Posts Tagged Neurorehabilitation

[ARTICLE] Effects of action observation therapy and mirror therapy after stroke on rehabilitation outcomes and neural mechanisms by MEG: study protocol for a randomized controlled trial – Full Text



Loss of upper-extremity motor function is one of the most debilitating deficits following stroke. Two promising treatment approaches, action observation therapy (AOT) and mirror therapy (MT), aim to enhance motor learning and promote neural reorganization in patients through different afferent inputs and patterns of visual feedback. Both approaches involve different patterns of motor observation, imitation, and execution but share some similar neural bases of the mirror neuron system. AOT and MT used in stroke rehabilitation may confer differential benefits and neural activities that remain to be determined. This clinical trial aims to investigate and compare treatment effects and neural activity changes of AOT and MT with those of the control intervention in patients with subacute stroke.


An estimated total of 90 patients with subacute stroke will be recruited for this study. All participants will be randomly assigned to receive AOT, MT, or control intervention for a 3-week training period (15 sessions). Outcome measurements will be taken at baseline, immediately after treatment, and at the 3-month follow-up. For the magnetoencephalography (MEG) study, we anticipate that we will recruit 12 to 15 patients per group. The primary outcome will be the Fugl-Meyer Assessment score. Secondary outcomes will include the modified Rankin Scale, the Box and Block Test, the ABILHAND questionnaire, the Questionnaire Upon Mental Imagery, the Functional Independence Measure, activity monitors, the Stroke Impact Scale version 3.0, and MEG signals.


This clinical trial will provide scientific evidence of treatment effects on motor, functional outcomes, and neural activity mechanisms after AOT and MT in patients with subacute stroke. Further application and use of AOT and MT may include telerehabilitation or home-based rehabilitation through web-based or video teaching.


Stroke is the leading cause of long-term adult disability worldwide [1]. Most patients with stroke experience upper-extremity (UE) motor impairment [2] and show minimal recovery of the affected arm even 6 months after stroke [3]. Due to the potentially severe adverse effects after stroke, it is critical in clinical practice to develop effective and specific stroke interventions to improve arm function and to explore the neural mechanisms involved [45]. Action observation therapy (AOT) and mirror therapy (MT) are two examples of novel approaches concerning stroke motor recovery that are supported by neuroscientific foundations [67]. However, the relative efficacy of AOT versus MT has not been validated in patients with stroke.

AOT is a promising approach grounded in basic neuroscience and the recent discovery of the mirror neuron system (MNS) [6]. AOT commonly includes action observation and action execution and allows patients to safely practice movements and motor tasks. AOT is recommended to help patients with stroke to form accurate images of motor actions [8] and to mediate their motor relearning process after stroke [6]. Researchers have found that AOT can induce stronger cognitive activity than motor imagery in patients with stroke and have suggested that AOT could be an effective approach for patients who have difficulty with motor representation [9]. AOT is a new approach in stroke rehabilitation; therefore, only a few studies have targeted enhancement of UE motor recovery and investigated the effects of AOT in patients with stroke [81011121314]. Based on these studies, AOT has been shown to be a beneficial and effective approach to improve patient motor function. However, the heterogeneity of study designs and small sample sizes of the studies lead to no clear conclusions about the efficacy of AOT in stroke rehabilitation.

MT has emerged as another novel stroke-rehabilitation approach during the last decade [151617]. In this treatment, participants are instructed to move their arms and watch the action reflection of the non-affected arm in the mirror, as if it were the affected one. The process creates the visual illusion of the non-affected arm as the affected arm is normally moving. MT focuses on visual and proprioceptive feedback of the non-affected limb, which may provide substitute inputs for absent or reduced proprioceptive feedback from the affected side of the body [18]. A growing amount of academic literature has demonstrated that patients with stroke gain improvements in motor and daily function, movement control strategies, and activities of daily living [1617] after treatment with MT, which supports its use in stroke rehabilitation. In short, MT is potentially a simpler, less expensive, and effective stroke-rehabilitation approach for practical implementation in clinical settings.

Action observation is based on activities of the MNS and mainly involves brain areas of the inferior parietal lobe, inferior frontal gyrus, and ventral premotor cortex [19]. Mirror neurons discharge both during the execution of motor acts or goal-directed actions and during the observation of other people performing the same or similar actions [20]. Experimental studies in healthy adults have demonstrated that the MNS was activated during both the observation and execution of movements, which helped to form new motor patterns during action observation [212223]. In addition, although positive effects of MT have been demonstrated in patients with stroke [24], there is no consensus about the underlying neural mechanisms of MT. Three hypotheses have been recently proposed to explain the beneficial effects of MT on motor recovery [7]. Accordingly, MT may affect perceptual motor processes via three functional neural networks: (1) activation of brain regions associated with MNS [2526], (2) recruitment of ipsilateral motor pathways [27], and (3) substitution of abnormal proprioception from the affected limb with feedback from the non-affected limb [1518]. Few AOT and MT neurophysiological or imaging studies have been conducted in patients with stroke. No studies have directly compared and unraveled the similarities or differences in neural plastic changes between AOT and MT in these patients. It is crucial to compare neuroplasticity mechanisms between these intervention regimens to optimize rehabilitative outcomes.


The main purposes of this clinical trial are to (1) compare the immediate and retention treatment effects of AOT and MT on different outcomes with those of a dose-matched control group and (2) explore and compare the neural mechanisms and changes in cortical neural activity associated with the effects of AOT and MT in stroke patients, using magnetoencephalography (MEG).[…]

Continue —> Effects of action observation therapy and mirror therapy after stroke on rehabilitation outcomes and neural mechanisms by MEG: study protocol for a randomized controlled trial | Trials | Full Text

Fig. 2 Action observation therapy. a Observation of task. b Execution of task


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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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[ARTICLE] Transcranial direct current stimulation as a motor neurorehabilitation tool: an empirical review – Full Text


The present review collects the most relevant empirical evidence available in the literature until date regarding the effects of transcranial direct current stimulation (tDCS) on the human motor function. tDCS in a non-invasive neurostimulation technique that delivers a weak current through the brain scalp altering the cortical excitability on the target brain area. The electrical current modulates the resting membrane potential of a variety of neuronal population (as pyramidal and gabaergic neurons); raising or dropping the firing rate up or down, depending on the nature of the electrode and the applied intensity. These local changes additionally have shown long-lasting effects, evidenced by its promotion of the brain-derived neurotrophic factor. Due to its easy and safe application and its neuromodulatory effects, tDCS has attracted a big attention in the motor neurorehabilitation field among the last years. Therefore, the present manuscript updates the knowledge available about the main concept of tDCS, its practical use, safety considerations, and its underlying mechanisms of action. Moreover, we will focus on the empirical data obtained by studies regarding the application of tDCS on the motor function of healthy and clinical population, comprising motor deficiencies of a variety of pathologies as Parkinson’s disease, stroke, multiple sclerosis and cerebral palsy, among others. Finally, we will discuss the main current issues and future directions of tDCS as a motor neurorehabilitation tool.


