Dataset Information

Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement.

ABSTRACT: Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lacking on its additive effects. Therefore, there is a need for determining the possible success of robotic interventions on selected patients, which in turn determine the necessity for new investigating instruments supporting the treatment decision-making process and customization. The objective of the work presented in this preliminary study was to verify that fully robot assistance would not affect the physiological oscillatory cortical activity related to a functional movement in healthy subjects. Further, the clinical results following the robotic treatment of a chronic stroke patient, who positively reacted to the robotic intervention, were analyzed and discussed. First results show that there is no difference in EEG activation pattern between assisted and no-assisted movement in healthy subjects. Even more importantly, the patient's pretreatment EEG activation pattern in no-assisted movement was completely altered, while it recovered to a quasi-physiological one in robot-assisted movement. The functional improvement following treatment was large. Using pretreatment EEG recording during robot-assisted movement might be a valid approach to assess the potential ability of the patient for recovering.

SUBMITTER: Caimmi M

PROVIDER: S-EPMC4739000 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement.

Caimmi Marco M Visani Elisa E Digiacomo Fabio F Scano Alessandro A Chiavenna Andrea A Gramigna Cristina C Molinari Tosatti Lorenzo L Franceschetti Silvana S Molteni Franco F Panzica Ferruccio F

BioMed research international 20160117

Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lacking on its additive effects. Therefore, there is a need for determining the possible success of robotic interventions on selected patients, which in turn determine the necessity for new investigating instruments supporting the treatment decision-making process and customization. The objective of the work presented in this preliminary study was to ver ...[more]

PMID: 27057546

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Project description:BackgroundHand function is often impaired after stroke, strongly affecting the ability to perform daily activities. Upper limb robotic devices have been developed to complement rehabilitation therapy offered to persons who suffered a stroke, but they rarely focus on the training of hand sensorimotor function. The primary goal of this study was to evaluate whether robot-assisted therapy of hand function following a neurocognitive approach (i.e., combining motor training with somatosensory and cognitive tasks) produces an equivalent decrease in upper limb motor impairment compared to dose-matched conventional neurocognitive therapy, when embedded in the rehabilitation program of inpatients in the subacute stage after stroke.MethodsA parallel-group, randomized controlled trial was conducted on subjects with subacute stroke receiving either conventional or robot-assisted neurocognitive hand therapy using a haptic device. Therapy was provided for 15, 45-min sessions over four weeks, nested within the standard therapy program. Primary outcome was the change from baseline in the upper extremity part of the Fugl-Meyer Assessment (FMA-UE) after the intervention, which was compared between groups using equivalence testing. Secondary outcome measures included upper limb motor, sensory and cognitive assessments, delivered therapy dose, as well as questionnaires on user technology acceptance.ResultsThirty-three participants with stroke were enrolled. 14 subjects in the robot-assisted and 13 subjects in the conventional therapy group completed the study. At the end of intervention, week 8 and week 32, the robot-assisted/conventional therapy group improved by 7.14/6.85, 7.79/7.31, and 8.64/8.08 points on the FMA-UE, respectively, establishing that motor recovery in the robot-assisted group is non-inferior to that in the control group.ConclusionsNeurocognitive robot-assisted therapy of hand function allows for a non-inferior motor recovery compared to conventional dose-matched neurocognitive therapy when performed during inpatient rehabilitation in the subacute stage. This allows the early familiarization of subjects with stroke to the use of such technologies, as a first step towards minimal therapist supervision in the clinic, or directly at home after hospital discharge, to help increase the dose of hand therapy for persons with stroke.Trial registrationEUDAMED database (CIV-13-02-009921), clinicaltrials.gov (NCT02096445). Registered 26 March 2014 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02096445.

Project description:The electroencephalogram (EEG) constitutes a relevant tool to study neural dynamics and to develop brain-machine interfaces (BMI) for rehabilitation of patients with paralysis due to stroke. However, the EEG is easily contaminated by artifacts of physiological origin, which can pollute the measured cortical activity and bias the interpretations of such data. This is especially relevant when recording EEG of stroke patients while they try to move their paretic limbs, since they generate more artifacts due to compensatory activity. In this paper, we study how physiological artifacts (i.e., eye movements, motion artifacts, muscle artifacts and compensatory movements with the other limb) can affect EEG activity of stroke patients. Data from 31 severely paralyzed stroke patients performing/attempting grasping movements with their healthy/paralyzed hand were analyzed offline. We estimated the cortical activation as the event-related desynchronization (ERD) of sensorimotor rhythms and used it to detect the movements with a pseudo-online simulated BMI. Automated state-of-the-art methods (linear regression to remove ocular contaminations and statistical thresholding to reject the other types of artifacts) were used to minimize the influence of artifacts. The effect of artifact reduction was quantified in terms of ERD and BMI performance. The results reveal a significant contamination affecting the EEG, being involuntary muscle activity the main source of artifacts. Artifact reduction helped extracting the oscillatory signatures of motor tasks, isolating relevant information from noise and revealing a more prominent ERD activity. Lower BMI performances were obtained when artifacts were eliminated from the training datasets. This suggests that artifacts produce an optimistic bias that improves theoretical accuracy but may result in a poor link between task-related oscillatory activity and BMI peripheral feedback. With a clinically relevant dataset of stroke patients, we evidence the need of appropriate methodologies to remove artifacts from EEG datasets to obtain accurate estimations of the motor brain activity.

