Posts Tagged neurological disorder

[REVIEW] Epilepsy: A Stigma More than Disease – Full Text PDF

Abstract

Epilepsy is a common neurological disorder that occurs from ancient times and accompanying with convulsions or seizures. Epilepsy has revealed a genetic basis. Epilepsy which is considered as a neurodevelopmental disorder has reduced the life expectancy and associated with various stigmatized attitudes or beliefs. Epilepsy and seizures can develop in any person both in male and female at any age. Head trauma and brain strokes are the major causes of epilepsy in adults. Epilepsy accompanied by changes in behavior, personality, and cognition. Several aspects of epilepsy can affect the brain and behavior. Stigma is a reality for a lot of people with a mental disorder. It is a mark of disgrace which sets a person apart from others. Negative attitudes and beliefs create prejudice which leads to negative actions and discrimination. Stigma and social exclusions are stereotyped characteristics of epilepsy. Someone with a mental illness known to be a dangerous and senseless rather than saying in poor health conditions. There are no effective cures for an epileptic people. Besides, many epileptic therapies or cures are still available for the diagnosis and prevention of people with epilepsy. Epilepsy treatment entails how epilepsy is treated and which techniques and antiepileptic drugs are used.

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[ARTICLE] Brain–computer interface and assist-as-needed model for upper limb robotic arm – Full Text

Post-stroke paralysis, whereby subjects loose voluntary control over muscle actuation, is one of the main causes of disability. Repetitive physical therapy can reinstate lost motions and strengths through neuroplasticity. However, manually delivered therapies are becoming ineffective due to scarcity of therapists, subjectivity in the treatment, and lack of patient motivation. Robot-assisted physical therapy is being researched these days to impart an evidence-based systematic treatment. Recently, intelligent controllers and brain–computer interface are proposed for rehabilitation robots to encourage patient participation which is the key to quick recovery. In the present work, a brain–computer interface and assist-as-needed training paradigm have been proposed for an upper limb rehabilitation robot. The brain–computer interface system is implemented with the use of electroencephalography sensor; moreover, backdrivability in the actuator has been achieved with the use of assist-as-needed control approach, which allows subjects to move the robot actively using their limited motions and strengths. The robot only assists for the remaining course of trajectory which subjects are unable to perform themselves. The robot intervention point is obtained from the patient’s intent which is captured through brain–computer interface. Problems encountered during the practical implementation of brain–computer interface and achievement of backdrivability in the actuator have been discussed and resolved.

The recovery of upper limb motions and strengths in patients with damaged neuromuscular system via robotic rehabilitation devices is a promising way of enhancing existing treatments and their efficacies. Various reasons may cause limb dysfunctions, including stroke, spinal cord injuries, or even ligament rupture. According to the World Health Organization, about 15 million people globally suffer from Cerebro-Vascular Accidents (CVAs) each year and up to 65% of these need limb recovery procedures.1 Only in the last 15 years, the number of CVA or stroke patients is increased by 40%, which is the result of a more intense pace of living, deterioration of ecology, and increased aging population.2 Considering these statistics, development of new and efficient ways of rehabilitation is just as important as implementation of improved prevention strategies.

For the last 20 years, robotics-based therapy was steadily paving its way for becoming an essential practice in rehabilitation medicine.3,4 According to the systematic review of Kwakkel et al.5 on the upper limb recovery using robot-aided therapy, repetitive, meaningful, labor-intensive treatment programs implemented with robotic devices provide positive impact for the restoration of functional abilities in human limbs. In medical terminology, a device that provides support, and aligns or improves the function of movable limbs is known as orthosis, and robotic devices intended to provide such treatment are called robotic orthoses.6 Particularly, two key directions gained major attention in the medical engineering research: robot-assisted therapy and functional electrical simulation (FES) therapy. The FES therapy describes a technique that stimulates weakened or paralyzed muscles on a human limb by applying electric charges externally. The goal of FES therapy is to reactivate the neural connections between a muscle and human’s sensorimotor system to enable patients’ ability to control their limbs without assistance.7 In the study by Popovic and others, the functional electrical therapy (FET) was applied with the use of surface electrodes and it was used to stimulate arm fingers of patients, this therapy has demonstrated positive therapeutic effects.8 It was revealed that daily 30-min therapy for 1-month period allowed improvement in movement range, speed, and increased strength in muscles. There are also side effects of FES-based treatment such as pain and irritation on the affected area, autonomic dysreflexia, increased spasticity, broken bones, and mild electric shocks from faulty equipment. However, the robot-assisted rehabilitation is non-invasive and free from above risks, and it is preferred for the rehabilitation of stroke survivors.

