Activity-Dependent Neurorehabilitation Beyond Physical Trainings: "Mental Exercise" Through Mirror Neuron Activation

The activity dependent brain repair mechanism has been widely adopted in many types of neurorehabilitation. The activity leads to target specific and non-specific beneficial effects in different brain regions, such as the releasing of neurotrophic factors, modulation of the cytokines and generation of new neurons in adult hood. However physical exercise program clinically are limited to some of the patients with preserved motor functions; while many patients suffered from paralysis cannot make such efforts. Here the authors proposed the employment of mirror neurons system in promoting brain rehabilitation by "observation based stimulation". Mirror neuron system has been considered as an important basis for action understanding and learning by mimicking others. During the action observation, mirror neuron system mediated the direct activation of the same group of motor neurons that are responsible for the observed action. The effect is clear, direct, specific and evolutionarily conserved. Moreover, recent evidences hinted for the beneficial effects on stroke patients after mirror neuron system activation therapy. Finally some music-relevant therapies were proposed to be related with mirror neuron system.

Challenges and opportunities for robot-mediated neurorehabilitation

Robot-mediated neurorehabilitation is a rapidly advancing field that seeks to use advances in robotics, virtual realities, and haptic interfaces, coupled with theories in neuroscience and rehabilitation to define new methods for treating neurological injuries such as stroke, spinal cord injury, and traumatic brain injury. The field is nascent and much work is needed to identify efficient hardware, software, and control system designs alongside the most effective methods for delivering treatment in home and hospital settings. This paper identifies the need for robots in neurorehabilitation and identifies important goals that will allow this field to advance.

Assessing the effectiveness of robot facilitated neurorehabilitation for relearning motor skills following a stroke

A growing awareness of the potential for machine-mediated neurorehabilitation has led to several novel concepts for delivering these therapies. To get from laboratory demonstrators and prototypes to the point where the concepts can be used by clinicians in practice still requires significant additional effort, not least in the requirement to assess and measure the impact of any proposed solution. To be widely accepted a study is required to use validated clinical measures but these tend to be subjective, costly to administer and may be insensitive to the effect of the treatment. Although this situation will not change, there is good reason to consider both clinical and mechanical assessments of recovery. This article outlines the problems in measuring the impact of an intervention and explores the concept of providing more mechanical assessment techniques and ultimately the possibility of combining the assessment process with aspects of the intervention.

The role of corticospinal tract damage in chronic motor recovery and neurorehabilitation: a pilot study

Background. With diffusion-tensor imaging (DTi) it is possible to estimate the structural characteristics of fiber bundles in vivo. This study used DTi to infer damage to the corticospinal tract (CST) and relates this parameter to (a) the level of residual motor ability at least 1 year poststroke and (b) the outcome of intensive motor rehabilitation with constraint-induced movement therapy (CIMT). Objective. To explore the role of CST damage in recovery and CIMT efficacy. Methods. Ten patients with low-functioning hemiparesis were scanned and tested at baseline, before and after CIMT. Lesion overlap with the CST was indexed as reduced anisotropy compared with a CST variability map derived from 26 controls. Residual motor ability was measured through the Wolf Motor Function Test (WMFT) and the Motor Activity Log (MAL) acquired at baseline. CIMT benefit was assessed through the pre—post treatment comparison of WMFT and MAL performance. Results. Lesion overlap with the CST correlated with residual motor ability at baseline, with greater deficits observed in patients with more extended CST damage. Infarct volume showed no systematic association with residual motor ability. CIMT led to significant improvements in motor function but outcome was not associated with the extent of CST damage or infarct volume. Conclusion. The study gives in vivo support for the proposition that structural CST damage, not infarct volume, is a major predictor for residual functional ability in the chronic state. The results provide initial evidence for positive effects of CIMT in patients with varying, including more severe, CST damage.