The central nervous system (CNS) works thanks to the communication between more than 100,000 millions of neurons, whose activity and networking is modulated by chemical and electrical processes [1]. Across history, humans have been trying to alter the electrical brain processes to enhance human’s brain function, for the treatment of psychopathologies and for a better understanding of the brain physiology. For example, in the antiquity, modulation of the electrical processes of the brain started with the use of electrical impulses of torpedo fishes applied directly on the CNS, for therapeutic purposes [2]. In 1746, Musschenbroek (1692–1761) used Leyde jars and electrostatic devices to treat neuralgia, contractures and paralysis. The discovery of biometallic electricity and the invention of the voltaic battery augmented the interest in the therapeutic effects of galvanism. Afterwards, Duchenne de Boulogne (1806–1875) upgraded the electrotherapy with volta and magnetofaradaic apparatuses. Fortunately, in the past Century, the technological advances and its integration in health sciences have let us go from uncontrolled and unsafe interventions with side effects to well-controlled, more effective and safe stimulation devices [3].

Currently, the most used stimulation devices can be divided into invasive techniques, such as deep brain stimulation (DBS), and non-invasive brain stimulation (NiBS) techniques, whose most representative methods are transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) [4].

Although results are variable [5], DBS has reported positive results over the motor function, especially on the motor symptoms of Parkinson’s disease. However, DBS is a technique that needs the implantation of the electrodes on the stimulated area, which is associated with the typical risk derived from surgery, as infections. Therefore, there is an increasing tendence on the search for non-invasive brain stimulation techniques, which can modulate the motor function avoiding those risks.

Hence, NiBS are characterized for its easy and safe use and relatively cheap price, demonstrating also successful results in the treatment of neurological and psychiatric alterations [4]. In the last decades, TMS has been the most researched and developed neuromodulation technique. TMS generates fast changes in the magnetic field delivering electrical currents through the brain, allowing the specific modulation of the cortical excitability through the initiation of action potentials [6]. Multiple studies have already shown its efficacy and safe use for the treatment of multiple pathologies [7], serving also as a useful tool for the functional location of brain areas, especially regarding the motor cortex [8, 9]. However, TMS requires the participation of the participant, and due to its functioning, it is difficult to perform a sham condition, which is highly desirable especially in the research field. In addition, TMS produces in most of the cases undesirable side-effects, as headache [10].

Therefore, the tDCS technique is attracting a strong interest in the neuroscience research field. tDCS has supposed a revolution in the last 15 years of research, solving most of the disadvantages of TMS [10]. tDCS is a neuromodulation tool consisting on a battery connected to two electrodes, the anode and cathode, which are placed directly over the brain scalp and over extracephalic regions. The current flows between both electrodes and induces the depolarization or hyperpolarization of the membrane of the underlying neurons, which depends of the anodal or cathodal nature of the electrode [11], altering the neuronal excitability resulting in the modification of the brain activity [12]. This device is completely portable, as it is provided by built-in rechargeable battery with duration of approximately 6 h stimulation time at 1 mA (0.5–1.5 W of power consumption), and needs approximately 7 h for complete recharging. In addition, including battery, it has a weight of 0.8 kg. Its portability is one of the biggest advantages of tDCS in the context of NiBS. Therefore, tDCS can be considered as a suitable complementary technique on motor rehabilitation therapy, allowing its application in different contexes, during the motor training and even combined with aerobic exercise [13, 14].

This non-invasive brain manipulation has opened the doors for a variety of potential treatments for the major neurological and psychiatry diseases [15], as depression [16], schizophrenia [17], Obsessive–Compulsive disorder [18] and addictions [19], among others.

However, motor functions are the major target for clinical and non-clinical studies regarding tDCS, serving mainly as a potential tool in post-stroke rehabilitation [20], but also in pathologies like Parkinson’s disease [21]. In addition, numerous studies have shown that tDCS produces changes in the brain plasticity processes, generating long-lasting effects that enhances even further its applicability in the neurorehabilitation field [22, 23].

The purpose of this review is to assess the current and future stage of tDCS regarding its use on the human motor function, identifying the empirical cues that point out its benefits as well as its potential limitation, providing a comprehensive framework for designing future research in the field of brain stimulation with tDCS and human motor rehabilitation. The present review is divided in four parts. The first part is based on a detailed definition on what we know about tDCS, the protocols of montage and parameters of stimulation, comprising the mechanisms of action of tDCS, what differs tDCS from other non-invasive neuromodulation techniques, and the main need to-know safety standards. Given the conciseness of this first part, we will present the recent studies focusing exclusively on the empirical data obtained from the use of tDCS in the human motor function, regarding, in the second part, healthy humans; in the third part, its clinical application on deteriorated human motor functions across different pathologies as Parkinson disease, stroke and cerebral palsy. Finally, in the fourth part of this review, we will discuss the main current issues of tDCS applied on the human motor function.[…]

Continue —> Transcranial direct current stimulation as a motor neurorehabilitation tool: an empirical review | BioMedical Engineering OnLine | Full Text

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[Abstract] Preliminary results of testing the recoveriX system on stroke patients 


Motor imagery based brain-computer interfaces (BCI) extract the movement intentions of subjects in real-time and can be used to control a cursor or medical devices. In the last years, the control of functional electrical stimulation (FES) devices drew researchers’ attention for the post-stroke rehabilitation field. In here, a patient can use the movement imagery to artificially induce movements of the paretic arms through FES in real-time.

Five patients who had a stroke that affected the motor system participated in the current study, and were trained across 10 to 24 sessions lasting about 40 min each with the recoveriX® system. The patients had to imagine 80 left and 80 right hand movements. The electroencephalogram (EEG) data was analyzed with Common Spatial Patterns (CSP) and linear discriminant analysis (LDA) and a feedback was provided in form of a cursor on a computer screen. If the correct imagination was classified, the FES device was also activated to induce the right or left hand movement.