The important advantage of robotic devices is that they can reduce the burden on health care workers who traditionally had to conduct labor-intensive training sessions for patients. Equipped with sensors, intelligent controllers, and haptic and visual interfaces, robotic orthosis can have a potential to put the recovery process to a new level by collecting relevant data about various health parameters (pulse rate, body temperature, etc.) and adjusting the training modes accordingly. Besides the positive impacts of robot-based rehabilitation, the reliability of robot-based assistance is still questionable and adversely it may worsen the recovery progress made before, and that depends on the type of assistance control robot employs.9 Assist-as-needed (AAN) control type has become one of the prominent strategies recently which has been recommended positively from clinical trials.10 In order to stabilize the system, AAN-based approach has become subject to be researched by scientists. In the work done by Wolbrecht, AAN control is obtained from the adaptive control by incorporating novel force to address and decrease the system’s parametric errors.11 There are also other works which propose AAN type of control for their systems;1214 however, there are no works which have incorporated both BCI (brain–computer interface)- and AAN-based control approach into the system.

Owing to the recent advances in biosensors, especially in their robustness and signal processing, robot controllers equipped with bio-sensing are able to achieve intelligence with less complex algorithms. One of the most recent applications of BCI is in the domain of orthoses.1517 Newer instances of orthoses combine latest advances in control theory and brain activity. Berlin Technical University in cooperation with Korean University created an exoskeleton to maneuver lower limbs. A feature of this work is the use of non-invasive electroencephalography (EEG). The study involved 11 healthy men aged 25 to 32 years.18 First upper limb exoskeleton controlled by BCI was proposed by AA Frolov et al.19 Authors concluded that BCI inclusion improves the movements of the paretic hand in post-stroke patients irrespective of severity and localization of the disease. In addition, it was shown that duration of the training also increases effectiveness of rehabilitation.

Based on the letters on the screen, it was possible to determine native language of the patient in the work done by Vasileva.20 In this work, non-invasive EEG had been used. However, it was noted that non-invasive devices have less accuracy than professional medical EEG equipment. To improve signal detection, Agapov et al.21 have developed advanced algorithm of processing visually evoked potentials. To visualize stimuli, “eSpeller” software was developed.

Motivated by the above-mentioned successes and advances, in the present work, possible use of BCI is investigated in the rehabilitation robots for the treatment of stroke survivors. The aim of this work is to develop EEG-based mechatronic system that can receive electrical brain signals, detect emotions and gestures of the patient, and intelligently control robotic arm. In addition, to ensure smooth and compliant movement of the rehabilitation robot and improve treatment efficacy, AAN control paradigm is also considered. This research used EEG package and a controller to develop BCI system and realize AAN-based control. Developed system can help patients to control robot with their thoughts and enhance their participation in the rehabilitation process. Methodology of the current work is explained in the “Methodology” section, and in the subsequent sections, results are discussed before drawing conclusions from this research work.

EEG sensor

In order to register the brain activity, 16 EEG electrodes distributed around the patient’s head have been used. To provide more information which is related to motor imaginary signals, the frequency characteristics were extracted from the data by converting them from the time domain to the frequency domain. Furthermore, to distinguish between movement intentions and rest positions, bandpass filter in the range of 5 to 40 Hz was used.22,23 Since EEG data set recording can be very large, the powerful surface Laplacian technique was applied to lower the risk of influence from the neighboring neurons on the crucial cerebral cortex neurons.24 Finally, only dominant frequency of 13 to 30 Hz, also known as beta wave frequency, was featured according to Gropper et al.25 This band distinction was benchmarker as a sensible area of resting brain activity.

