Browsing by Keyword "Neurology"
Now showing 1 - 20 of 27
Results Per Page
Sort Options
Item Brain connectivity and cognitive functioning in individuals six months after multiorgan failure(2020) Jimenez-Marin, Antonio; Rivera, Diego; Boado, Victoria; Diez, Ibai; Labayen, Fermin; Garrido, Irati; Ramos-Usuga, Daniela; Benito-Sánchez, Itziar; Rasero, Javier; Cabrera-Zubizarreta, Alberto; Gabilondo, Iñigo; Stramaglia, Sebastiano; Arango-Lasprilla, Juan Carlos; Cortes, Jesus M.; Tecnalia Research & InnovationMultiorgan failure (MOF) is a life-threating condition that affects two or more systems of organs not involved in the disorder that motivates admission to an Intensive Care Unit (ICU). Patients who survive MOF frequently present long-term functional, neurological, cognitive, and psychiatric sequelae. However, the changes to the brain that explain such symptoms remain unclear. Objective: To determine brain connectivity and cognitive functioning differences between a group of MOF patients six months after ICU discharge and healthy controls (HC). Methods: 22 MOF patients and 22 HC matched by age, sex, and years of education were recruited. Both groups were administered a 3T magnetic resonance imaging (MRI), including structural T1 and functional BOLD, as well as a comprehensive neuropsychological evaluation that included tests of learning and memory, speed of information processing and attention, executive function, visual constructional abilities, and language. Voxel-based morphometry was used to analyses T1 images. For the functional data at rest, functional connectivity (FC) analyses were performed. Results: There were no significant differences in structural imaging and neuropsychological performance between groups, even though patients with MOF performed worse in all the cognitive tests. Functional neuroimaging in the default mode network (DMN) showed hyper-connectivity towards sensory-motor, cerebellum, and visual networks. DMN connectivity had a significant association with the severity of MOF during ICU stay and with the neuropsychological scores in tests of attention and visual constructional abilities. Conclusions: In MOF patients without structural brain injury, DMN connectivity six months after ICU discharge is associated with MOF severity and neuropsychological impairment, which supports the use of resting-state functional MRI as a potential tool to predict the onset of long-term cognitive deficits in these patients. Similar to what occurs at the onset of other pathologies, the observed hyper-connectivity might suggest network re-adaptation following MOF.Item Brain oscillatory activity as a biomarker of motor recovery in chronic stroke(2020-04-01) Ray, Andreas M.; Figueiredo, Thiago D. C.; López‐Larraz, Eduardo; Birbaumer, Niels; Ramos‐Murguialday, Ander; López-Larraz, Eduardo; Ramos-Murguialday, Ander; Medical TechnologiesIn the present work, we investigated the relationship of oscillatory sensorimotor brain activity to motor recovery. The neurophysiological data of 30 chronic stroke patients with severe upper‐limb paralysis are the basis of the observational study presented here. These patients underwent an intervention including movement training based on combined brain–machine interfaces and physiotherapy of several weeks recorded in a double‐blinded randomized clinical trial. We analyzed the alpha oscillations over the motor cortex of 22 of these patients employing multilevel linear predictive modeling. We identified a significant correlation between the evolution of the alpha desynchronization during rehabilitative intervention and clinical improvement. Moreover, we observed that the initial alpha desynchronization conditions its modulation during intervention: Patients showing a strong alpha desynchronization at the beginning of the training improved if they increased their alpha desynchronization. Patients showing a small alpha desynchronization at initial training stages improved if they decreased it further on both hemispheres. In all patients, a progressive shift of desynchronization toward the ipsilesional hemisphere correlates significantly with clinical improvement regardless of lesion location. The results indicate that initial alpha desynchronization might be key for stratification of patients undergoing BMI interventions and that its interhemispheric balance plays an important role in motor recovery.Item Brain-computer interface in paralysis(2008-12) Birbaumer, Niels; Murguialday, Ander