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José del Rocio Millán Ruiz

Cette personne a quitté l’EPFL

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Publications associées (228)

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Non-Invasive Brain-Machine Interaction

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Pierre Ferrez, Eileen Lew Yi Lee

The promise of Brain-Computer Interfaces (BCI) technology is to augment human capabilities by enabling interaction with computers through a conscious and spontaneous modulation of the brainwaves after a short training period. Indeed, by analyzing brain ele ...

World Scientific Publishing2008

Validation of Brain-Machine Interfaces during Parabolic Flight

José del Rocio Millán Ruiz

Here we report on a validation study on brain–machine interfaces (BMIs) performed during the December 2007 ESA parabolic flight campaign. We investigated the feasibility of using BMIs for space applications by performing tests in microgravity. Brain signal ...

Elsevier2009

Adaptive Assistance for Brain-Computer Interfaces by Online Prediction of Command Reliability

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Sareh Saeedi

One of the challenges of using brain-computer interfaces (BCIs) over extended periods of time is the variation of the users' performance across different experimental days. The goal of the current study is to propose a performance estimator for an electroe ...

Institute of Electrical and Electronics Engineers2016

Collecting complex activity data sets in highly rich networked sensor environments

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Daniel Roggen, Hesam Sagha, Hamidreza Bayati, Marco Creatura

We deployed 72 sensors of 10 modalities in 15 wireless and wired networked sensor systems in the environment, in objects, and on the body to create a sensor-rich environment for the machine recognition of human activities. We acquired data from 12 subjects ...

2010

ROS-Neuro: A common middleware for BMI and robotics. The acquisition and recorder packages

José del Rocio Millán Ruiz, Luca Tonin

Recent advances in the Brain-Machine Interface (BMI) and in the robotic fields allowed researchers to design a new generation of brain-actuated neuroprostheses to control a variety of assistive devices-ranging from powered wheelchairs to telepresence robot ...

IEEE2019

Improving Skills and Perception in Robot Navigation by an Augmented Virtuality Assistance System

José del Rocio Millán Ruiz, Tom Edward Carlson

Successful navigation in a teleoperation scenario requires a good level of situational or environmental awareness. This paper presents the main features and capabilities of a new augmented virtuality-based system aimed at providing users with improved perc ...

Springer Verlag2014

Non-Invasive Estimation of Local Field Potentials for Neuroprosthesis Control

José del Rocio Millán Ruiz, Pierre Ferrez

Recent experiments have shown the possibility to use the brain electrical activity to directly control the movement of robots or prosthetic devices in real time. Such neuroprostheses can be invasive or non-invasive, depending on how the brain signals are r ...

2005

Closed-loop electrical neurostimulation: Challenges and opportunities

José del Rocio Millán Ruiz, Inaki Asier Iturrate Gil, Michael Eric Anthony Pereira

Non-invasive and invasive electrical neurostimulation are promising tools to better understand brain function and ultimately treat its malfunction. In current open-loop approaches, a clinician chooses a fixed set of stimulation parameters, informed by obse ...

2018

Towards Independence: A BCI Telepresence Robot for People with Severe Motor Disabilities

José del Rocio Millán Ruiz, Robert Leeb, Luca Tonin, Tom Edward Carlson

This paper presents an important step forward towards increasing the independence of people with severe motor disabilities, by using brain-computer interfaces (BCI) to harness the power of the Internet of Things. We analyze the stability of brain signals a ...

Ieee-Inst Electrical Electronics Engineers Inc2015

Harnessing prefrontal cognitive signals for brain-machine interfaces

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano

Brain-machine interfaces (BMIs) enable humans to interact with devices by modulating their brain signals. Despite impressive technological advancements, several obstacles remain. The most commonly used BMI control signals are derived from the brain areas i ...

Elsevier2017

Subject-oriented training for motor imagery brain-computer interfaces

José del Rocio Millán Ruiz, Robert Leeb, Serafeim Perdikis

Successful operation of motor imagery (MI)-based brain-computer interfaces (BCI) requires mutual adaptation between the human subject and the BCI. Traditional training methods, as well as more recent ones based on co-adaptation, have mainly focused on the ...

2014

Motor Attempt EEG Paradigm As a Diagnostic Tool for Disorders of Consciousness

José del Rocio Millán Ruiz, Serafeim Perdikis, Christoph Schneider

To investigate whether a motor attempt EEG paradigm coupled with functional electrical stimulation can detect command following and, therefore, signs of conscious awareness in patients with disorders of consciousness, we recorded nine patients admitted to ...

2018

Errare machinale est: The use of error-related potentials in brain-machine interfaces

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Aleksander Sobolewski

The ability to recognize errors is crucial for efficient behavior. Numerous studies have identified electrophysiological correlates of error recognition in the human brain (error-related potentials, ErrPs). Consequently, it has been proposed to use these s ...

Frontiers Research Foundation2014

Person Authentication using Brainwaves (EEG) and Maximum A Posteriori Model Adaptation

José del Rocio Millán Ruiz, Sébastien Marcel

In this paper, we investigate the use of brain activity for person authentication. It has been shown in previous studies that the brain-wave pattern of every individual is unique and that the electroencephalogram (EEG) can be used for biometric identificat ...

2007

The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users

José del Rocio Millán Ruiz, Luca Tonin, Serafeim Perdikis, Sareh Saeedi, Christoph Schneider

This work aims at corroborating the importance and efficacy of mutual learning in motor imagery (MI) brain–computer interface (BCI) by leveraging the insights obtained through our participation in the BCI race of the Cybathlon event. We hypothesized that, ...

2018

Unsupervised adaptation to on-body sensor displacement in acceleration-based activity recognition

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Hamidreza Bayati

A common assumption in activity recognition is that the system remains unchanged between its design and its posterior operation. However, many factors can affect the data distribution between two different experimental sessions including sensor displacemen ...

Ieee Computer Soc Press, Customer Service Center, Po Box 3014, 10662 Los Vaqueros Circle, Los Alamitos, Ca 90720-1264 Usa2011

Single trial detection of spatial covert visual attention for BCI

José del Rocio Millán Ruiz, Robert Leeb, Luca Tonin

This paper discusses a time-dependent classification approach for single trial recognition of spatial covert visual attention for Brain–Computer Interface. Covert visual attention is a natural and intuitive mental task that does not require any external st ...

2011

Minimizing calibration time of single-trial recognition of error potentials in brain-computer interfaces

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

One of the main problems of both synchronous and asynchronous EEG-based BCIs is the need of an initial calibration phase before the system can be used. This phase is necessary due to the high non-stationarity of the EEG, since it changes between sessions a ...

2011

Vibrotactile Feedback for Brain-Computer Interface Operation

José del Rocio Millán Ruiz

To be correctly mastered, Brain-Computer Interfaces (BCIs) need an uninterrupted flow of feedback to the user. This feedback is usually delivered through the visual channel. Our aim is to explore the benefits of vibrotactile feedback during usersï¿½ traini ...

2007

Inverse solutions for classifying Event Related Potentials

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

In this paper we want to show the use of inverse solutions ‒in particular cortical current density (CCD)‒with respect to the current surface electroencephalogram (EEG) in classifying event related potentials. We construct feature vector from selected chann ...

2011