Apraxia in neurorehabilitation: Classification, assessment and treatment

Apraxia is a higher-order motor disorder impairing the ability to correctly perform skilled, purposive movements as the result of neurological disorders most commonly stroke, dementia and movement disorders. It is increasingly recognised that apraxia negatively influences activities of daily living (ADL). Early diagnosis and treatment should be part of the neurorehabilitation programme. The aim of the present article is to describe the most important subtypes of apraxia such as ideational and ideomotor apraxia as well as their impact on ADL and outcome. Furthermore, the relationship to associated disorders such as aphasia is discussed. Finally, strategies concerning assessment, management and treatment of the disorder are presented.

Robot-aided neurorehabilitation of the upper extremities

Task-oriented repetitive movements can improve muscle strength and movement co-ordination in patients with impairments due to neurological lesions. The application of robotics and automation technology can serve to assist, enhance, evaluate and document the rehabilitation of movements. The paper provides an overview of existing devices that can support movement therapy of the upper extremities in subjects with neurological pathologies. The devices are critically compared with respect to technical function, clinical applicability, and, if they exist, clinical outcomes.

Upper Limb Portable Motion Analysis System Based on Inertial Technology for Neurorehabilitation Purposes

Here an inertial sensor-based monitoring system for measuring and analyzing upper limb movements is presented. The final goal is the integration of this motion-tracking device within a portable rehabilitation system for brain injury patients. A set of four inertial sensors mounted on a special garment worn by the patient provides the quaternions representing the patient upper limb’s orientation in space. A kinematic model is built to estimate 3D upper limb motion for accurate therapeutic evaluation. The human upper limb is represented as a kinematic chain of rigid bodies with three joints and six degrees of freedom. Validation of the system has been performed by co-registration of movements with a commercial optoelectronic tracking system. Successful results are shown that exhibit a high correlation among signals provided by both devices and obtained at the Institut Guttmann Neurorehabilitation Hospital.

Inverse kinematics of a 6 DoF human upper limb using ANFIS and ANN for anticipatory actuation in ADL-based physical Neurorehabilitation

Objective: This research is focused in the creation and validation of a solution to the inverse kinematics problem for a 6 degrees of freedom human upper limb. This system is intended to work within a realtime dysfunctional motion prediction system that allows anticipatory actuation in physical Neurorehabilitation under the assisted-as-needed paradigm. For this purpose, a multilayer perceptron-based and an ANFIS-based solution to the inverse kinematics problem are evaluated. Materials and methods: Both the multilayer perceptron-based and the ANFIS-based inverse kinematics methods have been trained with three-dimensional Cartesian positions corresponding to the end-effector of healthy human upper limbs that execute two different activities of the daily life: "serving water from a jar" and "picking up a bottle". Validation of the proposed methodologies has been performed by a 10 fold cross-validation procedure. Results: Once trained, the systems are able to map 3D positions of the end-effector to the corresponding healthy biomechanical configurations. A high mean correlation coefficient and a low root mean squared error have been found for both the multilayer perceptron and ANFIS-based methods. Conclusions: The obtained results indicate that both systems effectively solve the inverse kinematics problem, but, due to its low computational load, crucial in real-time applications, along with its high performance, a multilayer perceptron-based solution, consisting in 3 input neurons, 1 hidden layer with 3 neurons and 6 output neurons has been considered the most appropriated for the target application.

Cognitive neurorehabilitation based on interactive video technology

Cognitive impairment is the main cause of disability in developed societies. New interactive technologies help therapists in neurorehabilitation in order to increase patients’ autonomy and quality of life. This work proposes Interactive Video (IV) as a technology to develop cognitive rehabilitation tasks based on Activities of Daily Living (ADL). ADL cognitive task has been developed and integrated with eye-tracking technology for task interaction and patients’ performance monitoring.

Depth sensors-based upper limb motion capture system for functional neurorehabilitation

Versatile and accurate motion capture systems, with the required properties to be integrated within both clinical and domiciliary environments, would represent a significant advance in following the progress of the patients as well as in allowing the incorporation of new data exploitation and analysis methods to enhance the functional neurorehabilitation therapeutic processes. Besides, these systems would permit the later development of new applications focused on the automatization of the therapeutic tasks in order to increase the therapist/patient ratio, thus decreasing the costs [1]. However, current motion capture systems are not still ready to work within uncontrolled environments.

