered a brain disorder, according to the U.S. Centers for Disease Control (CDC), though some researchers have suggested it could be classified as a neurodegenerative disease like Parkinson’s or Alzheimer’s. In fact, there is research that suggests a genetic link between epilepsy and neurodegenerative diseases.

Not surprisingly, many of the companies developing therapies for neurodegenerative diseases are also working on treatments for epilepsy and vice versa. For example, a new, well-funded joint venture involving Pfizer (PFE) and Bain Capital called Cerevel, which we profiled in our piece on Parkinson’s disease, is also in advanced clinical trials for an epileptic drug. Its GABA A positive modulator drug candidate targets GABA (Gamma-Aminobutyric Acid) neurotransmitters that block impulses between nerve cells in the brain, helping keep the nervous system chill.

Impacts of Epilepsy

More than 50 million people worldwide have epilepsy, making it one of the most common neurological diseases globally, according to the World Health Organization (WHO). The CDC estimates about 3.4 million Americans live with the condition. Globally, an estimated 2.4 million people are diagnosed with epilepsy each year. Interestingly, the disorder seems to target those who can least afford it: WHO said nearly 80% of people with epilepsy live in low- and middle-income countries.

Impacts of epilepsy graphic

A 2015 study of a bunch of other studies that estimated the cost of epilepsy in the United States found that epilepsy-specific costs probably average out to about $10,000 based on the variety of ranges, which means epilepsy costs the United States healthcare system about $34 billion, though the numbers are widely debated. Conversely, WHO says low-cost treatments are available, with daily medication coming as cheaply as $5 per year, so another win for the U.S. healthcare system.

Treatments for Epilepsy

There are more than 20 antiepileptic drugs used to treat epilepsy, usually to help prevent or slow the occurrence of seizures. Other therapies include surgery and electroceutical treatment in which electrical stimulation is applied, usually to the vagus nerve, the longest cranial nerve in the body. While many find relief from one or more of these options, a third of those who suffer from epilepsy are not able to manage their seizures, according to the U.S. National Institutes of Health (NIH). Below we take a look at a range of innovative therapies designed to detect, stop, or find a cure for epilepsy.

Brain Stimulation Therapies

In our article on electroceutical treatments, we highlighted a London company called LivaNova (LIVN) that offers an implantable Vagus Nerve Stimulation (VNS) therapy that has been approved by the U.S. Food and Drug Administration (FDA) to help treat those with partial seizures who do not respond to seizure medications. A medical device company with a lengthy track record of returning value to investors, Medtronic (MDT) got FDA pre-market approval last year for its Deep Brain Stimulation (DBS) therapy for use in reducing partial-onset seizure for those who have proven to not respond to three or more antiepileptic medications. DBS therapy delivers controlled electrical pulses to an area in the brain called the anterior nucleus of the thalamus, which is part of a network involved in seizures. Yet another company offering a variation of brain stimulation therapy is NeuroPace, which markets its responsive neurostimulation device, or RNS system, as “the first and only brain-responsive neurostimulation system designed to prevent epileptic seizures at their source.”

Artificial Intelligence to Detect, Predict, and Control Epilepsy

The NIH is funding further research into implantable devices that can detect, predict, and stop a seizure before it happens, “working closely with industry partners to develop pattern-recognition algorithms,” which sounds an awful lot like artificial intelligence and machine learning will be at the forefront of some future diagnostics and treatment. AI in healthcare has been an ongoing theme around here, with a recent dive into AI and mental health. Back to AI and epilepsy: A group of neurologists at the Medical University of South Carolina developed a new method based on artificial intelligence to predict which patients will see success with surgical procedures designed to stop seizures. Sounds like a great idea to learn beforehand if it’s necessary to crack open your skull.

Click for company websiteA Boston area startup called Empatica, spun out from MIT in 2011, has raised $7.8 million for a smartwatch that detects possible seizures by monitoring subtle electrical changes across the surface of the skin. Other methods normally rely on electrical activity in the brain that tracks and records brain wave patterns called an electroencephalogram. Empatica’s seizure detection algorithm, on the other hand, can detect complex physiological patterns from electrodermal activity that is most likely to accompany a convulsive seizure. Psychology Today reportedthat the device, Embrace Watch, received FDA approval earlier this year for seizure control in children after getting the green light for the technology for adults in 2018.