In at least one session, all patients were able to achieve a maximum accuracy above 96%. Moreover, all patients exhibited improvements in motor function. On one hand, the high accuracies achieved within the study show that the patients are highly motivated to participate into a study to improve their lost motor functions. On the other hand, this study reflects the efficacy of combining motor imagination, visual feedback and real hand movement that activates tactile and proprioceptive systems.

Source: O174 Preliminary results of testing the recoveriX system on stroke patients – Clinical Neurophysiology

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[ARTICLE] Neural Engineering for Rehabilitation – BioMed Research International – Full Text PDF

… In this special issue, we provide the eight research articles
showing recent advances in neural engineering for rehabilitation.
We hope that this special issue will further contribute
to promoting the development of neurorehabilitation and
fundamentally providing clinically feasible neurorehabilitative
methods. To this end, more clinical studies with real
patients are especially required to accurately evaluate the
clinical effect of new rehabilitative methods even though
experiments performed with healthy subjects generally show
similar clinical effects.
Han-Jeong Hwang
Do-Won Kim
Janne M. Hahne
Jongsang Son



Neural Engineering for Rehabilitation
Han-Jeong Hwang, Do-Won Kim, Janne M. Hahne, and Jongsang Son
Volume 2017, Article ID 9638098, 2 pages

EEG-Based Computer Aided Diagnosis of AutismSpectrum Disorder UsingWavelet, Entropy, and ANN
Ridha Djemal, Khalil AlSharabi, Sutrisno Ibrahim, and Abdullah Alsuwailem
Volume 2017, Article ID 9816591, 9 pages

Evaluation of a Compact Hybrid Brain-Computer Interface System
Jaeyoung Shin, Klaus-Robert Müller, Christoph H. Schmitz,
Do-Won Kim, and Han-Jeong Hwang
Volume 2017, Article ID 6820482, 11 pages

Patient-Centered Robot-Aided Passive Neurorehabilitation Exercise Based on Safety-Motion Decision-Making Mechanism
Lizheng Pan, Aiguo Song, Suolin Duan, and Zhuqing Yu
Volume 2017, Article ID 4185939, 11 pages

Vowel Imagery Decoding toward Silent Speech BCI Using Extreme Learning Machine with Electroencephalogram
Beomjun Min, Jongin Kim, Hyeong-jun Park, and Boreom Lee
Volume 2016, Article ID 2618265, 11 pages

Integrative Evaluation of Automated Massage Combined withThermotherapy: Physical, Physiological, and Psychological Viewpoints
Do-Won Kim, DaeWoon Lee, Joergen Schreiber, Chang-Hwan Im, and Hansung Kim
Volume 2016, Article ID 2826905, 8 pages

Effect of Anodal-tDCS on Event-Related Potentials: A Controlled Study
Ahmed Izzidien, Sriharasha Ramaraju, Mohammed Ali Roula, and PeterW. McCarthy
Volume 2016, Article ID 1584947, 8 pages

Analysis of the Influence of Complexity and Entropy of Odorant on Fractal Dynamics and Entropy of EEG Signal
Hamidreza Namazi, Amin Akrami, Sina Nazeri, and Vladimir V. Kulish
Volume 2016, Article ID 5469587, 5 pages

Data-Driven User Feedback: An Improved Neurofeedback Strategy considering the Interindividual Variability of EEG Features
Chang-Hee Han, Jeong-Hwan Lim, Jun-Hak Lee, Kangsan Kim, and Chang-Hwan Im
Volume 2016, Article ID 3939815, 7 pages

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[Abstract] Transcranial direct current stimulation over multiple days enhances motor performance of a grip task



Recovery of handgrip is critical after stroke since it is positively related to upper limb function. To boost motor recovery, transcranial direct current stimulation (tDCS) is a promising, non-invasive brain stimulation technique for the rehabilitation of persons with stroke. When applied over the primary motor cortex (M1), tDCS has been shown to modulate neural processes involved in motor learning. However, no studies have looked at the impact of tDCS on the learning of a grip task in both stroke and healthy individuals.


To assess the use of tDCS over multiple days to promote motor learning of a grip task using a learning paradigm involving a speed-accuracy tradeoff in healthy individuals.


In a double-blinded experiment, 30 right-handed subjects (mean age: 22.1 ± 3.3 years) participated in the study and were randomly assigned to an anodal (n = 15) or sham (n = 15) stimulation group. First, subjects performed the grip task with their dominant hand while following the pace of a metronome. Afterwards, subjects trained on the task, at their own pace, over 5 consecutive days while receiving sham or anodal tDCS over M1. After training, subjects performed de novo the metronome-assisted task. The change in performance between the pre and post metronome-assisted task was used to assess the impact of the grip task and tDCS on learning.


Anodal tDCS over M1 had a significant effect on the speed-accuracy tradeoff function. The anodal tDCS group showed significantly greater improvement in performance (39.28 ± 15.92%) than the sham tDCS group (24.06 ± 16.35%) on the metronome-assisted task, t(28) = 2.583, P = 0.015 (effect size d = 0.94).


Anodal tDCS is effective in promoting grip motor learning in healthy individuals. Further studies are warranted to test its potential use for the rehabilitation of fine motor skills in stroke patients.

Source: Transcranial direct current stimulation over multiple days enhances motor performance of a grip task – ScienceDirect

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[ARTICLE] Enhancing the alignment of the preclinical and clinical stroke recovery research pipeline: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable translational working group – Full Text

Stroke recovery research involves distinct biological and clinical targets compared to the study of acute stroke. Guidelines are proposed for the pre-clinical modeling of stroke recovery and for the alignment of pre-clinical studies to clinical trials in stroke recovery.


Moving treatments from the preclinical to the clinical realms is notoriously difficult. For all diseases, only 10% of agents that enter phase 1 trials result in a clinically used drug.1,2 The success rate in stroke and traumatic brain injury is also low and well-documented.35 The translational failure in stroke has been attributed to the narrow therapeutic window and to mistakes such as very broad inclusion criteria, and imprecise, global outcome measures.35 On the preclinical side, depth and rigor of study design, analysis and interpretation have received special focus.

