Rehabilitative devices for a top-down approach

In recent years, neurorehabilitation has moved from a "bottom-up" to a "top down" approach. This change has also involved the technological devices developed for motor and cognitive rehabilitation. It implies that during a task or during therapeutic exercises, new "top-down" approaches are being used to stimulate the brain in a more direct way to elicit plasticity-mediated motor re-learning. This is opposed to "Bottom up" approaches, which act at the physical level and attempt to bring about changes at the level of the central neural system. Areas covered: In the present unsystematic review, we present the most promising innovative technological devices that can effectively support rehabilitation based on a top-down approach, according to the most recent neuroscientific and neurocognitive findings. In particular, we explore if and how the use of new technological devices comprising serious exergames, virtual reality, robots, brain computer interfaces, rhythmic music and biofeedback devices might provide a top-down based approach. Expert commentary: Motor and cognitive systems are strongly harnessed in humans and thus cannot be separated in neurorehabilitation. Recently developed technologies in motor-cognitive rehabilitation might have a greater positive effect than conventional therapies

Post-stroke Rehabilitation of Severe Upper Limb Paresis in Germany – Toward Long-Term Treatment With Brain-Computer Interfaces

Severe upper limb paresis can represent an immense burden for stroke survivors. Given the rising prevalence of stroke, restoration of severe upper limb motor impairment remains a major challenge for rehabilitation medicine because effective treatment strategies are lacking. Commonly applied interventions in Germany, such as mirror therapy and impairment-oriented training, are limited in efficacy, demanding for new strategies to be found. By translating brain signals into control commands of external devices, brain-computer interfaces (BCIs) and brain-machine interfaces (BMIs) represent promising, neurotechnology-based alternatives for stroke patients with highly restricted arm and hand function. In this mini-review, we outline perspectives on how BCI-based therapy can be integrated into the different stages of neurorehabilitation in Germany to meet a long-term treatment approach: We found that it is most appropriate to start therapy with BCI-based neurofeedback immediately after early rehabilitation. BCI-driven functional electrical stimulation (FES) and BMI robotic therapy are well suited for subsequent post hospital curative treatment in the subacute stage. BCI-based hand exoskeleton training can be continued within outpatient occupational therapy to further improve hand function and address motivational issues in chronic stroke patients. Once the rehabilitation potential is exhausted, BCI technology can be used to drive assistive devices to compensate for impaired function. However, there are several challenges yet to overcome before such long-term treatment strategies can be implemented within broad clinical application: 1. developing reliable BCI systems with better usability; 2. conducting more research to improve BCI training paradigms and 3. establishing reliable methods to identify suitable patients

Enhancement of Robot-Assisted Rehabilitation Outcomes of Post-Stroke Patients Using Movement-Related Cortical Potential

Post-stroke rehabilitation is essential for stroke survivors to help them regain independence and to improve their quality of life. Among various rehabilitation strategies, robot-assisted rehabilitation is an efficient method that is utilized more and more in clinical practice for motor recovery of post-stroke patients. However, excessive assistance from robotic devices during rehabilitation sessions can make patients perform motor training passively with minimal outcome. Towards the development of an efficient rehabilitation strategy, it is necessary to ensure the active participation of subjects during training sessions. This thesis uses the Electroencephalography (EEG) signal to extract the Movement-Related Cortical Potential (MRCP) pattern to be used as an indicator of the active engagement of stroke patients during rehabilitation training sessions. The MRCP pattern is also utilized in designing an adaptive rehabilitation training strategy that maximizes patients’ engagement. This project focuses on the hand motor recovery of post-stroke patients using the AMADEO rehabilitation device (Tyromotion GmbH, Austria). AMADEO is specifically developed for patients with fingers and hand motor deficits. The variations in brain activity are analyzed by extracting the MRCP pattern from the acquired EEG data during training sessions. Whereas, physical improvement in hand motor abilities is determined by two methods. One is clinical tests namely Fugl-Meyer Assessment (FMA) and Motor Assessment Scale (MAS) which include FMA-wrist, FMA-hand, MAS-hand movements, and MAS-advanced hand movements’ tests. The other method is the measurement of hand-kinematic parameters using the AMADEO assessment tool which contains hand strength measurements during flexion (force-flexion), and extension (force-extension), and Hand Range of Movement (HROM)