Ramos; Cohen, Leonardo; Medical TechnologiesPurpose of review: Communication with patients suffering from locked-in syndrome and other forms of paralysis is an unsolved challenge. Movement restoration for patients with chronic stroke or other brain damage also remains a therapeutic problem and available treatments do not offer significant improvements. This review considers recent research in brain-computer interfaces (BCIs) as promising solutions to these challenges. Recent findings: Experimentation with nonhuman primates suggests that intentional goal directed movements of the upper limbs can be reconstructed and transmitted to external manipulandum or robotic devices controlled from a relatively small number of microelectrodes implanted into movement-relevant brain areas after some training, opening the door for the development of BCI or brain-machine interfaces in humans. Although noninvasive BCIs using electroencephalographic recordings or event-related-brain-potentials in healthy individuals and patients with amyotrophic lateral sclerosis or stroke can transmit up to 80 bits/min of information, the use of BCIs - invasive or noninvasive - in severely or totally paralyzed patients has met some unforeseen difficulties. Summary: Invasive and noninvasive BCIs using recordings from nerve cells, large neuronal pools such as electrocorticogram and electroencephalography, or blood flow based measures such as functional magnetic resonance imaging and near-infrared spectroscopy show potential for communication in locked-in syndrome and movement restoration in chronic stroke, but controlled phase III clinical trials with larger populations of severely disturbed patients are urgently needed.Item Brain-computer interface in stroke: A review of progress(2011-10) Silvoni, Stefano; Ramos-Murguialday, Ander; Cavinato, Marianna; Volpato, Chiara; Cisotto, Giulia; Turolla, Andrea; Piccione, Francesco; Birbaumer, Niels; Medical TechnologiesBrain-computer interface (BCI) technology has been used for rehabilitation after stroke and there are a number of reports involving stroke patients in BCI-feedback training. Most publications have demonstrated the efficacy of BCI technology in post-stroke rehabilitation using output devices such as Functional Electrical Stimulation, robot, and orthosis. The aim of this review is to focus on the progress of BCI-based rehabilitation strategies and to underline future challenges. A brief history of clinical BCI-approaches is presented focusing on stroke motor rehabilitation. A context for three approaches of a BCI-based motor rehabilitation program is outlined: the substitutive strategy, classical conditioning and operant conditioning. Furthermore, we include an overview of a pilot study concerning a new neuro-forcefeedback strategy. This pilot study involved healthy participants. Finally we address some challenges for future BCI-based rehabilitation.Item Brain-machine interface in chronic stroke rehabilitation: A controlled study(2013-07) Ramos-Murguialday, Ander; Broetz, Doris; Rea, Massimiliano; Läer, Leonhard; Yilmaz, Özge; Brasil, Fabricio L.; Liberati, Giulia; Curado, Marco R.; Garcia-Cossio, Eliana; Vyziotis, Alexandros; Cho, Woosang; Agostini, Manuel; Soares, Ernesto; Soekadar, Surjo; Caria, Andrea; Cohen, Leonardo G.; Birbaumer, Niels; Medical TechnologiesObjective Chronic stroke patients with severe hand weakness respond poorly to rehabilitation efforts. Here, we evaluated efficacy of daily brain-machine interface (BMI) training to increase the hypothesized beneficial effects of physiotherapy alone in patients with severe paresis in a double-blind sham-controlled design proof of concept study. Methods Thirty-two chronic stroke patients with severe hand weakness were randomly assigned to 2 matched groups and participated in 17.8 ± 1.4 days of training rewarding desynchronization of ipsilesional oscillatory sensorimotor rhythms with contingent online movements of hand and arm orthoses (experimental group, n = 16). In the control group (sham group, n = 16), movements of the orthoses occurred randomly. Both groups received identical behavioral physiotherapy immediately following BMI training or the control intervention. Upper limb motor function scores, electromyography from arm and hand muscles, placebo-expectancy effects, and functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent activity were assessed before and after intervention. Results A significant group × time interaction in upper limb (combined hand and modified arm) Fugl-Meyer assessment (cFMA) motor scores was found. cFMA scores improved more in the experimental than in the control group, presenting a significant improvement of cFMA scores (3.41 ± 0.563-point difference, p = 0.018) reflecting a clinically meaningful change from no activity to some in paretic muscles. cFMA improvements in the experimental group correlated with changes in fMRI laterality index and with paretic hand electromyography activity. Placebo-expectancy scores were comparable for both groups. Interpretation The addition of BMI training to behaviorally oriented physiotherapy can be used to induce functional improvements in motor function in chronic stroke patients without residual finger movements and may open a new door in stroke neurorehabilitation. NEUROL 2013;74:100-108Item Brain-Machine Interface in Chronic Stroke: Randomized Trial Long-Term Follow-up(2019-03) Ramos-Murguialday, Ander; Curado, Marco R.; Broetz, Doris; Yilmaz, Özge; Brasil, Fabricio L.; Liberati, Giulia; Garcia-Cossio, Eliana; Cho, Woosang; Caria, Andrea; Cohen, Leonardo G.; Birbaumer, Niels; Medical TechnologiesBackground. Brain-machine interfaces (BMIs) have been recently proposed as a new tool to induce functional recovery in stroke patients. Objective. Here we evaluated long-term effects of BMI training and physiotherapy in motor function of severely paralyzed chronic stroke patients 6 months after intervention. Methods. A total of 30 chronic stroke patients with severe hand paresis from our previous study were invited, and 28 underwent follow-up assessments. BMI training included voluntary desynchronization of ipsilesional EEG-sensorimotor rhythms triggering paretic upper-limb movements via robotic orthoses (experimental group, n = 16) or random orthoses movements (sham group, n = 12). Both groups received identical physiotherapy following BMI sessions and a home-based training program after intervention. Upper-limb motor assessment scores, electromyography (EMG), and functional magnetic resonance imaging (fMRI) were assessed before (Pre), immediately after (Post1), and 6 months after intervention (Post2). Results. The experimental group presented with upper-limb Fugl-Meyer assessment (cFMA) scores significantly higher in Post2 (13.44 ± 1.96) as compared with the Pre session (11.16 ± 1.73; P =.015) and no significant changes between Post1 and Post2 sessions. The Sham group showed no significant changes on cFMA scores. Ashworth scores and EMG activity in both groups increased from Post1 to Post2. Moreover, fMRI-BOLD laterality index showed no significant difference from Pre or Post1 to Post2 sessions. Conclusions. BMI-based rehabilitation promotes long-lasting improvements in motor function of chronic stroke patients with severe paresis and represents a promising strategy in severe stroke neurorehabilitation.Item Chronic stroke recovery after combined BCI training and physiotherapy: A case report(2011-04) Caria, Andrea; Weber, Cornelia; Brötz, Doris; Ramos, Ander; Ticini, Luca F.; Gharabaghi, Alireza; Braun, Christoph; Birbaumer, Niels; Medical TechnologiesA case of partial recovery after stroke and its associated brain reorganization in a chronic patient after combined brain computer interface (BCI) training and physiotherapy is presented. A multimodal neuroimaging approach based on fMRI and diffusion tensor imaging was used to investigate plasticity of the brain motor system in parallel with longitudinal clinical assessments. A convergent association between functional and structural data in the ipsilesional premotor areas was observed. As a proof of concept investigation, these results encourage further research on a specific role of BCI on brain plasticity and recovery after stroke.Item Consensus-Based Core Set of Outcome Measures for Clinical Motor Rehabilitation After Stroke—A Delphi Study(2020-09-02) Pohl, Johannes; Held, Jeremia Philipp Oskar; Verheyden, Geert; Alt Murphy, Margit; Engelter, Stefan; Flöel, Agnes; Keller, Thierry; Kwakkel, Gert; Nef, Tobias; Ward, Nick; Luft, Andreas Rüdiger; Veerbeek, Janne Marieke; Tecnalia Research & InnovationIntroduction: Outcome measures are key to tailor rehabilitation goals to the stroke patient’s individual needs and to monitor poststroke recovery. The large number of available outcome measures leads to high variability in clinical use. Currently, an internationally agreed core set of motor outcome measures for clinical application is lacking. Therefore, the