Stroke recovery involves distinct biological principles and a very different time window compared to stroke neuroprotection.68 Unlike acute stroke, post-stroke behavioral activity shapes recovery and can be manipulated to promote recovery, or to negatively interact with recovery.6,9 In addition, stroke recovery involves a unique biology of altered synaptic signaling, enhanced synaptic plasticity and changes in neuronal circuits that provide novel drug and cellular targets but also raise special considerations in clinical translation. The special considerations include: the animal stroke models, the tissue and behavioral outcome measures, imaging biomarkers and conceptual management of the full translational pipeline.

Recent conceptual and technological developments in neuroscience are bringing promising physical, pharmacological and cellular therapies to the field of neurorehabilitation and brain repair. This paper outlines a series of guidelines and recommendations specifically tailored to enhance the quality and rigor of preclinical stroke recovery research.

The task of the translational working group of the Stroke Recovery and Rehabilitation Roundtable (SRRR)10 was to develop a set of guidelines and recommendations appropriate for preclinical stroke recovery research. Existing preclinical stroke research recommendation papers (e.g. STAIR, STEPS) focus chiefly on acute stroke.11,12 Although cognitive impairments and depression are common after stroke,13 the SRRR working groups concluded that these topics require a subsequent roundtable discussion so the emphasis here is on preclinical sensorimotor recovery. The ultimate goal of the translational group was to align preclinical to clinical stroke recovery studies so as to avoid past mistakes and maximize clinical translation.

Continue —> Enhancing the alignment of the preclinical and clinical stroke recovery research pipeline: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable translational working groupInternational Journal of Stroke – Dale Corbett, S Thomas Carmichael, Timothy H Murphy, Theresa A Jones, Martin E Schwab, Jukka Jolkkonen, Andrew N Clarkson, Numa Dancause, Tadeusz Weiloch, Heidi Johansen-Berg, Michael Nilsson, Louise D McCullough, Mary T Joy, 2017

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[ARTICLE] Affordable stroke therapy in high-, low- and middle-income countries: From Theradrive to Rehab CARES, a compact robot gym – Full Text


Affordable technology-assisted stroke rehabilitation approaches can improve access to rehabilitation for low-resource environments characterized by the limited availability of rehabilitation experts and poor rehabilitation infrastructure. This paper describes the evolution of an approach to the implementation of affordable, technology-assisted stroke rehabilitation which relies on low-cost mechatronic/robot devices integrated with off-the-shelf or custom games. Important lessons learned from the evolution and use of Theradrive in the USA and in Mexico are briefly described. We present how a stronger and more compact version of the Theradrive is leveraged in the development of a new low-cost, all-in-one robot gym with four exercise stations for upper and lower limb therapy called Rehab Community-based Affordable Robot Exercise System (Rehab C.A.R.E.S). Three of the exercise stations are designed to accommodate versions of the 1 DOF haptic Theradrive with different custom handles or off-the-shelf commercial motion machine. The fourth station leverages a unique configuration of Wii-boards. Overall, results from testing versions of Theradrive in USA and Mexico in a robot gym suggest that the resulting presentation of the Rehab C.A.R.E.S robot gym can be deployed as an affordable computer/robot-assisted solution for stroke rehabilitation in developed and developing countries.

Non-communicable diseases, especially cardiovascular diseases, are the leading cause of death and disability in the world. An increase in their prevalence often leads to higher incidences of stroke and consequently, an increase in the number of persons living with permanent disability due to stroke.1,2 Stroke is the leading cause of disability worldwide. Over 6.8 million adults live in the USA with disabilities due to a stroke, and by 2030, this number will grow by 4 million.3,4Seventy-five percent of adults recovering from stroke have residual impairment in their limbs, with only about 25% achieving recovery with minor impairments, and only 10% achieving full recovery.57 Greater than 30% are unable to walk without some assistance and 26% remain dependent in activities of daily living.8

The issues influencing rehabilitation outcomes are complex; some examples of these issues are poverty, increase in health costs, short length of stays, insurance limitations, and physical constraints on rehabilitation services (e.g. time).3,6 In low- and middle-income countries (LMIC), rehabilitation outcomes are worse since a disproportionate number of the population is without easy access to rehabilitation technologies, services and skilled clinicians.1,3,9,10 Improved stroke rehabilitation approaches can maximize the functional independence of stroke survivors discharged after inpatient and outpatient services and improve access to rehabilitation for low-resource environments in USA or other LMICs.

Our long-term goal is to develop and use affordable robot technologies to improve access to rehabilitation and ultimately improve the health and function of persons with persistent motor deficits due to a stroke in the USA and worldwide, especially in LMICs where more than 80% of those living with a stroke reside. Specifically, we desire to target stroke survivors who are diagnosed with hemiparesis, are living with severe to moderate motor function impairment, and are without easy access to rehabilitation. Research efforts are needed to develop cost-effective robot devices that can do the above and function in harsher environments characterized by extreme economic hardship (per country), intermittent energy and limited expert supervisors.

Our main approach to delivering rehabilitation has always promoted robot/computer-assisted motivating rehabilitation systems for stroke therapy.31 We have proposed the use and development of mechatronic devices alone or within a suite of devices for upper limb stroke therapy. This paper summarizes lessons learned regarding the delivery of affordable and accessible stroke therapy in HICs and LMICs. We illustrate these lessons via the use of Theradrive, alone (TD-1),2832 its development into a 1DOF Haptic Robot called Haptic Theradrive,3638 a therapy gym in Mexico (TD-2),3335 where Theradrive was one of six devices aimed at improving motor function after stroke. The paper then presents how a stronger and more compact version of the Theradrive is re-designed and leveraged in the development of a new low-cost, all-in-one robot gym called Rehab Community-based Affordable Robot Exercise System (Rehab C.A.R.E.S) with four exercise stations for upper and lower limb therapy. The prototype of the system is described along with strategies for control and new results from testing on exercise station 2. Finally, we discuss implications for deploying such a system in LMICs. […]

Continue —> Affordable stroke therapy in high-, low- and middle-income countries: From Theradrive to Rehab CARES, a compact robot gymJournal of Rehabilitation and Assistive Technologies Engineering – Michelle Jillian Johnson, Roshan Rai, Sarath Barathi, Rochelle Mendonca, Karla Bustamante-Valles, 2017


Figure 1. Theradrive (TD-1), Mexico Theradrive (TD-2), and Haptic Theradrive (TD-3). The Mexico Theradrive has a similar platform to TD-1. Note: Figure 1 used with permission from reference 37.