Abiding by the previous works associated with EEG signal processing in Iáñez et al.26 and Hortal et al.,27 the feature selection was reduced to the group of 29 features, which later were used for the further classification and predictive model construction.

After receiving data using an EEG, algorithm needs to determine the desired effect for the user. Input data for this algorithm are EEG signals recorded during the demonstration of stimuli. In most of the currently existing studies on this subject, the problem of classifying signals is divided into three large subtasks:

  • Preprocessing the signal (in order to remove noise components);
  • Formation of a feature space;
  • Classification of objects in the constructed feature space.

It should be noted that the greatest influence on the final quality of the classification is made by the extent to which the task of forming the feature space was successfully accomplished. The general scheme of operation of BCI is depicted in Figure 1.


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Figure 1. Block diagram of BCI interface.

 

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Continue —>  Brain–computer interface and assist-as-needed model for upper limb robotic arm – Akim Kapsalyamov, Shahid Hussain, Askhat Sharipov, Prashant Jamwal, 2019

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Figure 4. (a) ELA actuated upper limb rehabilitation robot, (b) upper limb rehabilitation robot in use, and (c) robotic orthosis in use with EEG sensor.

 

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[ARTICLE] Combining transcranial direct-current stimulation with gait training in patients with neurological disorders: a systematic review – Full Text

Abstract

Background

Transcranial direct-current stimulation (tDCS) is an easy-to-apply, cheap, and safe technique capable of affecting cortical brain activity. However, its effectiveness has not been proven for many clinical applications.

Objective

The aim of this systematic review was to determine whether the effect of different strategies for gait training in patients with neurological disorders can be enhanced by the combined application of tDCS compared to sham stimulation. Additionally, we attempted to record and analyze tDCS parameters to optimize its efficacy.

Methods

A search in Pubmed, PEDro, and Cochrane databases was performed to find randomized clinical trials that combined tDCS with gait training. A chronological filter from 2010 to 2018 was applied and only studies with variables that quantified the gait function were included.

Results

A total of 274 studies were found, of which 25 met the inclusion criteria. Of them, 17 were rejected based on exclusion criteria. Finally, 8 trials were evaluated that included 91 subjects with stroke, 57 suffering from Parkinson’s disease, and 39 with spinal cord injury. Four of the eight assessed studies did not report improved outcomes for any of its variables compared to the placebo treatment.

Conclusions

There are no conclusive results that confirm that tDCS can enhance the effect of the different strategies for gait training. Further research for specific pathologies, with larger sample sizes and adequate follow-up periods, are required to optimize the existing protocols for applying tDCS.

Introduction

Difficulty to walk is a key feature of neurological disorders [1], so much so that recovering and/or maintaining the patient’s walking ability has become one of the main aims of all neurorehabilitation programs [2]. Additionally, the loss of this ability is one of the most significant factors negatively impacting on the social and professional reintegration of neurological patients [3].

Strategies for gait rehabilitation traditionally focus on improving the residual ability to walk and compensation strategies. Over the last years, a new therapeutic paradigm has been established based on promoting neuroplasticity and motor learning, which has led to the development of different therapies employing treadmills and partial body-weight support, as well as robotic-assisted gait training [4]. Nevertheless, these new paradigms have not demonstrated superior results when compared to traditional therapies [5,6,7], and therefore recent studies advise combining therapies to enhance their therapeutic effect via greater activation of neuroplastic mechanisms [8].

Transcranial direct-current stimulation (tDCS) is an intervention for brain neuromodulation consisting of applying constant weak electric currents on the patient’s scalp in order to stimulate specific brain areas. The application of the anode (positive electrode) to the primary motor cortex causes an increase in neuron excitability whereas stimulation with the cathode (negative electrode) causes it to decrease [9].

