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José del Rocio Millán Ruiz

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Related publications (230)

Brain-Machine Interfaces: Progress in Large Clinical Validation

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

Brain-machine interfaces (BMI) have largely been demonstrated in laboratory conditions involving, mainly, healthy users. We have recently carried out a series of studies with a substantial number of motor-disabled end-users operating different brain-contro ...

2013

A Hybrid BCI for Enhanced Control of a Telepresence Robot

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

Motor-disabled end users have successfully driven a telepresence robot in a complex environment using a Brain-Computer Interface (BCI). However, to facilitate the interaction aspect that underpins the notion of telepresence, users must be able to voluntari ...

2013

Freeing the visual channel by exploiting vibrotactile BCI feedback

José del Rocio Millán Ruiz, Robert Leeb

Controlling a brain-actuated device requires the participant to look at and to split his attention between the interaction of the device with its environment and the status information of the Brain-Computer Interface (BCI). Such parallel visual tasks are p ...

2013

Driving a BCI Wheelchair: A Patient Case Study

José del Rocio Millán Ruiz, Guillaume Monnard, Robert Leeb, Tom Edward Carlson

Our brain-actuated wheelchair uses shared control to couple the user input with the contextual information about the surroundings in order to perform natural manoeuvres both safely and efficiently. In this study, we investigate the feasibility of using our ...

2012

Toward online detection of BCI performance degradation

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

One of the problems of non-invasive BCI applications is the noise and change of EEG recordings that can result in performance degradation. Signal noise and changes can for instance be the result of electrode misplacements, impedances degradation or complet ...

2012

The Birth of the Brain–Controlled Wheelchair

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

The prospect of controlling devices merely by the power of one’s thoughts is compelling, especially for assistive technology applications. In the accompanying video, we show how we have strived to push brain–computer interface (BCI) technology out of the l ...

2012

Time-Dependent Approach for Single Trial Classification of Covert Visuospatial Attention

José del Rocio Millán Ruiz, Luca Tonin, Robert Leeb

Recently, several studies have started to explore covert visuospatial attention as a control signal for brain–computer interfaces (BCIs). Covert visuospatial attention represents the ability to change the focus of attention from one point in the space with ...

Institute of Physics2012

Detection of Anticipatory Brain Potentials during Car Driving

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Zahra Khaliliardali, Lucian Andrei Gheorghe

Recognition of driver’s intention from electroencephalogram (EEG) can be helpful in developing an in-car brain computer interface (BCI) systems for intelligent cars. This could be beneficial in enhancing the quality of interaction between the driver and th ...

Ieee2012

Kinect=IMU? Learning MIMO Signal Mappings to Automatically Translate Activity Recognition Systems Across Sensor Modalities

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

We propose a method to automatically translate a pre-existing activity recognition system, devised for a source sensor domain S, so that it can operate on a newly discovered target sensor domain T , possibly of different modality. First, we use MIMO system ...

2012

Real-time Prediction of Fast and Slow Delivery of Mental Commands in a Motor Imagery BCI: An Entropy-based Approach

Michael Christoph Gastpar, Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi

Providing adaptive shared control for Brain- Computer Interfaces (BCIs) can result in better performance while reducing the user’s mental workload. In this respect, online estimation of accuracy and speed of command delivery are important factors. This stu ...

2012

Online Modulation of the Level of Assistance in Shared Control Systems

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, 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

Anticipation- and Error-related EEG Signals during Realistic Human-Machine interaction: A Study on Visual and Tactile Feedback

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

The exploitation of EEG signatures of cognitive processes can provide valuable information to improve interaction with brain actuated devices. In this work we study these correlates in a realistic situation simulated in a virtual reality environment. We fo ...

Ieee2012

BCI Telepresence: A Six Patient Evaluation

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

In this paper we present the results of six motor-disabled patients manoeuvring a telepresence robot via a BCI. Remarkably, although five of the patients had never visited the location where the telepresence robot was operating, they achieved similar perfo ...

2012

Online BCI with Stable Sources

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

In this paper, we show that the estimated intra-cranial sources using source localization on EEG signals can be used for online Brain Computer Interation (BCI) and the discriminant sources remain stable over days. Classifiers are trained on discriminant so ...

2012

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

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

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

Decoding Self-paced Upper Limb Reaching Movements from Brain Signals

José del Rocio Millán Ruiz, Eileen Lew Yi Lee

Future emerging technologies in upper limb neuroprosthetic devices will require decoding and executing the user's intended movement. Previous studies, using invasive and non-invasive brain signals, have shown promising results in decoding movement directio ...

EPFL2012

Interaction and Evaluation of an Augmented Virtuality Assistance System for Teleoperated Robots

José del Rocio Millán Ruiz, Tom Edward Carlson, Tomas de Jesus Mateo Sanguino

This paper presents the main features and capabilities of a developed system based on augmented virtuality (AV), which is devoted to the assisted navigation of teleoperated robots. The goal is to provide users with a greater perception of the robot navigat ...

2012

Latency Correction of Error Potentials Between Different Experiments Reduces Calibration Time for Single-Trial Classification

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

One fundamental limitation of EEG-based brain- computer interfaces is the time needed to calibrate the system prior to the detection of signals, due to the wide variety of issues affecting the EEG measurements. For event-related potentials (ERP), one of th ...

2012

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

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

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

Improved Recognition of Error Related Potentials through the use of Brain Connectivity Features

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Mohit Kumar Goel, Lucian Andrei Gheorghe, Huaijian Zhang

Brain error processing plays a key role in goal-directed behavior and learning in human brain. Directed transfer function (DTF) on EEG signal brings unique features for discrimination between correct and error cases in braincomputer interface (BCI) system. ...

Ieee2012

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