The Empatica smartwatch can detect electrical currents in the skin to predict the onset of an epileptic seizure.

Click for company websiteAI and drug discovery for better epileptic drug candidates is yet another application that we would expect to see grow in the coming years. Silicon Valley-based startup System1 Biosciences raised $25 million last year, which included Pfizer among its dozen investors. System1 builds a sort of brain model for testing drug candidates using stem cell lines derived from patients with brain disease. The company uses robotic automation to develop these three-dimensional cerebral organoids, allowing it to generate huge datasets in a relatively short amount of time, then applying “advanced data analysis” (also AI?) to detect patterns that might match the characteristics of a neurological disease (what it refers to as deep phenotypes) such as epilepsy with novel treatments.

Cannabis for Controlling Seizures

We’ve written extensively about the suddenly booming hemp CBD market, noting that the FDA approved a CBD-based drug for epilepsy last year in our recent article on the best certified CBD oils on the market. However, we’ve only briefly profiled the company behind Epidiolex for treating rare forms of epilepsy, GW Pharmaceuticals (GWPH). Sporting a market cap just south of $5 billion, GW Pharmaceuticals has taken in about $300 million in post-IPO equity since our article, bringing total post-IPO equity funding to about $568 million. Aside from its successful epileptic drug, GW also developed the world’s first cannabis-based prescription medicine for the treatment of spasticity due to multiple sclerosis that is available in 25 countries outside the United States.

The forms of epilepsy that GW Pharmaceuticals can treat or can potentially treat.

Back on the epilepsy side, Epidiolex has been approved for two rare forms of epilepsy, with clinical trials underway for two more rare neurological disorders associated with seizures – tuberous sclerosis complex and Rett syndrome. Also in the pipeline is a drug dubbed CBDV (GWP42006) that’s also for treating epileptic seizures, though the results of a trial last year were not encouraging. The same compound is also being investigated for autism. Be sure to check out our article on Charlotte’s Web, a CBD company that came about because of epilepsy.

Helping Cells Get Their Vitamin K

Click for company websiteNeuroene Therapeutics is a small startup spun out of the Medical University of South Carolina that recently picked up $1.5 million in funding to tests its lead drug compounds, which are analogous to the naturally occurring form of vitamin K that is essential for brain health. In particular, the lab-developed vitamin K protects the integrity of the cell’s mitochondria, which serves as a sort of power plant for brain cells, helping the neural circuit fire better. Unfortunately, you can’t get the effect from simply eating a bowl of Special K each morning covered in an organic sugar substitute, so the company is developing a method to deliver the effects directly to the brain.

A Nasal Spray to Stop Seizures

Click for company websiteFounded in 2007 near San Diego, Neurelis licenses, develops, and commercializes treatments for epilepsy and other neurological diseases. It has raised $44.8 million in disclosed funding, most coming in a $40.5 million venture round last November. The company’s flagship product is called Valtoco, a formulation that incorporates diazepam, an existing drug used to control seizures and alcohol withdrawal, with a vitamin E-based solution that is delivered using a nasal spray when a sudden seizure episode occurs. The product uses an absorption enhancement technology called Intravail developed by another San Diego area company called Aegis Therapeutics that Neurelis acquired in December last year. Neurelis submitted Valtoco to the FDA for approval in September.

Conclusions

While many people with epileptic conditions can control their seizures with many of the current medications or other therapies available now, there’s a big chunk of the population that is living with uncertainty. Considering the strong link between neurological disorders like epilepsy and certain neurodegenerative disorders, expect to see some good synergies in the next five to 10 years, especially as automation and advanced analytics using AI start connecting the dots between genetics, biochemistry, and brain disorders.

via When Will There Ever be a Cure for Epilepsy? – Nanalyze

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[Abstract] Self-efficacy and Reach Performance in Individuals With Mild Motor Impairment Due to Stroke

Background: Persistent deficits in arm function are common after stroke. An improved understanding of the factors that contribute to the performance of skilled arm movements is needed. One such factor may be self-efficacy (SE).