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[ARTICLE] Update on cell therapy for stroke – Full Text


Ischaemic stroke remains a leading cause of death and disability. Current stroke treatment options aim to minimise the damage from a pending stroke during the acute stroke period using intravenous thrombolytics and endovascular thrombectomy; however, there are no currently approved treatment options for reversing neurological damage once a stroke is completed. Preclinical studies suggest that cell therapy may be safe and effective in improving functional outcomes. Several recent clinical trials have reported safety and some improvement in outcomes following cell therapy administration in ischaemic stroke, which are reviewed. Cell therapy may provide a promising new treatment for stroke reducing stroke-related disability. Further investigation is needed to determine specific effects of cell therapy and to optimise cell delivery methods, cell dosing, type of cells used, timing of delivery, infarct size and location of infarct that are likely to benefit from cell therapy.


Until recently, intravenous recombinant tissue plasminogen activator was the only proven effective treatment for acute stroke. Endovascular thrombectomy has now been added to our arsenal for acute stroke treatment following the publication of five randomised trials demonstrating highly significant treatment effects favouring endovascular therapy.1–6 Outcome data support advancements in acute stroke care and neurorehabilitation with a significant increase in stroke survivors over time.7 However, despite these advancements, stroke remains a leading cause of long-term disability.8 For patients with residual deficits after stroke, we have no currently approved therapy for restoring function.

Cell therapy is one approach to enhancing recovery after stroke. In animal models, delivery of several different types of stem cells reduce infarct size and improve functional outcomes.9 Clinical trials of cell therapy completed in the 2000s mostly treating small cohorts of patients with chronic stroke demonstrated adequate safety and a suggestion of efficacy with the use of cell therapy. Kondziolka and colleagues used N-Tera 2 cells derived from a lung metastasis of a human testicular germ cell tumour that when treated with retinoic acid generate postmitotic neurons that maintain a fetal neuronal phenotype indefinitely in vitro (LBS neurons). LBS neurons were stereotactically implanted around the stroke bed of chronic subcortical ischaemic stroke. This study demonstrated safety and feasibility of stereotactic cell implantation, although there was no significant improvement in functional outcomes.10 11 Using a similar stereotactic approach implanting cells into the basal ganglia, Savitz and colleagues transplanted LGE cells (fetal porcine striatum-derived cells, Genvec) in five patients. Two patients showed improvements, but two patients experienced adverse effects including delayed worsening of neurological symptoms and seizure resulting in early termination of the study.12 Bang and colleagues reported the safety and feasibility of intravenous infusion of autologous mesenchymal stem cells (MSCs) with no reported adverse effects in five patients treated with intravenous MSCs. Although they reported some initial motor improvements, at 12 months, there was no significant difference in motor scores.13 These early clinical trials mostly focused on chronic subcortical strokes, but more recent trials are now investigating cell therapy for treatment of both cortical and subcortical infarcts. This review discusses the considerations for design of cell therapy trials and summarises the results of more recent studies.

Continue —> Update on cell therapy for stroke | Stroke and Vascular Neurology

Table 1

Summary of recent human cell therapy trials for stroke

Clinical trial/sponsor Age Time after stroke Additional selection criteria Cell type Route Stroke location Patients (n) Safety results Efficacy results
MASTERS/Athersys 18–83 24–48 hours NIHSS 8–20, infarct 5-100cc, premorbid mRS 0–1 Multistem adult-derived stem cell product Intravenous Cortical 129 Similar SAE at 1 year 22(34%) versus 24 (39%) placebo,
Lower mortality—5 deaths (8%) versus 9deaths (15%) in placebo19
No effect on 90-day Global Stroke Recovery Assessment (mRS 0–2, NIHSS increase by 75%, Barthel Index >95) but trend towards improved outcome with earlier delivery of cells19
InveST/Department of Biotechnology, India 18–75 7–29 days NIHSS >7, GCS >8, BI <50, paretic arm or leg stable >48 hours Autologous marrow-derived stem cells Intravenous 120
(58 cell therapy)
61 AE (33%) and eight deaths versus 60 AEs (36%) and five deaths placebo22 No effect on 180-day Barthel Index Score, mRS shift or score >3, NIHSS, change of infarct volume22
RECOVER-Stroke/Aldagen 30–75 13–19 days NIHSS 7–22, mRS >3 ALDHbrautologous marrow-derived stem cells Intracarotid infusion distal to ophthalmic Anterior circulation ± subcortical 29 IA, 19 sham 12 SAE IA, 11 SAE sham; 0 cell-related SAE23 No difference in mRS, Barthel, NIHSS at 90 days or 1 year
PISCES-II/ReNeuron 40–89 2–13 months Paretic arm with NIHSS motor arm score 2–3 CTX0E03 DP allogeneic human fetal neural stem cells Stereotaxic infusion into ipsilateral putamen 21 Pending Pending
Sanbio 18–75 6–60 months NIHSS>7, mRS 3–4, stable symptoms>3 weeks SB623 allogeneic marrow-derived stem cells transiently transfected with plasmid encoding Notch122 Stereotaxic infusion peri-infarct Subcortical ± cortical component24 18 28 SAE, 0 cell-related SAE25 Improved ESS at 6 months (p<0.01) and 12 months (p<0.001)
Improved NIHSS at 6 months (p<0.01) and 12 months(p<0.001)
Improved Fugl-Meyer at 6 months (p<0.001) and 12 months(p<0.001)25
PISCES/ReNeuron >60, male only 6–60 months Persistent hemiparesis, Stable NIHSS over 4 weeks (Pt 2 CTX0E03 DP allogeneic human neural stem cells Stereotaxic infusion into putamen Subcortical 11 16 SAE (in nine patients), 0 cell-related SAE28 Improved NIHSS at 2 years (p=0.002), No change, Barthel Index, MMSE, Ashworth, mRS28 29
  • AE, Adverse Event; ARAT, Action Research Arm Test; BI, Barthel Index; DP, drug product; ESS, European Stroke Scale; IA, intra-arterially; MASTERS, Multistem Administration for Stroke Treatment and Enhanced Recovery Study; MMSE, Mini-Mental Status Examination; mRS, modified Rankin Score; NIHSS, National Institutes of Health Stroke Scale; PISCES, Pilot Investigation of Stem Cells in Stroke; SAE, Serious aAverse Events.

