Publications associées à EEG source localization by multi-planar analytic sensing

Publications associées (31)

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

David Atienza Alonso, Amir Aminifar, José Angel Miranda Calero, Alireza Amirshahi, Jonathan Dan

The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

2024

Spectral representation of EEG data using learned graphs with application to motor imagery decoding

Maliheh Miri, Dimitri Nestor Alice Van De Ville, Hamid Behjat

Electroencephalography (EEG) data entail a complex spatiotemporal structure that reflects ongoing organi-zation of brain activity. Characterization of the spatial patterns is an indispensable step in numerous EEG processing pipelines. We present a novel me ...

Elsevier Sci Ltd2023

Brain's Dynamic Functional Organization with Simultaneous EEG-fMRI Networks

Patricia Figueiredo, João Pedro Forjaco Jorge

The brain's functional networks can be assessed using imaging techniques like functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Recent studies have suggested a link between the dynamic functional connectivity (dFC) captured by ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients

Silvestro Micera

ABS T R A C T BACKGROUND: Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanism ...

Edizioni Minerva Medica2023

Brain-controlled spinal cord stimulation to restore mobility after spinal cord injury

Carmina Andrea Galvez Solano

Spinal Cord Injury (SCI) affects almost 500,000 people every year, causing complete paralysis of both legs in severe cases, with no current treatment perspective. However, new neuroengineering technologies, such as the Brain Spine Interface (BSI), have eme ...

EPFL2023

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

Silvestro Micera

Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 heal ...

IOP Publishing Ltd2023

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?

Silvestro Micera

Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by ...

ELSEVIER SCI LTD2023

Real-time Personalized Monitoring of Neurological Disorders on Wearable Systems

Renato Zanetti

The terminology of neurological disorders encompasses a range of serious illnesses (e.g., epilepsy, Alzheimer's disease) leading to morbidity, disability, and stigma. Epilepsy alone affects over 50 million people worldwide, and these figures are rising as ...

EPFL2023

Personalized seizure signature: An interpretable approach to false alarm reduction for long‐term epileptic seizure detection

David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Dionisije Sopic

Objective Long-term automatic detection of focal seizures remains one of the major challenges in epilepsy due to the unacceptably high number of false alarms from state-of-the-art methods. Our aim was to investigate to what extent a new patient-specific ap ...

2022

Segmenting electroencephalography wires reduces radiofrequency shielding artifacts in simultaneous electroencephalography and functional magnetic resonance imaging at 7 T

Rolf Gruetter, João Pedro Forjaco Jorge, Thanh Phong Kevin Lê, Özlem Ipek

Purpose: Simultaneous scalp electroencephalography and functional magnetic resonance imaging (EEG-fMRI) enable noninvasive assessment of brain function with high spatial and temporal resolution. However, at ultra-high field, the data quality of both modali ...

Wiley2022

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi

Recent years have seen growing interest in leveraging deep learning models for monitoring epilepsy patients based on electroencephalographic (EEG) signals. However, these approaches often exhibit poor generalization when applied outside of the setting in w ...

2022

Computation Complexity Reduction Technique for Accurate Seizure Detection Implants

Alexandre Schmid, Keyvan Farhang Razi

An automatic seizure detection method from high-resolution intracranial-EEG (iEEG) signals is presented to minimize the computational complexity and realize real-time accurate seizure detection for biomedical implants. Complex signal processing on a large ...

IEEE2022

Exploring the spatial resolution of TMS-EEG coupling on the sensorimotor region

Estelle Emeline Raffin, Sylvain Jean-François Harquel

The use of TMS-EEG coupling as a neuroimaging tool for the functional exploration of the human brain recently gained strong interest. If this tool directly inherits the fine temporal resolution from EEG, its spatial counterpart remains unknown. In this stu ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Large-scale brain network dynamics in very preterm children and relationship with socio-emotional outcomes: an exploratory study

Dimitri Nestor Alice Van De Ville, Lorena Gonçalves de Alcântara e Freitas Krikler, Vanessa Siffredi, Younes Farouj

Background Children born very preterm (VPT;

SPRINGERNATURE2022

Identifying uncertainty states during wayfinding in indoor environments: An EEG classification Study

Mahsa Shoaran, Bingzhao Zhu

The researchers used a machine-learning classification approach to better understand neurological features associated with periods of wayfinding uncertainty. The participants (n = 30) were asked to complete wayfinding tasks of varying difficulty in a virtu ...

ELSEVIER SCI LTD2022

Automatic detection of generalized paroxysmal fast activity in interictal EEG using time-frequency analysis

Amir Hossein Omidvarnia

Objective: Markup of generalized interictal epileptiform discharges (IEDs) on EEG is an important step in the diagnosis and characterization of epilepsy. However, manual EEG markup is a time-consuming, subjective, and the specialized task where the human r ...

2021

Exploring MEG brain fingerprints: Evaluation, pitfalls, and interpretations

Sélima Zahar, Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Enrico Amico, Ekansh Sareen

Individual characterization of subjects based on their functional connectome (FC), termed “FC fingerprinting”, has become a highly sought-after goal in contemporary neuroscience research. Recent functional magnetic resonance imaging (fMRI) studies have dem ...

2021

PIRACY: An Optimized Pipeline for Functional Connectivity Analysis in the Rat Brain

Rolf Gruetter, Ileana Ozana Jelescu, Ting Yin, Yujian Diao

Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity (FC) and brain disorders. However, FC analysis can be seriously affected by random and structured noise from non-neural sources, such as phys ...

2021

Connectivity Measures Differentiate Cortical and Subcortical Sub-Acute Ischemic Stroke Patients

Silvestro Micera

Brain lesions caused by cerebral ischemia lead to network disturbances in both hemispheres, causing a subsequent reorganization of functional connectivity both locally and remotely with respect to the injury. Quantitative electroencephalography (qEEG) meth ...

FRONTIERS MEDIA SA2021

Two-stage Hardware-Friendly Epileptic Seizure Detection Method with a Dynamic Feature Selection

Alexandre Schmid, Keyvan Farhang Razi

A novel low-complexity method of detecting epileptic seizures from intracranial encephalography (iEEG) signals is presented. In the proposed algorithm, coastline, energy and nonlinear energy features of iEEG signals are extracted in a patient-specific two- ...

IEEE2021