goal was to develop such a set to serve as a quality standard in clinical motor rehabilitation poststroke. Methods: Outcome measures for the upper and lower extremities, and activities of daily living (ADL)/stroke-specific outcomes were identified and presented to stroke rehabilitation experts in an electronic Delphi study. In round 1, clinical feasibility and relevance of the outcome measures were rated on a 7-point Likert scale. In round 2, those rated at least as “relevant” and “feasible” were ranked within the body functions, activities, and participation domains of the International Classification of Functioning, Disability, and Health (ICF). Furthermore, measurement time points poststroke were indicated. In round 3, answers were reviewed in reference to overall results to reach final consensus.Item Corrigendum: Consensus-Based Core Set of Outcome Measures for Clinical Motor Rehabilitation After Stroke—A Delphi Study (Frontiers in Neurology, (2020), 11, (875), 10.3389/fneur.2020.00875)(2021-05-27) Pohl, Johannes; Held, Jeremia Philipp Oskar; Verheyden, Geert; Alt Murphy, Margit; Engelter, Stefan; Flöel, Agnes; Keller, Thierry; Kwakkel, Gert; Nef, Tobias; Ward, Nick; Luft, Andreas Rüdiger; Veerbeek, Janne Marieke; Tecnalia Research & InnovationIn the original article, there was a mistake in Table 2 as published. Important asterisks that were explained in the tables caption were not inserted in the table (second row, second and third columns). There is also an incorrect abbreviation (FMMA instead of FMA, in the second row, second column). The corrected Table 2 appears below. In the original article, there was a mistake in Table 3 as published. Important footnotes (1) and (2), that were further explained in the table’s caption, were not inserted in the table. The corrected Table 3 appears below. The authors apologize for these errors and state that they do not change the scientific conclusions of the article in any way. The original article has been updated. (Table presented.).Item Cortex integrity relevance in muscle synergies in severe chronic stroke(2014-09-23) García-Cossio, Eliana; Broetz, Doris; Birbaumer, Niels; Ramos-Murguialday, Ander; Medical TechnologiesBackground: Recent experimental evidence has indicated that the motor system coordinates muscle activations through a linear combination of muscle synergies that are specified at the spinal or brainstem networks level. After stroke upper limb impairment is characterized by abnormal patterns of muscle activations or synergies.Objective: This study aimed at characterizing the muscle synergies in severely affected chronic stroke patients. Furthermore, the influence of integrity of the sensorimotor cortex on synergy modularity and its relation with motor impairment was evaluated. Methods: Surface electromyography from 33 severely impaired chronic stroke patients was recorded during 6 bilateral movements. Muscle synergies were extracted and synergy patterns were correlated with motor impairment scales. Results: Muscle synergies extracted revealed different physiological patterns dependent on the preservation of the sensorimotor cortex. Patients without intact sensorimotor cortex showed a high preservation of muscle synergies. On the contrary, patients with intact sensorimotor cortex showed poorer muscle synergies preservation and an increase in new generated synergies. Furthermore, the preservation of muscle synergies correlated positively with hand functionality in patients with intact sensorimotor cortex and subcortical lesions only. Conclusion: Our results indicate that severely paralyzed chronic stroke patient with intact sensorimotor cortex might sculpt new synergy patterns as a response to maladaptive compensatory strategies.Item Enhancing sensorimotor BCI performance with assistive afferent activity: An online evaluation(2019-10-01) Vidaurre, C.; Ramos Murguialday, A.; Haufe, S.; Gómez, M.; Müller, K. R.; Nikulin, V. V.; Medical TechnologiesAn important goal in Brain-Computer Interfacing (BCI) is to find and enhance procedural strategies for users for whom BCI control is not sufficiently accurate. To address this challenge, we conducted offline analyses and online experiments to test whether the classification of different types of motor imagery could be improved when the training of the classifier was performed on the data obtained with the assistive muscular stimulation below the motor threshold. 