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An injury or disease of the central nervous system (CNS) results in significant limitations in the communication with the environment (e.g., mobility, reaching and grasping). Functional electrical stimulation (FES) externally activates the muscles; thus, can restore several motor functions and reduce other health related problems.

This review discusses the major bottleneck in current FES which prevents the wider use and better outcome of the treatment. We present a control method that we continually enhance during more than 30 years in the research and development of assistive systems. The presented control has a multi-level structure where upper levels use finite state control and the lower level implements model based control. We also discuss possible communication channels between the user and the controller of the FES. The artificial controller can be seen as the replica of the biological control. The principle of replication is used to minimize the problems which come from the interplay of biological and artificial control in FES. The biological control relies on an extensive network of neurons sending the output signals to the muscles. The network is being trained though many the trial and error processes in the early childhood, but staying open to changes throughout the life to satisfy the particular needs. The network considers the nonlinear and time variable properties of the motor system and provides adaptation in time and space.

The presented artificial control method implements the same strategy but relies on machine classification, heuristics, and simulation of model-based control. The motivation for writing this review comes from the fact that many control algorithms have been presented in the literature by the authors who do not have much experience in rehabilitation engineering and had never tested the operations with patients.

Almost all of the FES devices available implement only open-loop, sensory triggered preprogrammed sequences of stimulation. The suggestion is that the improvements in the FES devices need better controllers which consider the overall status of the potential user, various effects that stimulation has on afferent and efferent systems, reflexive responses to the FES and direct responses to the FES by non-stimulated sensory-motor systems, and the greater integration of the biological control.

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A. L. Benabid, S. Chabardes, J. Mitrofanis, P. Pollak P. “Deep brain stimulation of the subthalamic nucleus for the treatment of Parkinson’s disease”, The Lancet Neurology, vol. 31, no. 8(1), pp. 67-81. 2009.

J. H. Burridge, M. Haugland, B. Larsen, R. M. Pickering, N. Svaneborg, H. K. Iversen, P. B. Christensen, J. Haase, J. Brennum and T. Sinkjær, “Phase II trial to evaluate the ActiGait implanted drop-foot stimulator in established hemiplegia”, J. Rehabil. Med., vol. 39, pp. 212-218, 2007.

D. G. Everaert, R. B. Stein, G. M. Abrams, A. W. Dromerick, G. E. Francisco, B. J. Hafner, T. N. Huskey, M. C. Munin, K. J. Nolan and C. V. Kufta, “Effect of a foot-drop stimulator and ankle-foot orthosis on walking performance after stroke: a multicenter randomized controlled trial”, Neurorehabil Neural Repair, vol. 27, no. 7, pp. 579-591. 2013.

L. E. Fisher, M. E., Miller, S. N. Bailey, H. A. Jr. Davis, J. S. Anderson, L. R. Murray, D. T. Tyler and R. J. Triolo, “Standing after Spinal Cord Injury with Four-contact Nerve-Cuff Electrodes for Quadriceps Stimulation”, IEEE Trans. Neural. Syst. Rehabil. Eng., vol.16, pp. 473–478, 2008.

T. Keller, M. R. Popović, I. P. I. Papas, P-Y. Muller, “Transcutaneous Functional Electrical Stimulator -Compex Motion”, Artif. Organs, vol. 26, no. 3, pp. 219-223, 2002.

K. L. Kilgore, H. E. Hoyen, A. M. Bryden, R. L. Hart, M. W. Keith and P. H. Peckham, “An Implanted Upper-Extremity Neuroprosthesis Using Myoelectric Control”, J. Hand Surgery, vol. 33, pp. 539-550, 2008.

R. Kobetič, C. S. To, J.R. Schnellenberger, M. L. Audu, T. C. Bulea, R. Gaudio, G. Pinault, S. Tashman and R. J. Triolo, “Development of hybrid orthosis for standing, walking, and stair climbing after spinal cord injury”, J. Rehab. Res. Develop., vol. 46, pp. 447–462, 2009.

A. Kralj, T. Bajd, “Functional Electrical Stimulation: Standing and Walking after Spinal Cord Injury”, Boca Raton, Florida, CRC Press, 1989.

G. E. Loeb, R. A. Peck, W. H. Moore and K. Hood, “BION system for distributed neural prosthetic interfaces”, Med Eng Phys, vol. 23, pp. 9-18, 2001.

N. M. Malešević, L. Popović-Maneski, V. Ilić, N. Jorgovanović, G. Bijelić, T. Keller and D. B. Popović, “A Multi-Pad Electrode based Functional Electrical Stimulation System for Restoration of Grasp”, J. Neuro Eng. Rehabil., vol. 9, no. 66, 2012.

S. Mangold, T. Keller, A. Curt and V. Dietz, “Transcutaneous functional electrical stimulation for grasping in subjects with cervical spinal cord injury”, Spinal Cord, vol. 43, no. 1, pp. 1-3, 2005.

P. H. Peckham and J. S. Knutson, “Functional electrical stimulation for neuromuscular applications”, Annual Review of Biomed. Eng., vol. 7, pp. 327-360, 2005.

D. B. Popović, M. B. Popović, T. Sinkjær, A. Stefanović and L. Schwirtlich, “Therapy of Paretic Arm in Hemiplegic Subjects Augmented with a Neural Prosthesis: A Cross-over study”, Can. J. Physio. Pharmacol., vol. 82, pp. 749-756, 2004.

D. B. Popović, T. Sinkjær and M. B. Popović MB. “Electrical stimulation as a means for achieving recovery of function in stroke patients”, J. NeuroRehab., vol. 25, pp. 45–58, 2009.

D. B. Popović, “Advances in functional electrical stimulation (FES)”. Journal of Electromyography and Kinesiology. vol. 24, no. 6, pp. 795-802, 2014.

A. Prochazka, M. Gauthier, M. Wieler and Z. Kenwell, Z. “The bionic glove: An electrical stimulator garment that provides controlled grasp and hand opening in quadriplegia”, Arch. Phys. Med. Rehabil., vol. 78, no. 6, pp. 608–14, 1997.