Project description:BackgroundUnsupervised robot-assisted rehabilitation is a promising approach to increase the dose of therapy after stroke, which may help promote sensorimotor recovery without requiring significant additional resources and manpower. However, the unsupervised use of robotic technologies is not yet a standard, as rehabilitation robots often show low usability or are considered unsafe to be used by patients independently. In this paper we explore the feasibility of unsupervised therapy with an upper limb rehabilitation robot in a clinical setting, evaluate the effect on the overall therapy dose, and assess user experience during unsupervised use of the robot and its usability.MethodsSubacute stroke patients underwent a four-week protocol composed of daily 45 min-sessions of robot-assisted therapy. The first week consisted of supervised therapy, where a therapist explained how to interact with the device. The second week was minimally supervised, i.e., the therapist was present but intervened only if needed. After this phase, if participants learnt how to use the device, they proceeded to two weeks of fully unsupervised training. Feasibility, dose of robot-assisted therapy achieved during unsupervised use, user experience, and usability of the device were evaluated. Questionnaires to evaluate usability and user experience were performed after the minimally supervised week and at the end of the study, to evaluate the impact of therapists' absence.ResultsUnsupervised robot-assisted therapy was found to be feasible, as 12 out of the 13 recruited participants could progress to unsupervised training. During the two weeks of unsupervised therapy participants on average performed an additional 360 min of robot-assisted rehabilitation. Participants were satisfied with the device usability (mean System Usability Scale scores > 79), and no adverse events or device deficiencies occurred.ConclusionsWe demonstrated that unsupervised robot-assisted therapy in a clinical setting with an actuated device for the upper limb was feasible and can lead to a meaningful increase in therapy dose. These results support the application of unsupervised robot-assisted therapy as a complement to usual care in clinical settings and pave the way to its application in home settings.Trial registrationRegistered on 13.05.2020 on clinicaltrials.gov (NCT04388891).

Project description:BackgroundAttention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent, complex disorder which is characterized by symptoms of inattention, hyperactivity, and impulsivity. Convergent evidence from neurobiological studies of ADHD identifies dysfunction in fronto-striatal-cerebellar circuitry as the source of behavioural deficits. Recent studies have shown that regions governing basic sensory processing, such as the somatosensory cortex, show abnormalities in those with ADHD suggesting that these processes may also be compromised.MethodsWe used event-related magnetoencephalography (MEG) to examine patterns of cortical rhythms in the primary (SI) and secondary (SII) somatosensory cortices in response to median nerve stimulation, in 9 adults with ADHD and 10 healthy controls. Stimuli were brief (0.2 ms) non-painful electrical pulses presented to the median nerve in two counterbalanced conditions: unpredictable and predictable stimulus presentation. We measured changes in strength, synchronicity, and frequency of cortical rhythms.ResultsHealthy comparison group showed strong event-related desynchrony and synchrony in SI and SII. By contrast, those with ADHD showed significantly weaker event-related desynchrony and event-related synchrony in the alpha (8-12 Hz) and beta (15-30 Hz) bands, respectively. This was most striking during random presentation of median nerve stimulation. Adults with ADHD showed significantly shorter duration of beta rebound in both SI and SII except for when the onset of the stimulus event could be predicted. In this case, the rhythmicity of SI (but not SII) in the ADHD group did not differ from that of controls.ConclusionOur findings suggest that somatosensory processing is altered in individuals with ADHD. MEG constitutes a promising approach to profiling patterns of neural activity during the processing of sensory input (e.g., detection of a tactile stimulus, stimulus predictability) and facilitating our understanding of how basic sensory processing may underlie and/or be influenced by more complex neural networks involved in higher order processing.

Project description:This study applied a comprehensive electroencephalography (EEG) analysis for movement-related cortical potentials (MRCPs) and event-related desynchronization (ERD) in order to understand movement-related brain activity changes during movement preparation and execution stage of unilateral wrist extension. Thirty-four healthy subjects completed two event-related potential tests in the same sequence. Unilateral wrist extension was involved in both tests as the movement task. Instruction Response Movement (IRM) was a brisk movement response task with visual "go" signal, while Cued Instruction Response Movement (CIRM) added a visual cue contenting the direction information to create a prolonged motor preparation stage. Recorded EEG data were segmented and averaged to show time domain changes and then transformed into time-frequency mapping to show the time-frequency changes. All components were calculated and compared among C3, Cz, and C4 locations. The motor potential appeared bilaterally in both tests' movement execution stages, and Cz had the largest peak value among the investigated locations (p < 0.01). In CIRM, a contingent negative variation (CNV) component presented bilaterally during the movement preparation stage with the largest amplitude at Cz. ERD of the mu rhythm (mu ERD) presented bilateral sensorimotor cortices during movement execution stages in both tests and was the smallest at Cz among the investigated locations. In the movement preparation stage of CIRM, mu ERD presented mainly in the contralateral sensory motor cortex area (C3 and C4 for right and left wrist movements, respectively) and showed significant differences between different locations. EEG changes in the time and time-frequency domains showed different topographical features. Movement execution was controlled bilaterally, while movement preparation was controlled mainly by contralateral sensorimotor cortices. Mu ERD was found to have stronger contra-lateralization features in the movement preparation stage and might be a better indicator for detecting movement intentions. This information could be helpful and might provide comprehensive information for studying movement disorders (such as those in post-stroke hemiplegic patients) or for facilitating the development of neuro-rehabilitation engineering technology such as brain computer interface.

Dataset Information

Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement.

Publications

Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement.

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