The effectiveness of tDCS has been proven for treating certain pathologies such as depression, addictions, fibromyalgia, or chronic pain [10]. Also, tDCS has shown to improve precision and motor learning [11] in healthy volunteers. Improvements in the functionality of upper limbs and fine motor skills of the hand with paresis have been observed in patients with stroke using tDCS, although the results were somewhat controversial [1213]. Similarly, a Cochrane review on the effectiveness of tDCS in treating Parkinson’s disease highlights the great potential of the technique to improve motor skills, but the significance level of the evidence was not enough to clearly recommend it [14]. In terms of gait rehabilitation, current studies are scarce and controversial [10].

Furthermore, tDCS is useful not only as a therapy by itself but also in combination with other rehabilitation strategies to increase their therapeutic potential; in these cases, the subjects’ basal activity and the need for combining the stimulation with the behavior to be enhanced have been highlighted. Several studies have combined tDCS with different modalities of therapeutic exercising, such as aerobic exercise to increase the hypoalgesic effect in patients with fibromyalgia [15] or muscle strengthening to increase functionality in patients suffering from knee osteoarthritis [16]. Along these lines, various studies have combined tDCS with gait training in patients with neurological disorders, obtaining rather disparate outcomes [17,18,19,20]. As a result, the main aim of this systematic review was to determine whether the application of tDCS can enhance the effectiveness of other treatment strategies for gait training. Additionally, as a secondary objective, we attempted to record and identify the optimal parameters of the applied current since they are key factors for its effectiveness. […]

 

Continue —>  Combining transcranial direct-current stimulation with gait training in patients with neurological disorders: a systematic review | Journal of NeuroEngineering and Rehabilitation | Full Text

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[WEB SITE] How Neuro-Physiotherapy Imparts Quality to Life

By Dr. Nayeem U Zia

Since the last decade or so, we have been witnessing an upsurge in neurological problems such as strokes, Parkinson’s disease, diabetic neuropathy, and motor neuron diseases in our society. An alarming concern is that these problems have started affecting people at a younger age. Worldwide, neurological disorders are associated with higher rates of morbidity and mortality which in turn inflict higher cost of rehabilitation upon the sufferers. Given the topography, changing life style and the stressors, Kashmiris , per se, have a strong affinity toward neurological problems.
A belief that still dominates the clinical decision making of most healthcare professionals is that the recovery from neurological disorders is strictly a time bound phenomenon and to expect it happen after a set time frame, is unrealistic. Research has nullified it and suggests that brain can modify itself at any point in time provided the treatment is channelized in a right direction.
Unfortunately, we all come across a chunk of people who have fallen prey to such dogmas and live a lifeless life. Another chunk of the patient population is suffering because of its contentment with regard to the menial and irrelevant improvements. Needless to mention, it is the acumen of a skilled neuro-physiotherapist that determines the potential of rewiring of central nervous system connections essential for recovery. The concept of recovery has changed over a period of time; earlier, recovery was perceived as patients’ ability to achieve nominal and insignificant improvements that would enable them to come out of bed and walk a few steps. On the contrary, recovery now is tantamount to movements with a purpose in order to help patients regain functions, and eventually fulfill their social responsibilities.
Rehabilitation of patients with neurological problems is a high cost affair with huge financial and social costs. Soon after a person gets afflicted with a neurological disorder, besides the patient, the family members start bearing the brunt of the disease. Research reports reveal that the caregivers of neurologically impaired patients are exposed to a high level of stress which affects their productivity and, in turn, compromises the role they play in society. Recovery from neurological disorders, being relatively slower, demands close supervision and assistance from family members. In the meantime family members start dedicating their time and money towards the rehabilitation of the patient. Moreover, with modern family systems, every ailing person does not enjoy the luxury of extended social support and, eventually a number of impediments start emerging in the path of recovery.
In a nutshell, neurological problems not only affect patients but pose a massive challenge to family members too. The best strategy to cope up with the neurological problems is to facilitate patients’ functional independence as rapidly as possible that will eventually offload the family members to a greater extent.
Neurorehabilitation has undergone timely refinements to ensure best possible and evidence based care to patients. Modern day Neurorehabilitation uses approaches that emphasize minimizing compensations to ensure complete functional recovery. Functional independence is its essence and a neuro-physiotherapist proves to be an apt resource to deliver the best in order to achieve the short-term and long-term functional milestones. People in the valley have a limited knowledge of neuro-physiotherapy and the role a neuro-physiotherapist plays. A neuro-Physiotherapist, being a responsible member of healthcare team, plays a vital role right from the onset of a neurological problem to the stage of community rehabilitation of a patient.
Since Physiotherapists are movement science experts, fellow medical professionals and patients’ families can’t afford taking a neuro-Physiotherapist’s consultation and advice for granted. An insignificant problem, if left unaddressed, can have devastating repercussions later. For instance, a trivial fault in the shoulder after stroke/brain injury can affect a patient’s ability to drink and eat with the hand. Therefore, physiotherapy consultation from the outset remains crucial in determining a patient’s functional outcomes and ignoring it is at one’s peril.

