Investigation of Optimal Afferent Feedback Modality for Inducing Neural Plasticity with A Self-Paced Brain-Computer Interface
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Mads Jochumsen | Usman Rashid | Jimmy Lauber | Rasmus Wiberg Nedergaard | Juan Carlos Arceo | Imran Khan Niazi | Muhammad Samran Navid | Lucien Robinault | Sylvain Cremoux | Heidi Haavik | I. Niazi | Jimmy Lauber | S. Crémoux | Usman Rashid | Lucien Robinault | M. S. Navid | R. W. Nedergaard | Heidi Haavik | Mads Jochumsen
[1] Mads Jochumsen,et al. Comparison of Features for Movement Prediction from Single-Trial Movement-Related Cortical Potentials in Healthy Subjects and Stroke Patients , 2015, Comput. Intell. Neurosci..
[2] L. Cohen,et al. Brain–machine interface in chronic stroke rehabilitation: A controlled study , 2013, Annals of neurology.
[3] José Luis Pons Rovira,et al. A Closed-Loop Brain–Computer Interface Triggering an Active Ankle–Foot Orthosis for Inducing Cortical Neural Plasticity , 2014, IEEE Transactions on Biomedical Engineering.
[4] Mads Jochumsen,et al. Paired Associative Stimulation Delivered by Pairing Movement‐Related Cortical Potentials With Peripheral Electrical Stimulation: An Investigation of the Duration of Neuromodulatory Effects , 2018, Neuromodulation : journal of the International Neuromodulation Society.
[5] D. F. Collins,et al. Central Contributions to Contractions Evoked by Tetanic Neuromuscular Electrical Stimulation , 2007, Exercise and sport sciences reviews.
[6] Mark E. Dohring,et al. Feasibility of a New Application of Noninvasive Brain Computer Interface (BCI): A Case Study of Training for Recovery of Volitional Motor Control After Stroke , 2009, Journal of neurologic physical therapy : JNPT.
[7] D. Farina,et al. The effect of type of afferent feedback timed with motor imagery on the induction of cortical plasticity , 2017, Brain Research.
[8] A. Pavlovic,et al. Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface. , 2016, Journal of neurophysiology.
[9] Xingyu Wang,et al. Temporally Constrained Sparse Group Spatial Patterns for Motor Imagery BCI , 2019, IEEE Transactions on Cybernetics.
[10] Cuntai Guan,et al. Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke , 2014, Front. Neuroeng..
[11] J. Millán,et al. Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke , 2018, Nature Communications.
[12] Mads Jochumsen,et al. Detection and classification of movement-related cortical potentials associated with task force and speed , 2013, Journal of neural engineering.
[13] Walter Paulus,et al. The associative brain at work: Evidence from paired associative stimulation studies in humans , 2017, Clinical Neurophysiology.
[14] Alireza Gharabaghi,et al. Oscillatory entrainment of the motor cortical network during motor imagery is modulated by the feedback modality , 2015, NeuroImage.
[15] M. Hallett,et al. Modulation of muscle responses evoked by transcranial magnetic stimulation during the acquisition of new fine motor skills. , 1995, Journal of neurophysiology.
[16] J. Nielsen,et al. Major role for sensory feedback in soleus EMG activity in the stance phase of walking in man , 2000, The Journal of physiology.
[17] Xingyu Wang,et al. Sparse Bayesian Classification of EEG for Brain–Computer Interface , 2016, IEEE Transactions on Neural Networks and Learning Systems.
[18] G. Lewis,et al. Short-term Effects of Electrical Stimulation and Voluntary Activity on Corticomotor Excitability in Healthy Individuals and People With Stroke , 2012, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[19] D. Bates,et al. Fitting Linear Mixed-Effects Models Using lme4 , 2014, 1406.5823.
[20] Dario Farina,et al. Detecting and classifying movement-related cortical potentials associated with hand movements in healthy subjects and stroke patients from single-electrode, single-trial EEG , 2015, Journal of neural engineering.
[21] Thomas Sinkjær,et al. Cortical excitability changes following grasping exercise augmented with electrical stimulation , 2008, Experimental Brain Research.
[22] T. Sinkjær,et al. Evidence that a transcortical pathway contributes to stretch reflexes in the tibialis anterior muscle in man , 1998, The Journal of physiology.
[23] Mads Jochumsen,et al. Modeling and Control of Rehabilitation Robotic Device: motoBOTTE , 2018, Converging Clinical and Engineering Research on Neurorehabilitation III.
[24] Twisk J,et al. Different ways to estimate treatment effects in randomised controlled trials , 2018, Contemporary clinical trials communications.
