Publication

Structured Sampling and Recovery of iEEG Signals

Publications associées (31)

A machine-learning algorithm correctly classifies cortical evoked potentials from both visual stimulation and electrical stimulation of the optic nerve

Vivien Gaillet, Diego Ghezzi, Eleonora Borda, Elodie Geneviève Zollinger

Objective. Optic nerve's intraneural stimulation is an emerging neuroprosthetic approach to provide artificial vision to totally blind patients. An open question is the possibility to evoke individual non-overlapping phosphenes via selective intraneural op ...

IOP PUBLISHING LTD2021

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Mahsa Shoaran, Bingzhao Zhu

Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique decision ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Soft Printable Electrode Coating for Neural Interfaces

Florian Dylan Fallegger, Elvira Pirondini, Stéphanie Lacour, Arnaud Bichat, Grégoire Courtine, Quentin Barraud, Michael Shur

The mechanical mismatch between implantable interfaces and neural tissues may be reduced by employing soft polymeric materials. Here, we report on a simple strategy to prepare and pattern a soft electrode coating of neural interfacing devices based on a sc ...

2020

Deep learning-based BCI for gait decoding from EEG with LSTM recurrent neural network

Silvestro Micera, Fiorenzo Artoni, Stefano Tortora

Objective.Mobile Brain/Body Imaging (MoBI) frameworks allowed the research community to find evidence of cortical involvement at walking initiation and during locomotion. However, the decoding of gait patterns from brain signals remains an open challenge. ...

IOP PUBLISHING LTD2020

Longitudinal neural and vascular structural dynamics produced by chronic microelectrode implantation

Andrea Lozzi

Implanted microelectrode arrays sense local neuronal activity, signals which are used as control commands for brain computer interface (BCI) technology. Patients with tetraplegia have used BCI technology to achieve an extraordinary degree of interaction wi ...

2020

Closed-Loop Neural Interfaces with Embedded Machine Learning

Mahsa Shoaran, Uisub Shin, Bingzhao Zhu

Neural interfaces capable of multi-site electrical recording, on-site signal classification, and closed-loop therapy are critical for the diagnosis and treatment of neurological disorders. However, deploying machine learning algorithms on low-power neural ...

IEEE2020

EpilepsyGAN: Synthetic Epileptic Brain Activities with Privacy Preservation

David Atienza Alonso, Amir Aminifar, Damián Pascual Ortiz, Alireza Amirshahi

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can also be life-thr ...

2021

A Review of Microelectronic Systems and Circuit Techniques for Electrical Neural Recording Aimed at Closed-Loop Epilepsy Control

Alexandre Schmid, Reza Ranjandish

Closed-loop implantable electronics offer a new trend in therapeutic systems aimed at controlling some neurological diseases such as epilepsy. Seizures are detected and electrical stimulation applied to the brain or groups of nerves. To this aim, the signa ...

2020

All-Printed Electrocorticography Array for In Vivo Neural Recordings

Fabian Michael Lütolf, Diego Ghezzi, Eleonora Borda, Laura Ferlauto, Nenad Marjanovic

Bioelectronic and neuroprosthetic interfaces rely on implanted microelectrode arrays (MEAs) to interact with the human body. Printing techniques, such as inkjet and screen printing, are attractive methods for the manufacturing of MEAs because they allow fl ...

2020

Inferring subjective preferences on robot trajectories using EEG signals

Aude Billard, Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Inaki Asier Iturrate Gil, Iason Batzianoulis, Fumiaki Iwane

Cognitive information has been exploited in non-invasive Brain Computer Interface (BCI) scenarios to provide autonomous external agents with additional information. In this context, Error-related potentials (ErrPs), temporal deflections in electroencephalo ...

IEEE2019

Cortical reactive balance responses to unexpected slippages while walking: a pilot study

Daniela De Venuto, Silvestro Micera

Understanding how the human brain cortex behaves when the dynamical balance is unexpectedly challenged can be useful to enable fall prevention strategies during daily activities. In this respect, we designed and tested a novel methodological approach to ea ...

IEEE2019