Bibliothèque

Single-subject auditory ERP-BCI performance enhancement in ALS via an AI coding assistant prompt. Introduction: Auditory event-related potential (ERP) brain-computer interfaces (BCIs) offer communication support for individuals with amyotro…

Frontiers in Human Neuroscience · auteur h-index 6 · 0 citation

Beyond Brain Data: An Enactive Approach to Brain-Computer Interface-Mediated Mind Reading and Mental Privacy

Neuroethics · auteur h-index 8 · 0 citation

Application and prospects of brain-computer interface technology for motor function reconstruction after brachial plexus injury. BACKGROUND: Brachial plexus injury (BPI) is a severe peripheral nerve disorder leading to significant upper lim…

Annals of Medicine · auteur h-index 6 · 1 citation

Optimized cortical EEG modeling for Parkinson disease diagnosis with snow Shepherd Stride tuning mechanism

Cognitive Neurodynamics · auteur h-index 0 · 0 citation

Enhancing upper limb motor recovery prediction after acute stroke using EEG and subacute data. Electroencephalography (EEG) has shown promise in assessing and monitoring functional recovery in stroke survivors, but its utility in predicting…

APL Bioengineering · auteur h-index 65 · 0 citation

A Unified SPD Token Transformer Framework for EEG Classification: Systematic Comparison of Geometric Embeddings. Spatial covariance matrices of EEG signals are Symmetric Positive Definite (SPD) and lie on a Riemannian manifold, yet the theo…

Open MIND · auteur h-index 0 · 0 citation

Levels of shared autonomy in brain-robot interfaces: enabling multi-robot multi-human collaboration for activities of daily living. Individuals with ALS and other severe motor impairments often rely on caregivers for daily tasks, which limi…

Frontiers in Human Neuroscience · auteur h-index 13 · 0 citation

Enhancing upper limb motor recovery prediction after acute stroke using EEG and subacute data.. Electroencephalography (EEG) has shown promise in assessing and monitoring functional recovery in stroke survivors, but its utility in predictin…

Florence Research (University of Florence) · auteur h-index 0 · 0 citation

The Double-Edged Nature of Delay: Toward a Functional Latency Window in Neurorehabilitation and Brain–Machine Interaction. Delay pervades human–machine systems—from synaptic transmission and axonal conduction to sensing, computation, and ac…

Theoretical and Natural Science · auteur h-index 7 · 0 citation

Corral Neuroprosthetics – Transition‑Motif Controllers for Assistive Interfaces. We propose a conceptual–methods framework for assistive neurotechnology aimed at paralysis and related disabilities: Corral Neuroprosthetics. The central claim…

Zenodo (CERN European Organization for Nuclear Research) · 0 citation

Rethinking stroke rehabilitation in the technological age. Singapore is due to become a super-aged society by 2026, when more than 21% of the population would be aged 65 years or older.[1] This demographic shift coincides with a troubling t…

Singapore Medical Journal · auteur h-index 41 · 1 citation

Reliable decision making on clinical EEG: Trusted multi-view learning with subjective logic for uncertainty quantification

Expert Systems with Applications · auteur h-index 28 · 0 citation

Directed Neural Network Dynamics in Sensorimotor Integration: Divergent Roles of Frontal Theta Band Activity Depending on Age. Sensorimotor integration processes are crucial for daily-life activities, such as grasping objects or driving a c…

Journal of Neuroscience · auteur h-index 68 · 1 citation

Reliable predictor of BCI motor imagery performance using median nerve stimulation. Abstract Objective. Predicting performance in brain–computer interfaces (BCIs) is crucial for enhancing user experience, optimizing training and identifying…

Journal of Neural Engineering · auteur h-index 50 · 4 citations

DeepFingerNet Predicts Finger Trajectory From ECoG Measurements. Decoding fine motor movements, such as finger trajectories, from brain signals poses a critical challenge for brain-computer interface (BCI) systems, particularly when employi…

IEEE Transactions on Instrumentation and Measurement · auteur h-index 87 · 0 citation

Reward processing and prediction errors in frontal and basal ganglia signals during decision making. Biomarkers for non-motor symptoms in neurological and psychiatric disorders treated with deep brain stimulation (DBS)

Brain stimulation · auteur h-index 49 · 0 citation

Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements

Journal of Neuroscience Methods · auteur h-index 79 · 8 citations

How to design optimal brain stimulation to modulate phase-amplitude coupling?. Abstract Objective. Phase-amplitude coupling (PAC), the coupling of the amplitude of a faster brain rhythm to the phase of a slower brain rhythm, plays a signifi…

Journal of Neural Engineering · auteur h-index 49 · 8 citations

Recording of single-unit activities with flexible micro-electrocorticographic array in rats for decoding of whole-body navigation. Abstract Objective. Micro-electrocorticographic ( μ ECoG) arrays are able to record neural activities from th…