Objective: To determine the level of SE for skilled, goal-directed reach actions in individuals with mild motor impairment after stroke and whether SE for reach performance correlated with actual reach performance.

Methods: A total of 20 individuals with chronic stroke (months poststroke: mean 58.1 ± 38.8) and mild motor impairment (upper-extremity Fugl-Meyer [FM] motor score: mean 53.2, range 39 to 66) and 6 age-matched controls reached to targets presented in 2 directions (ipsilateral, contralateral). Prior to each block (24 reach trials), individuals rated their confidence on reaching to targets accurately and quickly on a scale that ranged from 0 (not very confident) to 10 (very confident).

Results: Overall reach performance was slower and less accurate in the more-affected arm compared with both the less-affected arm and controls. SE for both reach speed and reach accuracy was lower for the more-affected arm compared with the less-affected arm. For reaches with the more-affected arm, SE for reach speed and age significantly predicted movement time to ipsilateral targets (R2 = 0.352), whereas SE for reach accuracy and FM motor score significantly predicted end point error to contralateral targets (R2 = 0.291).

Conclusions: SE relates to measures of reach control and may serve as a target for interventions to improve proximal arm control after stroke.

via Self-efficacy and Reach Performance in Individuals With Mild Motor Impairment Due to Stroke – Jill Campbell Stewart, Rebecca Lewthwaite, Janelle Rocktashel, Carolee J. Winstein, 2019

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[Abstract] Effectiveness of electrical stimulation therapy in improving arm function after stroke: a systematic review and a meta-analysis of randomised controlled trials

The aim of this study is to investigate the effectiveness of electrical stimulation in arm function recovery after stroke.

Data were obtained from the PubMed, Cochrane Library, Embase, and Scopus databases from their inception until 12 January 2019. Only randomized controlled trials (RCTs) reporting the effects of electrical stimulation on the recovery of arm function after stroke were selected.

Forty-eight RCTs with a total of 1712 patients were included in the analysis. The body function assessment, Upper-Extremity Fugl-Meyer Assessment, indicated more favorable outcomes in the electrical stimulation group than in the placebo group immediately after treatment (23 RCTs (n = 794): standard mean difference (SMD) = 0.67, 95% confidence interval (CI) = 0.51–0.84) and at follow-up (12 RCTs (n = 391): SMD = 0.66, 95% CI = 0.35–0.97). The activity assessment, Action Research Arm Test, revealed superior outcomes in the electrical stimulation group than those in the placebo group immediately after treatment (10 RCTs (n = 411): SMD = 0.70, 95% CI = 0.39–1.02) and at follow-up (8 RCTs (n = 289): SMD = 0.93, 95% CI = 0.34–1.52). Other activity assessments, including Wolf Motor Function Test, Box and Block Test, and Motor Activity Log, also revealed superior outcomes in the electrical stimulation group than those in the placebo group. Comparisons between three types of electrical stimulation (sensory, cyclic, and electromyography-triggered electrical stimulation) groups revealed no significant differences in the body function and activity.

Electrical stimulation therapy can effectively improve the arm function in stroke patients.

via Effectiveness of electrical stimulation therapy in improving arm function after stroke: a systematic review and a meta-analysis of randomised controlled trials – Jheng-Dao Yang, Chun-De Liao, Shih-Wei Huang, Ka-Wai Tam, Tsan-Hon Liou, Yu-Hao Lee, Chia-Yun Lin, Hung-Chou Chen, 2019

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[ARTICLE] Effects of Hand Configuration on the Grasping, Holding, and Placement of an Instrumented Object in Patients With Hemiparesis – Full Text

Abstract

Objective: Limitations with manual dexterity are an important problem for patients suffering from hemiparesis post stroke. Sensorimotor deficits, compensatory strategies and the use of alternative grasping configurations may influence the efficiency of prehensile motor behavior. The aim of the present study is to examine how different grasp configurations affect patient ability to regulate both grip forces and object orientation when lifting, holding and placing an object.