Neuroplastic Changes Following Brain Ischemia and their Contribution to Stroke Recovery: Novel Approaches in Neurorehabilitation

Ischemic damage to the brain triggers substantial reorganization of spared areas and pathways, which is associated with limited, spontaneous restoration of function. A better understanding of this plastic remodeling is crucial to develop more effective strategies for stroke rehabilitation. In this review article, we discuss advances in the comprehension of post-stroke network reorganization in patients and animal models. We first focus on rodent studies that have shed light on the mechanisms underlying neuronal remodeling in the perilesional area and contralesional hemisphere after motor cortex infarcts. Analysis of electrophysiological data has demonstrated brain-wide alterations in functional connectivity in both hemispheres, well beyond the infarcted area. We then illustrate the potential use of non-invasive brain stimulation (NIBS) techniques to boost recovery. We finally discuss rehabilitative protocols based on robotic devices as a tool to promote endogenous plasticity and functional restoration

Advanced technology for gait rehabilitation: An overview

Most gait training systems are designed for acute and subacute neurological inpatients. Many systems are used for relearning gait movements (nonfunctional training) or gait cycle training (functional gait training). Each system presents its own advantages and disadvantages in terms of functional outcomes. However, training gait cycle movements is not sufficient for the rehabilitation of ambulation. There is a need for new solutions to overcome the limitations of existing systems in order to ensure individually tailored training conditions for each of the potential users, no matter the complexity of his or her condition. There is also a need for a new, integrative approach in gait rehabilitation, one that encompasses and addresses all aspects of physical as well as psychological aspects of ambulation in real-life multitasking situations. In this respect, a multidisciplinary multinational team performed an overview of the current technology for gait rehabilitation and reviewed the principles of ambulation training

Technologies and combination therapies for enhancing movement training for people with a disability

There has been a dramatic increase over the last decade in research on technologies for enhancing movement training and exercise for people with a disability. This paper reviews some of the recent developments in this area, using examples from a National Science Foundation initiated study of mobility research projects in Europe to illustrate important themes and key directions for future research. This paper also reviews several recent studies aimed at combining movement training with plasticity or regeneration therapies, again drawing in part from European research examples. Such combination therapies will likely involve complex interactions with motor training that must be understood in order to achieve the goal of eliminating severe motor impairment

Differentiated Effects of Robot Hand Training With and Without Neural Guidance on Neuroplasticity Patterns in Chronic Stroke

Robot-assisted training combined with neural guided strategy has been increasingly applied to stroke rehabilitation. However, the induced neuroplasticity is seldom characterized. It is still uncertain whether this kind of guidance could enhance the long-term training effect for stroke motor recovery. This study was conducted to explore the clinical improvement and the neurological changes after 20-session guided or non-guided robot hand training using two measures: changes in brain discriminant ability between motor-imagery and resting states revealed from electroencephalography (EEG) signals and changes in brain network variability revealed from resting-state functional magnetic resonance imaging (fMRI) data in 24 chronic stroke subjects. The subjects were randomly assigned to receive either combined action observation (AO) with EEG-guided robot-hand training (RobotEEG_AO, n = 13) or robot-hand training without AO and EEG guidance (Robotnon−EEG_Text, n = 11). The robot hand in RobotEEG_AO group was activated only when significant mu suppression (8–12 Hz) was detected from subjects' EEG signals in ipsilesional hemisphere, while the robot hand in Robotnon−EEG_Text group was randomly activated regardless of their EEG signals. Paretic upper-limb motor functions were evaluated at three time-points: before, immediately after and 6 months after the interventions. Only RobotEEG_AO group showed a long-term significant improvement in their upper-limb motor functions while no significant and long-lasting training effect on the paretic motor functions was shown in Robotnon−EEG_Text group. Significant neuroplasticity changes were only observed in RobotEEG_AO group as well. The brain discriminant ability based on the ipsilesional EEG signals significantly improved after intervention. For brain network variability, the whole brain was first divided into six functional subnetworks, and significant increase in the temporal variability was found in four out of the six subnetworks, including sensory-motor areas, attention network, auditory network, and default mode network after intervention. Our results revealed the differences in the long-term training effect and the neuroplasticity changes following the two interventional strategies: with and without neural guidance. The findings might imply that sustainable motor function improvement could be achieved through proper neural guidance, which might provide insights into strategies for effective stroke rehabilitation. Furthermore, neuroplasticity could be promoted more profoundly by the intervention with proper neurofeedback, and might be shaped in relation to better motor skill acquisition