Journal of Neural Engineering · auteur h-index 31 · 3 citations

Unsupervised neural decoding for concurrent and continuous multi-finger force prediction

Computers in Biology and Medicine · auteur h-index 33 · 14 citations

Enhancing Motor Imagery Electroencephalography Classification with a Correlation-Optimized Weighted Stacking Ensemble Model. In the evolving field of Brain–Computer Interfaces (BCIs), accurately classifying Electroencephalography (EEG) sign…

Electronics · auteur h-index 29 · 14 citations

IoT-Enabled Smart Mental Health Assessment Using Deep Hybrid Regression Models Over Actigraph-Based Sequential Motor Activity Data

Arabian Journal for Science and Engineering · auteur h-index 11 · 5 citations

Neural Manifold Constraint for Spike Prediction Models Under Behavioral Reinforcement. Spike prediction models effectively predict downstream spike trains from upstream neural activity for neural prostheses. Such prostheses could potentiall…

IEEE Transactions on Neural Systems and Rehabilitation Engineering · auteur h-index 23 · 4 citations

Prediction of Dexterous Finger Forces With Forearm Rotation Using Motoneuron Discharges. Motor unit (MU) discharge information obtained via electromyogram (EMG) decomposition can be used to decode dexterous multi-finger movement intention f…

IEEE Transactions on Neural Systems and Rehabilitation Engineering · auteur h-index 33 · 8 citations

Electroencephalography-based parietofrontal connectivity modulated by electroacupuncture for predicting upper limb motor recovery in subacute stroke. BACKGROUND: Predicting motor recovery in stroke patients is essential for effective rehabi…

Medicine · auteur h-index 22 · 2 citations

The impact of task context on predicting finger movements in a brain-machine interface. A key factor in the clinical translation of brain-machine interfaces (BMIs) for restoring hand motor function will be their robustness to changes in a t…

eLife · auteur h-index 39 · 7 citations

EEG-Based Motor Imagery Recognition Framework via Multisubject Dynamic Transfer and Iterative Self-Training. A robust decoding model that can efficiently deal with the subject and period variation is urgently needed to apply the brain-compu…

IEEE Transactions on Neural Networks and Learning Systems · 23 citations

Improvement of brain–computer interface in motor imagery training through the designing of a dynamic experiment and FBCSP. Motor imagery (MI) can produce a specific brain pattern when the subject imagines performing a particular action with…

Heliyon · auteur h-index 14 · 23 citations

Hierarchical approach for fusion of electroencephalography and electromyography for predicting finger movements and kinematics using deep learning

Neurocomputing · auteur h-index 21 · 20 citations

A cerebellum inspired spiking neural network as a multi-model for pattern classification and robotic trajectory prediction. Spiking neural networks were introduced to understand spatiotemporal information processing in neurons and have foun…

Frontiers in Neuroscience · 11 citations

The influence of the motor command accuracy on the prediction error and the automatic corrective response

Physiology & Behavior · auteur h-index 21 · 3 citations

Sensory-Motor Modulations of EEG Event-Related Potentials Reflect Walking-Related Macro-Affordances. One fundamental principle of the brain functional organization is the elaboration of sensory information for the specification of action pl…

Brain Sciences · auteur h-index 3 · 10 citations

A deep neural network with subdomain adaptation for motor imagery brain-computer interface. BACKGROUND: The nonstationarity problem of EEG is very serious, especially for spontaneous signals, which leads to the poor effect of machine learni…

Medical Engineering & Physics · 18 citations

Galvanic Vestibular Stimulation-Based Prediction Error Decoding and Channel Optimization. A significant problem in brain-computer interface (BCI) research is decoding - obtaining required information from very weak noisy electroencephalogra…

International Journal of Neural Systems · 6 citations

Deep Learning-Based Approaches for Decoding Motor Intent From Peripheral Nerve Signals. Previous literature shows that deep learning is an effective tool to decode the motor intent from neural signals obtained from different parts of the ne…

Frontiers in Neuroscience · 21 citations

Relevance of Predictive and Postdictive Error Information in the Course of Motor Learning

Neuroscience · 11 citations

Vividness of Visual Imagery and Personality Impact Motor-Imagery Brain Computer Interfaces. Brain-computer interfaces (BCIs) are communication bridges between a human brain and external world, enabling humans to interact with their environm…

Frontiers in Human Neuroscience · 47 citations

Focused Review on Neural Correlates of Different Types of Motor Errors and Related Terminological Issues. The Error-related negativity (Ne/ERN) and the feedback-related negativity (FRN), two event-related potentials in electroencephalogram…

Journal of Human Kinetics · 8 citations

Elman neural network for the early identification of cognitive impairment in Alzheimer�s disease. Early detection of dementia can be useful to delay progression of the disease and to raise awareness of the condition. Alterations in temporal…

Functional Neurology · auteur h-index 4 · 20 citations