Methods: Twelve stroke patients with mild to moderate hemiparesis were recruited. Each was required to lift, hold and replace an instrumented object. Four different grasp configurations were tested on both the hemiparetic and less affected arms. Load cells from each of the 6 faces of the instrumented object and an integrated inertial measurement unit were used to extract data regarding the timing of unloading/loading phases, regulation of grip forces, and object orientation throughout the task.

Results: Grip forces were greatest when using a palmar-digital grasp and lowest when using a top grasp. The time delay between peak acceleration and maximum grip force was also greatest for palmar-digital grasp and lowest for the top grasp. Use of the hemiparetic arm was associated with increased duration of the unloading phase and greater difficulty with maintaining the vertical orientation of the object at the transitions to object lifting and object placement. The occurrence of touch and push errors at the onset of grasp varied according to both grasp configuration and use of the hemiparetic arm.

Conclusion: Stroke patients exhibit impairments in the scale and temporal precision of grip force adjustments and reduced ability to maintain object orientation with various grasp configurations using the hemiparetic arm. Nonetheless, the timing and magnitude of grip force adjustments may be facilitated using a top grasp configuration. Conversely, whole hand prehension strategies compound difficulties with grip force scaling and inhibit the synchrony of grasp onset and object release.

 

Introduction

Cerebrovascular accidents (stroke) are a frequent cause of disability (1) and the recovery of upper-limb function in particular, is a key determinant of independence in activities of daily living (2). Broadly speaking, the physical impairment experienced by patients is characterized by loss of strength, abnormal movement patterns (pathological synergies), and changes in muscle tone to the side of the body contralateral to the stroke (34). This presentation is commonly referred to as hemiparesis and its severity tends to reflect the extent of the lesion to the corticospinal tract (5). Subtle changes in movement kinematics and hand function on the ipsilesional upper-limb have also been documented and may be the consequence of direct impairment of ipsilateral motor pathways (67), as well as reorganization of the non-lesioned hemisphere to support recovery of motor-function in the hemiparetic limb (810). Above all though, patients living with stroke find that limitations with manual dexterity of the hemiparetic arm have the most significant effect upon their ability to carry out activities involving hand use in daily life (11).

These impairments in patient hand function manifest in multiple different aspects of motor performance. This may include reduced strength (3), loss of individuated finger control (12), and abnormal force control at the level of the fingers (13). Increased muscle tone and spasticity though the flexors of the wrist and hand may further compound these difficulties and inhibit the ability to open the hand in preparation for grasping (14). Atypical reaching and grasping patterns are often seen to emerge both as a consequence of and as a response to the motor dysfunction (1516).

Unfortunately, rehabilitation of upper limb impairments proves to be challenging. Whilst numerous therapeutic modalities (e.g., bilateral training, constraint-induced therapy, electrical stimulation, task-oriented, high intensity programs) have been evaluated in clinical trials, none have demonstrated consistent effects upon hand function (1719). Indeed, previous research papers have described therapy outcomes in upper limb rehabilitation post stroke as “unacceptably poor” (20). Ideally, the design of neurorehabilitation programs should be grounded upon an understanding of basic mechanisms involved in neural plasticity and motor learning (2122). Part of this process implies coming to terms with the factors which characterize the disorganization in voluntary motor output (21). However, the majority of clinical tools currently used for evaluating hand function distinguish motor performance according to ordinal rating scales or task completion time (e.g., Frenchay Arm Test, Jebson-Taylor Hand Function Test) (2324). These kinds of assessments lack sensitivity and may prove insufficient for detecting the presence of mild motor deficits or subtle, yet clinically important changes in hand coordination (2526). Evidence based frameworks for hand rehabilitation have specifically called for the integration of new technology to support patient assessment and treatment planning (27). Despite this, the transposition of technology for upper limb rehabilitation from the research domain into clinical practice has been limited (2829). In the assessment of manual dexterity, the underlying challenge involves analyzing sensorimotor function of the hand with respect to its interaction with objects in the environment (30).

Successfully managing grasping and object handling tasks requires skilled control of prehensile finger forces. In healthy adults, grip forces are regulated to be marginally greater than the minimum required to prevent the object from slipping (31). This safety margin is calibrated according to the shape, surface friction and weight distribution of the object (3233). As the hand moves through space (lifting, transporting, object placement), grip force is continually modulated, proportional to the load forces associated with the mass and acceleration of that object (34). This temporal coupling between grip and load forces is considered a hallmark of anticipatory sensorimotor control (35). Disruption to motor planning, volitional motor control or somatosensory feedback may lead to a breakdown in the timing and magnitude of grip force adjustments.