10 healthy participants underwent three different types of experimental conditions: a) Motor imagery (MI) of hands and feet b) sensory threshold neuromuscular electrical stimulation (STM) of hands and feet while resting and c) sensory threshold neuromuscular electrical stimulation during performance of motor imagery (BOTH). Also, another group of 10 participants underwent conditions a) and c). Then, online experiments with 15 users were performed. These subjects received neurofeedback during MI using classifiers calibrated either on MI or BOTH data recorded in the same experiment. Offline analyses showed that decoding MI alone using a classifier based on BOTH resulted in a better BCI accuracy compared to using a classifier based on MI alone. Online experiments confirmed accuracy improvement of MI alone being decoded with the classifier trained on BOTH data. In addition, we observed that the performance in MI condition could be predicted on the basis of a more pronounced connectivity within sensorimotor areas in the frequency bands providing the best performance in BOTH. These finding might offer a new avenue for training SMR-based BCI systems particularly for users having difficulties to achieve efficient BCI control. It might also be an alternative strategy for users who cannot perform real movements but still have remaining afferent pathways (e.g., ALS and stroke patients).Item The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke: Big data neuroimaging to study brain–behavior relationships after stroke(2020) Liew, Sook‐Lei; Zavaliangos‐Petropulu, Artemis; Jahanshad, Neda; Lang, Catherine E.; Hayward, Kathryn S.; Lohse, Keith R.; Juliano, Julia M.; Assogna, Francesca; Baugh, Lee A.; Bhattacharya, Anup K.; Bigjahan, Bavrina; Borich, Michael R.; Boyd, Lara A.; Brodtmann, Amy; Buetefisch, Cathrin M.; Byblow, Winston D.; Cassidy, Jessica M.; Conforto, Adriana B.; Craddock, R. Cameron; Dimyan, Michael A.; Dula, Adrienne N.; Ermer, Elsa; Etherton, Mark R.; Fercho, Kelene A.; Gregory, Chris M.; Hadidchi, Shahram; Holguin, Jess A.; Hwang, Darryl H.; Jung, Simon; Kautz, Steven A.; Khlif, Mohamed Salah; Khoshab, Nima; Kim, Bokkyu; Kim, Hosung; Kuceyeski, Amy; Lotze, Martin; MacIntosh, Bradley J.; Margetis, John L.; Mohamed, Feroze B.; Piras, Fabrizio; Ramos‐Murguialday, Ander; Richard, Geneviève; Roberts, Pamela; Robertson, Andrew D.; Rondina, Jane M.; Rost, Natalia S.; Sanossian, Nerses; Schweighofer, Nicolas; Seo, Na Jin; Shiroishi, Mark S.; Soekadar, Surjo R.; Spalletta, Gianfranco; Stinear, Cathy M.; Suri, Anisha; Tang, Wai Kwong W.; Thielman, Gregory T.; Vecchio, Daniela; Villringer, Arno; Ward, Nick S.; Werden, Emilio; Westlye, Lars T.; Winstein, Carolee; Wittenberg, George F.; Wong, Kristin A.; Yu, Chunshui; Cramer, Steven C.; Thompson, Paul M.; Zavaliangos-Petropulu, Artemis; Ramos-Murguialday, Ander; Medical TechnologiesThe goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.Item Epidural electrocorticography for monitoring of arousal in locked-in state(2014-10-21) Martens, Suzanne; Bensch, Michael; Halder, Sebastian; Hill, Jeremy; Nijboer, Femke; Ramos-Murguialday, Ander; Schoelkopf, Bernhard; Birbaumer, Niels; Gharabaghi, Alireza; Medical TechnologiesElectroencephalography (EEG) often fails to assess both the level (i.e., arousal) and the content (i.e., awareness) of pathologically altered consciousness in patients without motor responsiveness. This might be related to a decline of awareness, to episodes of low arousal and disturbed sleep patterns, and/or to distorting and attenuating effects of the skull and intermediate tissue on the recorded brain signals. Novel approaches are required to overcome these limitations. We introduced epidural electrocorticography (ECoG) for monitoring of cortical physiology in a late-stage amytrophic lateral sclerosis patient in completely locked-in state (CLIS). Despite long-term application for a period of six months, no implant-related complications occurred. Recordings from the left frontal cortex were sufficient to identify three arousal states. Spectral analysis of the intrinsic oscillatory activity enabled us to extract state-dependent dominant frequencies at < 4, ∼7 and ∼20 Hz, representing sleep-like periods, and phases of low and elevated arousal, respectively. In the absence of other biomarkers, ECoG proved to be a reliable tool for monitoring circadian rhythmicity, i.e., avoiding interference with the patient when he was sleeping and exploiting time windows of responsiveness. Moreover, the effects of interventions addressing