Dysfunctional profile for patients in physical neurorehabilitation of upper limb

This paper proposes a first approach to Objective Motor Assessment (OMA) methodology. Also, it introduces the Dysfunctional profile (DP) concept. DP consists of a data matrix characterizing the Upper Limb (UL) physical alterations of a patient with Acquired Brain Injury (ABI) during the rehabilitation process. This research is based on the comparison methology of UL movement between subjects with ABI and healthy subjects as part of OMA. The purpose of this comparison is to classify subjects according to their motor control and subsequently issue a functional assessment of the movement. For this purpose Artificial Neural Networks (ANN) have been used to classify patients. Different network structures are tested. The obtained classification accuracy was 95.65%. This result allows the use of ANNs as a viable option for dysfunctional assessment. This work can be considered a pilot study for further research to corroborate these results.

Monitoring visual attention on a neurorehabilitation environment based on interactive video

The use of new technologies in neurorehabilitation has led to higher intensity rehabilitation processes, extending therapies in an economically sustainable way. Interactive Video (IV) technology allows therapists to work with virtual environments that reproduce real situations. In this way, patients deal with Activities of the Daily Living (ADL) immersed within enhanced environments [1]. These rehabilitation exercises, which focus in re-learning lost functions, will try to modulate the neural plasticity processes [2]. This research presents a system where a neurorehabilitation IV-based environment has been integrated with an eye-tracker device in order to monitor and to interact using visual attention. While patients are interacting with the neurorehabilitation environment, their visual behavior is closely related with their cognitive state, which in turn mirrors the brain damage condition suffered by them [3] [4]. Patients’ gaze data can provide knowledge on their attention focus and their cognitive state, as well as on the validity of the rehabilitation tasks proposed [5].

Use of Biological Motion based Cues and Ecological Sounds in the Neurorehabilitation of Apraxia

Technological progress in the area of informatics and human interface platforms create a window of opportunities for the neurorehablitation of patients with motor impairments. The CogWatch project (www.cogwatch.eu) aims to create an intelligent assistance system to improve motor planning and execution in patients with apraxia during their daily activities. Due to the brain damage caused by cardiovascular incident these patients suffer from impairments in the ability to use tools, and to sequence actions during daily tasks (such as making breakfast). Based on the common coding theory (Hommel et al., 2001) and mirror neuron primate research (Rizzolatti et al., 2001) we aim to explore use of cues, which incorporate aspects of biological motion from healthy adults performing everyday tasks requiring tool use and ecological sounds linked to the action goal. We hypothesize that patients with apraxia will benefit from supplementary sensory information relevant to the task, which will reinforce the selection of the appropriate motor plan. Findings from this study determine the type of sensory guidance in the CogWatch interface. Rationale for the experimental design is presented and the relevant literature is discussed.

Real-time functional magnetic resonance imaging neurofeedback in motor neurorehabilitation

Purpose of review Recent developments in functional magnetic resonance imaging (fMRI) have catalyzed a new field of translational neuroscience. Using fMRI to monitor the aspects of task-related changes in neural activation or brain connectivity, investigators can offer feedback of simple or complex neural signals/patterns back to the participant on a quasireal-time basis [real-time-fMRI-based neurofeedback (rt-fMRI-NF)]. Here, we introduce some background methodology of the new developments in this field and give a perspective on how they may be used in neurorehabilitation in the future. Recent findings The development of rt-fMRI-NF has been used to promote self-regulation of activity in several brain regions and networks. In addition, and unlike other noninvasive techniques, rt-fMRI-NF can access specific subcortical regions and in principle any region that can be monitored using fMRI including the cerebellum, brainstem and spinal cord. In Parkinson’s disease and stroke, rt-fMRI-NF has been demonstrated to alter neural activity after the self-regulation training was completed and to modify specific behaviours. Summary Future exploitation of rt-fMRI-NF could be used to induce neuroplasticity in brain networks that are involved in certain neurological conditions. However, currently, the use of rt-fMRI-NF in randomized, controlled clinical trials is in its infancy.