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

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

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

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

Monitoring of Cardiovascular and Neurological Diseases Using Wearable Devices

Dionisije Sopic

In this thesis, I focus on monitoring of patients suffering from cardiovascular and neurological diseases through the use of wearable devices. The main diseases considered in this thesis are atrial fibrillation (AF), myocardial infarction (MI), and epileps ...

EPFL2020

EEG Correlates of Difficulty Levels in Dynamical Transitions of Simulated Flying and Mapping Tasks

David Atienza Alonso, José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao

Decoding the subjective perception of task difficulty may help improve operator performance, i.e., automatically optimize the task difficulty level. Here, we aim to decode a compound of cognitive states that covaries with the task difficulty level. We desi ...

2020

A Multifaceted Approach to Covert Attention Brain-Computer Interfaces

Christoph Schneider

Over the last years, brain-computer interfaces (BCIs) have shown their value for assistive technology and neurorehabilitation. Recently, a BCI-approach for the rehabilitation of hemispatial neglect has been proposed on the basis of covert visuospatial atte ...

EPFL2018

An EEG-based brain-computer interface for gait training

José del Rocio Millán Ruiz, Kyuhwa Lee, Dong Liu

This work presents an electroencephalography (EEG)-based Brain-computer Interface (BCI) that decodes cerebral activities to control a lower-limb gait training exoskeleton. Motor imagery (MI) of flexion and extension of both legs was distinguished from the ...

2017

Optimal Sensor Architecture Selection for Health Management of Complex Systems

Martin Vetterli, Juri Ranieri

With technological progress, humans tend to create engineering systems with constantly increasing complexity and higher operational requirements. Many complex systems require the use of a Health Management (HM) solution to ensure safety and enable lifecycl ...

Ieee2016

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

Heat exchanger network design of large-scale industrial site with layout inspired constraints

François Maréchal, Nasibeh Pouransari

This paper presents a systematic approach for the synthesis of the heat recovery network in total site using a Mixed Integer Linear Programming model. This model returns a near-to-optimal network configuration with minimum utility cost while allows to sele ...

Elsevier2014

Stochastic MPC framework for controlling the average constraint violation

Colin Neil Jones, Milan Korda

This paper considers linear discrete-time systems with additive, bounded, disturbances subject to hard control input bounds and a stochastic constraint on the amount of state-constraint violation averaged over time. The amount of violations is quantified b ...

Institute of Electrical and Electronics Engineers2014

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

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

Computation Complexity Reduction Technique for Accurate Seizure Detection Implants

Monitoring of Cardiovascular and Neurological Diseases Using Wearable Devices

EEG Correlates of Difficulty Levels in Dynamical Transitions of Simulated Flying and Mapping Tasks

A Multifaceted Approach to Covert Attention Brain-Computer Interfaces

An EEG-based brain-computer interface for gait training

Optimal Sensor Architecture Selection for Health Management of Complex Systems

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Heat exchanger network design of large-scale industrial site with layout inspired constraints

Stochastic MPC framework for controlling the average constraint violation

A Multifaceted Approach to Covert Attention Brain-Computer Interfaces

EEG Correlates of Difficulty Levels in Dynamical Transitions of Simulated Flying and Mapping Tasks

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Heat exchanger network design of large-scale industrial site with layout inspired constraints

Monitoring of Cardiovascular and Neurological Diseases Using Wearable Devices

An EEG-based brain-computer interface for gait training

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

Stochastic MPC framework for controlling the average constraint violation

Computation Complexity Reduction Technique for Accurate Seizure Detection Implants

Optimal Sensor Architecture Selection for Health Management of Complex Systems