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José del Rocio Millán Ruiz

Cette personne a quitté l’EPFL

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Publications associées (228)

Page 5 sur 12

Brain-coupled Interaction for Semi-autonomous Navigation of an Assistive Robot

Roland Siegwart, José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano

This paper presents a novel semi-autonomous navigation strategy designed for low throughput interfaces. A mobile robot (e.g. intelligent wheelchair) proposes the most probable action, as analyzed from the environment, to a human user who can either accept ...

Elsevier2010

BNCI Horizon 2020: towards a roadmap for the BCI community

José del Rocio Millán Ruiz

The brain-computer interface (BCI) field has grown dramatically over the past few years, but there are still no coordinated efforts to ensure efficient communication and collaboration among key stakeholders. The European Commission (EC) has recently renewe ...

2015

Spatial filters yield stable features for error-related potentials across conditions

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

Error-related potentials (ErrP) have been increasingly studied in psychophysical experiments as well as for brain-machine interfacing. In the latter case, the generalisation capabilities of ErrP decoders is a crucial element to avoid frequent recalibration ...

2016

Brain-Controlled Robots

José del Rocio Millán Ruiz

The idea of moving robots or prosthetic devices not by manual control, but by mere thinking (i.e., the brain activity of human subjects) has fascinated researchers for the last 30 years, but it is only now that first experiments have shown the possibility ...

2008

Comparing BCI performance using scalp EEG-and inverse solution-based features

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Mohit Kumar Goel

Several studies have proposed the use of inverse solutions based features to improve the decoding performance of brain-computer interfaces. Most of these studies have compared the performance of inverse solutions features over scalp activity in a small set ...

2014

Uncovering EEG Correlates of Covert Attention in Soccer Goalkeepers: Towards Innovative Sport Training Procedures

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Luca Tonin

Advances in sports sciences and neurosciences offer new opportunities to design efficient and motivating sport training tools. For instance, using NeuroFeedback (NF), athletes can learn to self-regulate specific brain rhythms and consequently improve their ...

Nature Research2020

Self-paced Movement Intention Detection from Human Brain Signals: Invasive and Non-invasive EEG

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Huaijian Zhang, Eileen Lew Yi Lee

Neural signatures of humans’ movement intention can be exploited by future neuroprosthesis. We propose a method for detecting self-paced upper limb movement intention from brain signals acquired with both invasive and noninvasive methods. In the first stud ...

Ieee2012

The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Daniel Roggen, Hesam Sagha

There is a growing interest on using ambient and wearable sensors for human activity recognition, fostered by several application domains and wider availability of sensing technologies. This has triggered increasing attention on the development of robust m ...

Elsevier2013

The timing of exploratory decision-making revealed by single-trial topographic EEG analyses

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Micah Murray, Nicolas Bourdaud

Decision-making in an uncertain environment is driven by two major needs: exploring the environment to gather information or exploiting acquired knowledge to maximize reward. The neural processes underlying exploratory decision-making have been mainly stud ...

Elsevier2012

Teaching brain-machine interfaces as an alternative paradigm to neuroprosthetics control

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Inaki Asier Iturrate Gil

Brain-machine interfaces (BMI) usually decode movement parameters from cortical activity to control neuroprostheses. This requires subjects to learn to modulate their brain activity to convey all necessary information, thus imposing natural limits on the c ...

Nature Publishing Group2015

Online Modulation of the Level of Assistance in Shared Control Systems

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Tom Edward Carlson

In this paper we propose a method to modulate the level of assistance provided by a shared controller, not only given the environmental context, but also according to the context of the user’s current behaviour. We show that the enhanced situational contex ...

2012

Dynamic Quantification of Activity Recognition Capabilities in Opportunistic Systems

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha

Opportunistic activity and context recognition systems draw from the characteristic to use sensing devices according to a recognition goal at runtime that just happen to be available instead of pre-defining them at the design time of the system. Whenever a ...

2011

Are we ready? Issues in transferring BCI technology from experts to users

José del Rocio Millán Ruiz, Robert Leeb, Serafeim Perdikis, Luca Tonin, Andrea Biasiucci, Tom Edward Carlson, Michele Tavella

Brain-Computer Interfaces (BCIs) are no longer only used by healthy subjects under control conditions in laboratory environments, but by patients controlling applications at their homes, without the BCI experts around. But are the technology and the field ...

Verlag der Technischen Universitaet Graz2011

Differential contributions of subthalamic beta rhythms and 1/f broadband activity to motor symptoms in Parkinson’s disease

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Inaki Asier Iturrate Gil, Jocelyne Bloch, Aleksander Sobolewski, Stéphanie Martin

Excessive beta oscillatory activity in the subthalamic nucleus (STN) is linked to Parkinson’s Disease (PD) motor symptoms. However, previous works have been inconsistent regarding the functional role of beta activity in untreated Parkinsonian states, quest ...

2018

Sensory threshold neuromuscular electrical stimulation fosters motor imagery performance

José del Rocio Millán Ruiz, Serafeim Perdikis, Inaki Asier Iturrate Gil, Michael Eric Anthony Pereira, Tiffany Corbet

Motor imagery (MI) has been largely studied as a way to enhance motor learning and to restore motor functions. Although it is agreed that users should emphasize kinesthetic imagery during MI, recordings of MI brain patterns are not sufficiently reliable fo ...

2018

Augmenting Information from Brain-Computer Interfaces through Bayesian Plan Recognition

José del Rocio Millán Ruiz

For severely disabled people, Brain-Computer Interfaces (BCIs) may provide the means to regain mobility and manipulation capabilities. However, information obtained from current BCIs is uncertain and of limited bandwidth and resolution. This paper presents ...

2009

An online EEG BCI based on covert visuospatial attention in absence of exogenous stimulation

José del Rocio Millán Ruiz, Robert Leeb, Luca Tonin, Aleksander Sobolewski

Objective. In this work we present—for the first time—the online operation of an electroencephalogram (EEG) brain–computer interface (BCI) system based on covert visuospatial attention (CVSA), without relying on any evoked responses. Electrophysiological c ...

Iop Publishing Ltd2013

A Probabilistic Approach to Handle Missing Data for Multi-Sensory Activity Recognition

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hesam Sagha

Context and activity recognition in complex scenarios is prone to data loss due to disconnections, sensor failure, transmission problems, etc. This generally implies significant changes in the recognition performance. In the case of classifier fusion fault ...

2010

Detecting intention to grasp during reaching movements from EEG

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Inaki Asier Iturrate Gil, Luca Randazzo

Brain-computer interfaces (BCI) have been shown to be a promising tool in rehabilitation and assistive scenarios. Within these contexts, brain signals can be decoded and used as commands for a robotic device, allowing to translate user’s intentions into mo ...

2015

Rewards-Driven Control of Robot Arm by Decoding EEG Signals

Aude Billard, José del Rocio Millán Ruiz, Ajay Kumar Tanwani

Decoding the user intention from non-invasive EEG signals is a challenging problem. In this paper, we study the feasibility of predicting the goal for controlling the robot arm in self-paced reaching movements, i.e., spontaneous movements that do not requi ...

2014