R. van den Brand, J. Heutschi, Q. Barraud, J. DiGiovanna, K. Bartholdi, M. Huerlimann, L. Friedli, I. Vollenweider, E. M. Moraud, S. Duis, N. Dominici, S. Micera, P. Musienko and G. Courtine, “Restoring Voluntary Control of Locomotion after Paralyzing Spinal Cord Injury”, Science, vol. 336 no. 6085, pp. 1182-1185, 2012.

V. Visser-Vandewalle, Z. Temel, Ch. van der Linden, L. Ackermans and E. Beuls, “Deep brain stimulation in movement disorders: The applications reconsidered”, Acta Neurologica Belgica, vol. 104, pp. 33-36, 2004. NESS_L300_for_Foot_Drop.php [Accessed, Dec. 2016] NESS_H200_for_Hand_Rehab.php [Accessed, Dec. 2016] Pages/default.aspx [Accessed, Dec. 2016] products/microstim-2v2-kit [Accessed, Dec. 2016] [Accessed, Dec. 2016] xchg/ob_com_en/hs.xsl/4762.html [Accessed, 2016] [Accessed, Dec. 2016]

G. Rizzolatti and G. Luppino, “The cortical motor system”, Neuron, vol. 31, no. 6, pp. 889-901, 2001.

M. Jeannerod, The neural and behavioural organization of goal-directed movements, Clarendon Press/Oxford University Press, 1988.

N. Bernstein, The Co-ordination and Regulation of Movements, Pergamon Press, Oxford (1967)

M. L. Latash, Control of human movement, Human Kinetics, 1993.

D. B. Popović and T. Sinkjær, Control of Movement for the Physically Disabled, London: Springer, 2000.

D. B. Popović, “Control of walking in disabled humans”, Journal of Automatic control, vol. 13(suppl.), pp. 1-38, 2003.

R. Grasso, Y. P. Ivanenko M. Zago, M. Molinari, G. Scivoletto V. Castellano, V, Macellari and F. Lacquaniti,”Distributed plasticity of locomotor pattern generators in spinal cord injured patients”, Brain, vol. 127, no. 5, pp. 1019-10034, 2004.

Y. P. Ivanenko, R. P. Poppele and F. Lacquaniti F, “Five basic muscle activation patterns account for muscle activity during human locomotion”, The Journal of Physiology, vol. 556, pp. 267-282, 2004.

A. Scheiner, J. T. Mortimer and U. Roessmann, “Imbalanced biphasic electrical stimulation: muscle tissue damage”, Annals of Biomed. Eng., vol. 1, no. 18(4), pp. 407-25, 1990.

J. T. Mortimer, “Motor prostheses”, In Handbook of Physiology: The Nervous System, Motor Control. published on line 2011.

T. J. Bajzek and R. J. Jaeger, “Characterization and control of muscle response to electrical stimulation”, Ann. Biomed. Eng., vol. 15, pp. 485–501, 1987.

R. Baratta and M. Solomonow, “The dynamic response model of nine different skeletal muscles”, IEEE Trans. Biomed. Eng., vol. 37, pp. 243–51, 1990.

P. E. Crago, P. H. Peckham and J. T. Mortimer, ”The choice of pulse duration for chronic electrical stimulation via surface, nerve and intramuscular electrodes”, Ann. Biomed. Eng., vol. 2, pp. 252–264, 1974.

P. E. Crago, P. H. Peckham and G. B. Thrope, “Modulation of muscle force by recruitment during intramuscular stimulation”, IEEE Trans. Biomed. Eng,, vol. 27, pp. 679–684, 1980.

J. A. Gruner and C. P. Mason, “Nonlinear muscle recruitment during intramuscular and nerve stimulation.” J Rehabil. Res. Develop., vol. 26, no. 2, pp. 1-16, 1988.

D. B. Popovic, T. Gordon, V. F, Rafuse and A. Prochazka, “Properties of implanted electrodes for functional electrical stimulation”, Annals of Biomed. Eng., vol. 19, no. 3, pp. 303-316, 1991

D. B. Popović and M. B. Popović, “Automatic determination of the optimal shape of the surface electrode: Selective stimulation”, J. Neurosci. Methods, vol. 178, pp. 174-181, 2009.

L. Popović-Maneski, M. Kostić, T. Keller, S. Mitrović, Lj. Konstantinović and D. B. Popović, “Multi-pad electrode for effective grasping: Design”, IEEE Trans. Neur. Sys. Rehabil. Eng., vol. 21, pp. 648-654, 2013.

L. Popović-Maneski, N, Malešević, A. Savić and D. B. Popović, “Spatially distributed asynchronous stimulation delays muscle fatigue”, Muscle & Nerve, vol. 48, pp. 930-937, 2013.

T. Sinkjær, M. Haugland, A. Inmann, M. Hansen and D. K. Nielsen, “Biopotentials as command and feedback signals in functional electrical stimulation systems”, Medical Engineering & Physics, vol. 25, no. 1, pp. 29-40, 2003.

N. Birbaumer, A. R. Murguialday and L. G. Cohen, “Brain-computer-interface (BCI) in paralysis”, The European Image of God and Man, pp. 483-492, Lippincott Williams & Wilkins, 2010.

J.J. Daly, R. Cheng, J. Rogers, K. Litinas, K. Hrovat and M. Dohring, “Feasibility of a new application of noninvasive brain computer interface (BCI): a case study of training for recovery of volitional motor control after stroke”, Journal of Neurologic Physical Therapy, vol. 33, no. 4, pp. 203-11, 2009.

A. H. Do, P. T. Wang, C. E. King, A. Abiri, Z. Nenadic, “Brain-computer interface controlled functional electrical stimulation system for ankle movement”, Journal of Neuroengineering and Rehabilitation, vol. 8, no. 49. 2011.

J. D. Millán, R. Rupp, G. R. Müller-Putz, R. Murray-Smith, C. Giugliemma, M. Tangermann, C. Vidaurre, F. Cincotti, A. Kübler, R. Leeb and C. Neuper, “Combining brain–computer interfaces and assistive technologies: state-of-the-art and challenges”, Frontiers in Neuroscience, vol. 4, 161, 2010.

C. T. Moritz, S. I. Perlmutter, E. E. Fetz, ”Direct control of paralysed muscles by cortical neurons”, Nature, vol. 456 (7222), pp. 639-642, 2008.

G. Pfurtscheller, G. R. Müller-Putz, J. Pfurtscheller and R. Rupp, “EEG-based asynchronous BCI controls functional electrical stimulation in a tetraplegic patient”, EURASIP Journal on Applied Signal Processing, p. 3152-5, 2005.