Physiotherapists too need to be well versed in the latest developments in the field of neuro-physiotherapy to ensure quality care delivery. A neuro-Physiotherapist can make best use of treatments methods such as Constraint Induced Movement Therapy (CIMT), Virtual Reality (VR), Functional Electrical Stimulation (FES), Proprioceptive Neuromuscular Facilitation (PNF), Neurodevelopmental Treatment (NDT), Motor Relearning Programme (MRP), Task Specific Training, Partial Body Weight Support Treadmill Training (PBWSTT), and Robotics and so on. In order to achieve set functional objectives, neuro-physiotherapists equipped with the magic wand will surely help patients impart quality to their lives.

The author is a Physiotherapist at the J&K Health services, an Ex-Assistant Professor, Hamdard University Delhi and a Certified NDT Therapist , NDTA USA. He can be reached at: nayampt@gmail.com

 

via How Neuro-Physiotherapy Imparts Quality to Life | Kashmir Reader

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[Abstract] Systematic review of high-level mobility training in people with a neurological impairment.

Abstract

AIM:

The objective of this paper was to systematically review the efficacy of interventions targeting high-level mobility skills in people with a neurological impairment.

METHODS:

A comprehensive electronic database search was conducted. Study designs were graded using the American Academy of Cerebral Palsy and Developmental Medicine (AACPDM) system and methodological quality was described using the Physiotherapy Evidence Database (PEDro) scale.

RESULTS:

Twelve exploratory studies (AACPDM levels IV/V), of limited methodological quality (PEDro scores of 2-3 out of 10), were included. Interventions included treadmill training, a three-phase programme, a high-level mobility group, plyometric training, running technique coaching and walk training with blood flow restriction. Diagnoses included acquired brain injury, cerebral palsy, incomplete spinal cord injury and neurofibromatosis type 1. There were difficulties generalizing results from exploratory designs with a broad range of participants, interventions and outcome measures. However, it seems that people with a neurological impairment have the capacity to improve high-level mobility skills, running speed and distance with intervention. There were no adverse events that limited participation.

CONCLUSION:

There is preliminary evidence to support the efficacy of interventions to improve high-level mobility skills in people with neurological impairments. Well-controlled research with a larger sample is required to provide sufficient evidence to change clinical practice.

 

via Systematic review of high-level mobility training in people with a neurological impairment. – PubMed – NCBI

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[WEB SITE] New algorithm helps neurological disorder patients to walk naturally

Soon, wheelchairs may no longer be needed; new research enables patients with neurological disorders to walk again.

Millions of people cannot move their limbs as a result of a neurological disorder or having experienced an injury. But a newly developed algorithm, when coupled with robot-assisted rehabilitation, can help patients who had a stroke or a spinal cord injury to walk naturally.