Numerous studies have examined grip force regulation in neurological pathologies including cerebellar dysfunction (36), peripheral sensory neuropathy (3738), Parkinson’s disease (36373940) as well as congenital and acquired brain lesions (13364145). For patients suffering from hemiparesis post stroke, difficulty with coordinating the grasping and lifting action are frequently associated with temporal discrepancies between grip forces and load forces (46). The cerebral hemisphere implicated in the CVA (1347) and the extent of the resulting sensory deficits (4849) have also been observed to influence anticipatory grip force scaling. This body of work highlights the potential interest of using instrumented objects for the diagnosis and evaluation of the impairments associated with hemiparesis (4546485053).

As it stands, these objective studies of hand function post stroke have focused primarily upon either the lifting or the vertical movement components in object handling. To a certain extent, this limitation has been related to technical restrictions. Other than a handful of studies by Hermsdorfer et al. (849), research in this field has predominantly used manipulanda designed for the study of precision grip, where strain gauge force transducers are attached to a separate base unit [e.g., (232529333537)]. These devices cannot be freely handled by subjects, much less a person with an upper-limb movement disorder. Indeed, patients with hemiparesis often experience specific impairments with precision grip (53) and regularly use alternative grasping strategies such as whole hand grasping (151654). Previous researchers have hypothesized that these alternative grasp strategies may impact grip force scaling (55) and compromise patient ability to manage hand-object-environment relationships during object manipulation (56).

In a recent study with healthy adult subjects, (57) we demonstrated how an instrumented object with multiple load cells and an integrated inertial measurement unit (58) may be used to examine relationships between different grasp configurations, grip force regulation and object orientation. The purpose of the present investigation was to extend this work to the study of patients with hemiparesis post stroke. The first objective was to compare how four alternative grasp configurations commonly used in daily tasks affect grip force regulation in this population. The second objective was to explore the timing and coordination of the whole task sequence (grasping, lifting, holding, placement and object release). The third and final objective was to evaluate the stability of the hand-held object’s orientation across the different phases of the task.[…]

 

Continue —> Frontiers | Effects of Hand Configuration on the Grasping, Holding, and Placement of an Instrumented Object in Patients With Hemiparesis | Neurology

Figure 1. Illustration of the iBox device and the experimental setup. (A) The iBox instrumented object. (B)Setup for the experimental procedure. Initial positions of the iBox and hand start area are indicated by the dotted lines. The gray shaded rectangle indicates the deposit area for the top grasp task.

 

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[Abstract] Evaluation of a 12-month lifestyle intervention by individuals with traumatic brain injury.

Abstract

Weight gain and inactivity are common problems for individuals living with a traumatic brain injury (TBI). Yet, interventions to support a healthy lifestyle specific to individuals with TBI are lacking. The purpose of this study was to complete a program evaluation of a 12-month evidence-based healthy lifestyle intervention adapted for people with a TBI. Eighteen participants completed a brief interview after the yearlong intervention to determine their perceptions of the program effectiveness as well as barriers and facilitators in making lifestyle changes. Participants reported staff, tracking of dietary and activity behavior, and in-person meetings as most helpful aspects. Lack of motivation and difficulty preparing healthy meals were the primary barriers to a healthy lifestyle. Qualitative data revealed five themes that influenced healthy behaviors, including (1) self-regulation, (2) environmental resources, (3) knowledge of health behaviors, (4) TBI-related impairment and comorbidities, and (5) social support. Results suggest that future iterations of the healthy lifestyle intervention should emphasize self-regulation activities; require tracking of dietary and activity behaviors across 12 months; provide concurrent support for individual motivation issues; provide prepared meals; utilize web-based, telephonic, or hybrid approaches to delivery; further simplify the curriculum and learning tools; and include caregivers and peer accountability partners. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

 

via Evaluation of a 12-month lifestyle intervention by individuals with traumatic brain injury. – PubMed – NCBI

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