G. Pfurtscheller G. R. Müller, J. Pfurtscheller, H. J. Gerner and R. Rupp. ”Thought–control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia”, Neuroscience Letters. vol. 351, no. 1, pp. 33-36. 2003.

C. Ethier, E. R. Oby, M. J. Bauman and L. E. Miller, “Restoration of grasp following paralysis through brain-controlled stimulation of muscles” Nature, vol. 485, pp. 368–371, 2012.

A. M. Savić, N. M. Malešević and M. B. Popović, “Feasibility of a Hybrid Brain-Computer Interface for Advanced Functional Electrical Therapy”, Hindawi Publ Corp, Scientific World Journal, Article ID 797128, 2014.

A. B. Schwartz, T. Cui T, D. J. Weber and D. W. Moran, “Brain-Controlled Interfaces: Movement Restoration with Neural Prosthetics”, Neuron, vol. 52, no. 1, pp. 205–220, 2006.

M. Taylor, S. I. Helms Tillery and A. B. Schwartz, “Direct Cortical Control of 3D Neuroprosthetic Devices”, Science, vol. 296 (5574), pp. 1829-1832, 2002.

J. R. Wolpaw, N. Birbaumer, W. J. Heetderks, D. J. McFarland, P.H. Peckham, G. Schalk, E. Donchin, L. A. Quatrano, C. J. Robinson and T. M. Vaughan, “Brain-computer interface technology: a review of the first international meeting”, IEEE Trans. Rehabil. Eng., vol. 8, no. 2, pp. 164-173, 2000.

S. Došen and D. B. Popović, “Transradial prosthesis: artificial vision for control of prehension”, Artificial organs, vol. 35, no. 1, pp. 37-48, 2011.

S. Došen, C. Cipriani, M. Kostić, M. C. Carrozza and D. B. Popović, “Cognitive vision system for the control of a dexterous prosthetic hand: An evaluation study”, Journal of NeuroEngineering and Rehabilitation, on line 7:42, 2010

M. Marković. S. Došen, C. Cipriani, D. B. Popović and D. Farina, “Stereovision and augmented reality for closed-loop control of grasping in hand prostheses”, J. Neural Engineering, vol. 11, no. 4, p. 046001, 2014.

R. Tomović, D. B. Popović and R. B. Stein, Nonanalytical Methods for Motor Control, World Sci Publ, Singapore, 1995.

J. Kojović, M. Djurić-Jovičić, S. Došen, M. B. Popović and D. B. Popović, “Sensor-Driven Four-Channel Stimulation of Paretic Leg: Functional Electrical Walking Therapy”, J. Neurosci.. Methods, vol. 181, pp. 101-105, 2009.

D. B. Popović and M. B. Popović, “Tuning of a Nonanalytic Hierarchical Control System for Reaching with FES”, IEEE Trans. on Biomed. Eng., vol. 45, pp. 203-212, 1998.

M. B. Popović and D. B. Popović, “Cloning Biological Synergies Improved Control of Elbow Neuroprostheses”, IEEE EMB Magazine, vol. 20, no. 1, pp. 74-81, 2001.

M. B. Popović, “Control of neural prostheses for grasping and reaching”, Med. Eng. Phys., vol. 25, no. 1, pp. 41-50, 2003.

D. B. Popović, R. Tomović, D. Tepavac and L. Schwirtlich, “Control aspects of active above-knee prosthesis”, Intern. J Man-machine Studies, vol. 35, no. 6, pp. 751-767, 2001.

D. B. Popović, R. B. Stein, M. N. Oguztoreli, M. Lebiedowska and S. Jonić. “Optimal control of walking with functional electrical stimulation: a computer simulation study”, IEEE Trans. Rehabil. Eng., vol. 7, no. 1, pp. 69-79, 1999.

S. Jonić, T. Janković, V. Gajić and D. B. Popović, “Three machine learning techniques for automatic determination of rules to control locomotion”, IEEE Trans. Biomed. Eng., vol 46, no. 3, p. 10, 1999.

G. Shue, P. E. Crago and H. J Chizeck, “Muscle-joint models incorporating activation dynamics, moment-angle, and moment-velocity properties” IEEE Trans. Biomed. Eng., vol.42, pp. 212-223, 1992.

R. B. Stein, E. P. Zehr, M. K. Lebiedowska, D. B. Popović, A. Scheiner and H. J. Chizeck, “Estimating mechanical parameters of leg segments in individuals with and without physical disabilities” IEEE Trans Rehabil. Eng., vol. 4, pp. 201-211, 1996.

R. Riener and T. Fuhr, “Patient-driven control of FES-supported standing up: a simulation study”, IEEE Trans. Rehabil.Eng., vol. 6, no. 2, pp. 113-124, 1998.

M. Ferrarin, F. Palazzo, R. Riener and J. Quintern, “Model-based control of FES-induced single joint movements”, IEEE Trans. Neural Syst. Rehabi. Eng., vol. 9, no. 3, pp. 245-257, 2001.

Z. Matjacic, K. Hunt, H. Gollee and T. Sinkjaer, “Control of posture with FES systems”, Med. Eng. Phys., vol. 25, no. 1, pp. 51-62, 2003.

D. B. Popović, M. Radulović, L. Schwirtlich and N. Jauković, “Automatic vs. hand-controlled walking of paraplegics”, Med, Eng, Phys., vol. 25, pp. 63-74, 2003.

S. Jezernik, R,G. Wassink and T. Keller, “Sliding mode closed-loop control of FES controlling the shank movement”, IEEE Trans. Biomed. Eng., vol. 51, no. 2, pp. 163-172, 2004.

D. Graupe, “EMG pattern analysis for patient-responsive control of FES in paraplegics for walker-supported walking”, IEEE Trans.Biomed. Eng., vol. 36, no. 7, pp. 711-919, 1989.

C. T Freeman, A. M. Hughes, J. H. Burridge, P. H. Chappell, P. L. Lewin ans E. Rogers, “Iterative learning control of FES applied to the upper extremity for rehabilitation”, Control Engineering Practice, vol. 17, no. 3, pp. 368-381, 2009.

Source: CONTROL OF FUNCTIONAL ELECTRICAL STIMULATION FOR RESTORATION OF MOTOR FUNCTION | Popović | Facta Universitatis, Series: Electronics and Energetics

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