In the United States, there are approximately 17,000 new cases of spinal cord injury (SCI) every year. Of these, 20 percent result in complete paraplegia (paralysis of the legs and lower half of body) and over 13 percent result in tetraplegia (paralysis of all four limbs).

But SCI is not the only reason that people experience this type of disability. Stroke, multiple sclerosis, cerebral palsy, and a range of other neurological disorders can all lead to paralysis. In fact, a recent survey estimated that in the U.S., almost 5.4 million people live with paralysis, with stroke being the leading cause of this disability.

Now, researchers from the National Centre of Competence in Research Robotics at École Polytechnique Fédérale de Lausanne (EPFL), and at the Lausanne University Hospital in Switzerland, have come up with a groundbreaking technology that may help these patients to regain their locomotor skills.

The scientists came up with an algorithm that helps a robotic harness to facilitate the movements of the patients, thus enabling them to move naturally.

The new research has been published in the journal Science Translational Medicine, and the first author of the study is Jean-Baptiste Mignardot.

Helping people to walk again

Current rehabilitation technologies for people with motor disabilities as a result of SCI or stroke involve walking on a treadmill, with the upper torso being supported by an apparatus. But existing technologies are either too rigid or do not allow the patients to move naturally in all directions.

As the authors of the new study explain, the challenge of locomotor rehabilitation resides in helping the nervous system to “relearn” the right movements. This is difficult due to the loss of muscle mass in the patients, as well as to the neurological wiring that has “forgotten” correct posture.

In order to overcome these obstacles and promote natural walking, Mignardot and colleagues designed an algorithm that coordinates with a robotic rehabilitation harness. The team tested the algorithm in more than 30 patients. The “smart walk assist” markedly and immediately improved the patients’ locomotor abilities.

This mobile harness, which is attached to the ceiling, enables patients to walk. This video shows how it works:

Additionally, after only 1 hour of training with the harness and algorithm, the “unsupported walking ability” of five of the patients improved considerably. By contrast, 1 hour on a conventional treadmill did not improve gait.

The researchers developed the so-called gravity-assist algorithm after carefully monitoring the movements of the patients and considering parameters such as “leg movement, length of stride, and muscle activity.”

As the authors explain, based on these measurements, the algorithm identifies the forces that must be applied to the upper half of the body in order to allow for natural walking.

The smart walk assist is an innovative body-weight support system because it manages to resist the force of gravity and push the patient back and forth, to the left and to the right, or in more of these directions at once, which recreates a natural gait and movement that the patients need in their day to day lives.

Grégoire Courtine, a neuroscientist at EPFL and the Lausanne University Hospital, comments on the significance of the findings, saying, “I expect that this platform will play a critical role in the rehabilitation of walking for people with neurological disorders.”

This is a smart, discreet, and efficient assistance that will aid rehabilitation of many persons with neurological disorders.”

Prof. Jocelyne Bloch, Department of Neurosurgery, Lausanne University Hospital

Source: New algorithm helps neurological disorder patients to walk naturally

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[WEB SITE] MusicGlove: World’s First FDA Approved Music-Based Hand Rehabilitation Device

When it comes to therapy for stroke patients, we picture mundane, boring exercises that they have to perform for months, and sometimes years. How great would it be to add excitement and fun  to the entire regime so that patients are actually motivated (and even look forward) to continue to exercise and feel better?

MusicGlove does just that. A glove that lets you play a Guitar Hero like game on a tablet or a bigger screen, it is meant for people who have survived strokes or have other neurological and muscular injuries that limit the movement of their hands. A study has shown that patients who use MusicGlove for therapy show significant improvement in their hand movements only after two weeks as compared to people who go through traditional therapy. It requires minimal interaction with the  therapist and the patient can “play” it whenever they want to.

Plus, there’s music!…

via Assistive Technology Blog: MusicGlove: World’s First FDA Approved Music-Based Hand Rehabilitation Device.

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