the patient’s arousal, e.g., amantadine medication, could be evaluated objectively on the basis of physiological markers, even in the absence of behavioral parameters. Epidural ECoG constitutes a feasible trade-off between surgical risk and quality of recorded brain signals to gain information on the patient’s present level of arousal. This approach enables us to optimize the timing of interactions and medical interventions, all of which should take place when the patient is in a phase of high arousal. Furthermore, avoiding low-responsiveness periods will facilitate measures to implement alternative communication pathways involving brain-computer interfaces (BCI).Item Evaluation of upper extremity neurorehabilitation using technology: A European Delphi consensus study within the EU COST Action Network on Robotics for Neurorehabilitation(2016-09-23) Hughes, Ann Marie; Bouças, Sofia Barbosa; Burridge, Jane H.; Alt Murphy, Margit; Buurke, Jaap; Feys, Peter; Klamroth-Marganska, Verena; Lamers, Ilse; Prange-Lasonder, Gerdienke; Timmermans, Annick; Keller, Thierry; Tecnalia Research & InnovationBackground: The need for cost-effective neurorehabilitation is driving investment into technologies for patient assessment and treatment. Translation of these technologies into clinical practice is limited by a paucity of evidence for cost-effectiveness. Methodological issues, including lack of agreement on assessment methods, limit the value of meta-analyses of trials. In this paper we report the consensus reached on assessment protocols and outcome measures for evaluation of the upper extremity in neurorehabilitation using technology. The outcomes of this research will be part of the development of European guidelines. Methods: A rigorous, systematic and comprehensive modified Delphi study incorporated questions and statements generation, design and piloting of consensus questionnaire and five consensus experts groups consisting of clinicians, clinical researchers, non-clinical researchers, and engineers, all with working experience of neurological assessments or technologies. For data analysis, two major groups were created: i) clinicians (e.g., practicing therapists and medical doctors) and ii) researchers (clinical and non-clinical researchers (e.g. movement scientists, technology developers and engineers). Results: Fifteen questions or statements were identified during an initial ideas generation round, following which the questionnaire was designed and piloted. Subsequently, questions and statements went through five consensus rounds over 20 months in four European countries. Two hundred eight participants: 60 clinicians (29 %), 35 clinical researchers (17 %), 77 non-clinical researchers (37 %) and 35 engineers (17 %) contributed. At each round questions and statements were added and others removed. Consensus (≥69 %) was obtained for 22 statements on i) the perceived importance of recommendations; ii) the purpose of measurement; iii) use of a minimum set of measures; iv) minimum number, timing and duration of assessments; v) use of technology-generated assessments and the restriction of clinical assessments to validated outcome measures except in certain circumstances for research. Conclusions: Consensus was reached by a large international multidisciplinary expert panel on measures and protocols for assessment of the upper limb in research and clinical practice. Our results will inform the development of best practice for upper extremity assessment using technologies, and the formulation of evidence-based guidelines for the evaluation of upper extremity neurorehabilitation.Item Event-related desynchronization during movement attempt and execution in severely paralyzed stroke patients: An artifact removal relevance analysis: An artifact removal relevance analysis(2018) López-Larraz, Eduardo; Figueiredo, Thiago C.; Insausti-Delgado, Ainhoa; Ziemann, Ulf; Birbaumer, Niels; Ramos-Murguialday, Ander; Tecnalia Research & Innovation; Medical TechnologiesThe 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.Item Kinematic and neurophysiological consequences of an assisted-force-feedback brain-machine interface training: A case study(2013) Silvoni, Stefano; Cavinato, Marianna; Volpato, Chiara; Cisotto, Giulia; Genna, Clara; Agostini, Michela; Turolla, Andrea; Ramos-Murguialday, Ander; Piccione, Francesco; Medical TechnologiesIn a proof-of-principle prototypical demonstration we describe a new type of brain-machine interface (BMI) paradigm for upper limb motor-training. The proposed technique allows a fast contingent and proportionally modulated stimulation of afferent proprioceptive and motor output neural pathways using operant learning. Continuous and immediate assisted-feedback of force proportional to rolandic rhythm oscillations during actual movements was employed and illustrated with a single case experiment. One hemiplegic patient was trained for 2 weeks coupling somatosensory brain oscillations with force-field control during a robot-mediated center-out motor-task whose execution approaches movements of everyday life. The robot facilitated actual movements adding a modulated force directed to the target, thus providing a non-delayed proprioceptive feedback. Neuro-electric, kinematic, and motor-behavioral measures were recorded in pre- and post-assessments without force assistance. Patient's healthy arm was used as control since neither a placebo control was possible nor other control conditions. We observed a generalized and significant kinematic improvement in the affected arm and a spatial accuracy improvement in both arms, together with an increase and focalization of the somatosensory rhythm changes used to provide assisted-force-feedback. The interpretation of the neurophysiological and kinematic evidences reported here is strictly related to the repetition of the motor-task and the presence of the assisted-force-feedback. Results are described as systematic observations only, without firm conclusions about the effectiveness of the methodology. In this prototypical view, the design of appropriate control conditions is discussed. This study presents a novel operant-learning-based BMI-application for motor-training coupling brain oscillations and force feedback during an actual movement.Item Measuring resistance to externally induced movement of the wrist joint in chronic stroke patients using an objective hand-held dynamometer(2023-01) Mahmoud, Wala'; Haugland, Morten; Ramos-Murguialday, Ander; Hultborn, Hans; Ziemann, Ulf; Medical TechnologiesObjective: We evaluated the resistance to externally induced wrist extension in chronic stroke patients. We aimed to objectively measure and distinguish passive (muscle and soft tissue stiffness) and active (spasticity and spastic dystonia) components of the resistance. Methods: We used a hand-held dynamometer, which measures torque, joint movement and electromyography (EMG) simultaneously, to assess the resistance to externally induced wrist extension. Slow and fast stretches were applied to the affected and unaffected wrists in 57 chronic stroke patients (57 ± 11 years). We extracted from the data parameters that represent passive and muscle activity components and assessed the validity, test–retest reliability and the clinical utility of the measurement. Results: The analysis showed (1) a significant difference in the passive and muscle activity components between the affected and unaffected sides; (2) a significant correlation between passive and muscle activity components and the modified Ashworth scale (MAS); (3) a significant difference between the subgroups of patients stratified by the MAS; (4) an excellent intra-rater reliability on each of the passive and muscle activity components with intra-class coefficients between 0.92 and 0.99; (5) and small measurement error. Conclusions: Using a hand-held dynamometer, we were able to objectively measure the resistance to muscle stretch in the wrist joint in chronic stroke patients and discriminate muscle overactivity components from muscle and soft tissue stiffness. We demonstrated validity, test–retest reliability and the clinical utility of the measurement. Significance: Quantification of the different components of resistance to externally induced movement enables the objective evaluation of neurorehabilitation effects in chronic stroke patients.Item Movement related slow cortical potentials in severely paralyzed chronic stroke patients(2015-01-15) Yilmaz, Ozge; Birbaumer, Niels; Ramos-Murguialday, Ander; Medical TechnologiesMovement-related slow cortical potentials (SCPs) are proposed as reliable and immediate indicators of cortical reorganization in motor learning. SCP amplitude and latency have been reported as markers for the brain's computational effort, attention and movement planning. SCPs have been used as an EEG signature of motor control and as a main feature in Brain-Machine-Interfaces (BMIs). Some reports suggest SCPs are modified