Computational neurorehabilitation: modeling plasticity and learning to predict recovery

Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling – regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity

Effectiveness of intensive physiotherapy for gait improvement in stroke: systematic review

Introduction: Stroke is one of the leading causes of functional disability worldwide. Approximately 80% of post-stroke subjects have motor changes. Improvement of gait pattern is one of the main objectives of physiotherapists intervention in these cases. The real challenge in the recovery of gait after stroke is to understand how the remaining neural networks can be modified, to be able to provide response strategies that compensate for the function of the affected structures. There is evidence that intensive training, including physiotherapy, positively influences neuroplasticity, improving mobility, pattern and gait velocity in post-stroke recovery. Objectives: Review and analyze in a systematic way the experimental studies (RCT) that evaluate the effects of Intensive Physiotherapy on gait improvement in poststroke subjects. Methodology: Were only included all RCT performed in humans, without any specific age, that had a clinical diagnosis of stroke at any stage of evolution, with sensorimotor deficits and functional gait changes. The databases used were: Pubmed, PEDro (Physiotherapy Evidence Database) and CENTRAL (Cochrane Center Register of Controlled Trials). Results: After the application of the criteria, there were 4 final studies that were included in the systematic review. 3 of the studies obtained a score of 8 on the PEDro scale and 1 obtained a score of 4. The fact that there is clinical and methodological heterogeneity in the studies evaluated, supports the realization of the current systematic narrative review, without meta-analysis. Discussion: Although the results obtained in the 4 studies are promising, it is important to note that the significant improvements that have been found, should be carefully considered since pilot studies with small samples, such as these, are not designed to test differences between groups, in terms of the effectiveness of the intervention applied. Conclusion: Intensive Physiotherapy seems to be safe and applicable in post-stroke subjects and there are indications that it is effective in improving gait, namely speed, travelled distance and spatiotemporal parameters. However, there is a need to develop more RCTs with larger samples and that evaluate the longterm resultsN/

Comfort of two shoulder actuation mechanisms for arm therapy exoskeletons: a comparative study in healthy subjects

Robotic exoskeletons can be used to study and treat patients with neurological impairments. They can guide and support the human limb over a large range of motion, which requires that the movement trajectory of the exoskeleton coincide with the one of the human arm. This is straightforward to achieve for rather simple joints like the elbow, but very challenging for complex joints like the human shoulder, which is comprised by several bones and can exhibit a movement with multiple rotational and translational degrees of freedom. Thus, several research groups have developed different shoulder actuation mechanism. However, there are no experimental studies that directly compare the comfort of two different shoulder actuation mechanisms. In this study, the comfort and the naturalness of the new shoulder actuation mechanism of the ARMin III exoskeleton are compared to a ball-and-socket-type shoulder actuation. The study was conducted in 20 healthy subjects using questionnaires and 3D-motion records to assess comfort and naturalness. The results indicate that the new shoulder actuation is slightly better than a ball-and-socket-type actuation. However, the differences are small, and under the tested conditions, the comfort and the naturalness of the two tested shoulder actuations do not differ a lo