Publications related to Measuring the complexity of time series: an application to neurophysiological signals

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

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

Efficient Continual Finite-Sum Minimization

Volkan Cevher, Efstratios Panteleimon Skoulakis, Leello Tadesse Dadi

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

2024

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

Silvestro Micera, Michael Lassi

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

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

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

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 ...

Oxford2023

QuNex-An integrative platform for reproducible neuroimaging analytics

Valerio Zerbi

IntroductionNeuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges in ...

FRONTIERS MEDIA SA2023

Johann Sebastian Bach – The Chorales

Martin Alois Rohrmeier, Johannes Hentschel

This is a README file for a data repository originating from the DCML corpus initiative and serves as welcome page for both the GitHub repo

Zenodo2023

A Functional Perspective on Information Measures

Amedeo Roberto Esposito

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

EPFL2022

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

The EEG multiverse of schizophrenia

Michael Herzog, Maya Roinishvili, Ophélie Gladys Favrod, Patricia Figueiredo, Janir Nuno Ramos Antunes Da Cruz, Wei-Hsiang Lin, Dario Alejandro Gordillo Lopez

Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which ev ...

OXFORD UNIV PRESS INC2022

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 ...

FRONTIERS MEDIA SA2021

Measuring the complexity of time series: an application to neurophysiological signals

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

Efficient Continual Finite-Sum Minimization

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

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

QuNex-An integrative platform for reproducible neuroimaging analytics

Johann Sebastian Bach – The Chorales

A Functional Perspective on Information Measures

Computation Complexity Reduction Technique for Accurate Seizure Detection Implants

The EEG multiverse of schizophrenia

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

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

The EEG multiverse of schizophrenia

Computation Complexity Reduction Technique for Accurate Seizure Detection Implants

A Functional Perspective on Information Measures

Johann Sebastian Bach – The Chorales

QuNex-An integrative platform for reproducible neuroimaging analytics

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

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

Efficient Continual Finite-Sum Minimization

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