following stroke. In this study, we investigated movement-related SCPs in severe chronic stroke patients with no residual paretic hand movements preceding and during paretic (when they try to move) and healthy hand movements. The aim was to identify SCP signatures related to cortex integrity and complete paralysis due to stroke in the chronic stage. Twenty severely impaired (no residual finger extension) chronic stoke patients, of whom ten presented subcortical and ten cortical and subcortical lesions, underwent EEG and EMG recordings during a cue triggered hand movement (open/close) paradigm. SCP onset appeared and peaked significantly earlier during paretic hand movements than during healthy hand movements. Amplitudes were significantly larger over the midline (Cz, Fz) for paretic hand movements while contralateral (C4, F4) and midline (Cz, Fz) amplitudes were significantly larger than ipsilateral activity for healthy hand movements. Dividing the participants into subcortical only and mixed lesioned patient groups, no significant differences observed in SCP amplitude and latency between groups. This suggests lesions in the thalamocortical loop as the main factor in SCP changes after stroke. Furthermore, we demonstrated how, after long-term complete paralysis, post-stroke intention to move a paralyzed hand resulted in longer and larger SCPs originating in the frontal areas. These results suggest SCP are a valuable feature that should be incorporated in the design of new neurofeedback strategies for motor neurorehabilitation.Item Neuromuscular electrical stimulation induced brain patterns to decode motor imagery(2013-09) Vidaurre, C.; Pascual, J.; Ramos-Murguialday, A.; Lorenz, R.; Blankertz, B.; Birbaumer, N.; Müller, K. R.; Medical TechnologiesObjective: Regardless of the paradigm used to implement a brain-computer interface (BCI), all systems suffer from BCI-inefficiency. In the case of patients the inefficiency can be high. Some solutions have been proposed to overcome this problem, however they have not been completely successful yet. Methods: EEG from 10 healthy users was recorded during neuromuscular electrical stimulation (NMES) of hands and feet and during motor imagery (MI) of the same limbs. Features and classifiers were computed using part of these data to decode MI. Results: Offline analyses showed that it was possible to decode MI using a classifier based on afferent patterns induced by NMES and even infer a better model than with MI data. Conclusion: Afferent NMES motor patterns can support the calibration of BCI systems and be used to decode MI. Significance: This finding might be a new way to train sensorimotor rhythm (SMR) based BCI systems for healthy users having difficulties to attain BCI control. It might also be an alternative to train MI-based BCIs for users who cannot perform real movements but have remaining afferents (ALS, stroke patients).Item Neurophysiology of robot-mediated training and therapy: A perspective for future use in clinical populations(2013) Turner, Duncan L.; Ramos-Murguialday, Ander; Birbaumer, Niels; Hoffmann, Ulrich; Luft, Andreas; Medical TechnologiesThe recovery of functional movements following injury to the central nervous system (CNS) is multifaceted and is accompanied by processes occurring in the injured and non-injured hemispheres of the brain or above/below a spinal cord lesion. The changes in the CNS are the consequence of functional and structural processes collectively termed neuroplasticity and these may occur spontaneously and/or be induced by movement practice. The neurophysiological mechanisms underlying such brain plasticity may take different forms in different types of injury, for example stroke vs. spinal cord injury (SCI). Recovery of movement can be enhanced by intensive, repetitive, variable, and rewarding motor practice. To this end, robots that enable or facilitate repetitive movements have been developed to assist recovery and rehabilitation. Here, we suggest that some elements of robot-mediated training such as assistance and perturbation may have the potential to enhance neuroplasticity. Together the elemental components for developing integrated robot-mediated training protocols may form part of a neurorehabilitation framework alongside those methods already employed by therapists. Robots could thus open up a wider choice of options for delivering movement rehabilitation grounded on the principles underpinning neuroplasticity in the human CNS.