[25] Ning Jiang,et al. Peripheral Electrical Stimulation Triggered by Self-Paced Detection of Motor Intention Enhances Motor Evoked Potentials , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[26] Ning Jiang,et al. Enhanced Low-Latency Detection of Motor Intention From EEG for Closed-Loop Brain-Computer Interface Applications , 2014, IEEE Transactions on Biomedical Engineering.
[27] John C Rothwell,et al. Differences between the effects of three plasticity inducing protocols on the organization of the human motor cortex , 2006, The European journal of neuroscience.
[28] D. Farina,et al. Detection of movement intention from single-trial movement-related cortical potentials , 2011, Journal of neural engineering.
[29] José del R. Millán,et al. Sensory threshold neuromuscular electrical stimulation fosters motor imagery performance , 2018, NeuroImage.
[30] J. Krakauer. Motor learning: its relevance to stroke recovery and neurorehabilitation. , 2006, Current opinion in neurology.
[31] L. Cohen,et al. Induction of plasticity in the human motor cortex by paired associative stimulation. , 2000, Brain : a journal of neurology.
[32] Tim Friede,et al. Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations , 2016, Biometrical journal. Biometrische Zeitschrift.
[33] J L Pons,et al. Detection of the onset of upper-limb movements based on the combined analysis of changes in the sensorimotor rhythms and slow cortical potentials , 2014, Journal of neural engineering.
[34] Sjoerd J de Vries,et al. Motor imagery and stroke rehabilitation: a critical discussion. , 2007, Journal of rehabilitation medicine.
[35] Cuntai Guan,et al. A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke , 2015, Clinical EEG and neuroscience.
[36] D. Farina,et al. Precise temporal association between cortical potentials evoked by motor imagination and afference induces cortical plasticity , 2012, The Journal of physiology.
[37] E. Biryukova,et al. Post-stroke Rehabilitation Training with a Motor-Imagery-Based Brain-Computer Interface (BCI)-Controlled Hand Exoskeleton: A Randomized Controlled Multicenter Trial , 2017, Front. Neurosci..
[38] Gernot R Müller-Putz,et al. Upper limb movements can be decoded from the time-domain of low-frequency EEG , 2017, PloS one.
[39] D. F. Collins,et al. Motor unit recruitment when neuromuscular electrical stimulation is applied over a nerve trunk compared with a muscle belly: triceps surae. , 2011, Journal of applied physiology.
[40] Mads Jochumsen,et al. Pairing Voluntary Movement and Muscle-Located Electrical Stimulation Increases Cortical Excitability , 2016, Front. Hum. Neurosci..
[41] M. Ridding,et al. Determinants of the induction of cortical plasticity by non‐invasive brain stimulation in healthy subjects , 2010, The Journal of physiology.
[42] Ning Jiang,et al. Detection of Movement Related Cortical Potentials from EEG Using Constrained ICA for Brain-Computer Interface Applications , 2017, Front. Neurosci..
[43] Cuntai Guan,et al. Brain-Computer Interface in Stroke Rehabilitation , 2013, J. Comput. Sci. Eng..
[44] Yu Zhang,et al. EEG classification using sparse Bayesian extreme learning machine for brain–computer interface , 2018, Neural Computing and Applications.
[45] J. Millán,et al. Detection of self-paced reaching movement intention from EEG signals , 2012, Front. Neuroeng..
[46] H. Asanuma,et al. Projection from the sensory to the motor cortex is important in learning motor skills in the monkey. , 1993, Journal of neurophysiology.
[47] Tomohiro Kizuka,et al. Motor imagery and electrical stimulation reproduce corticospinal excitability at levels similar to voluntary muscle contraction , 2014, Journal of NeuroEngineering and Rehabilitation.
[48] T Sinkjaer,et al. Changes in excitability of the cortical projections to the human tibialis anterior after paired associative stimulation. , 2007, Journal of neurophysiology.
[49] S. Rossi,et al. Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research , 2009, Clinical Neurophysiology.
[50] Fumitoshi Matsuno,et al. A Novel EOG/EEG Hybrid Human–Machine Interface Adopting Eye Movements and ERPs: Application to Robot Control , 2015, IEEE Transactions on Biomedical Engineering.
[51] J.-F. Debril,et al. Enhanced precision of ankle torque measure with an open-unit dynamometer mounted with a 3D force-torque sensor , 2015, European Journal of Applied Physiology.
[52] Mads Jochumsen,et al. Effect of subject training on a movement-related cortical potential-based brain-computer interface , 2018, Biomed. Signal Process. Control..
[53] J. Nielsen,et al. Afferent feedback in the control of human gait. , 2002, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[54] Thomas Sinkjaer,et al. Motor cortex excitability following repetitive electrical stimulation of the common peroneal nerve depends on the voluntary drive , 2005, Experimental Brain Research.