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José del Rocio Millán Ruiz

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Related publications (230)

Inferring Driver’s Turning Direction through Detection of Error Related Brain Activity

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

This work presents EEG-based Brain-computer interface (BCI) that uses error related brain activity to improve the prediction of driver’s intended turning direction. In experiments while subjects drive in a realistic car simulator, we show a directional cue ...

2013

Making the most of context-awareness in brain-computer interfaces

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi, Tom Edward Carlson

In order for brain-computer interfaces (BCIs) to be used reliably for extended periods of time, they must be able to adapt to the users evolving needs. This adaptation should not only be a function of the environmental (external) context, but should also c ...

2013

Single trial analysis of slow cortical potentials: A study on anticipation related potentials

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Gangadhar Garipelli

Objective. Abundant literature suggests the use of Slow Cortical Potentials (SCPs) in a wide spectrum of basic and applied neuroscience areas. Due to low signal to noise ratio, often these potentials are studied using grand-average analysis, which conceal ...

Institute of Physics2013

Robust Activity Recognition Combining Anomaly Detection and Classifier Retraining

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

Activity recognition systems based on body-worn motion sensors suffer from a decrease in performance during the deployment and run-time phases, because of probable changes in the sensors (e.g. displacement or rotation), which is the case in many real-life ...

2013

The hybrid Brain-Computer Interface: a bridge to assistive technology?

José del Rocio Millán Ruiz, Robert Leeb

Brain-Computer Interfaces (BCIs) can be extended by other input signals to form a so-called hybrid BCI (hBCI). Such an hBCI allows the processing of several input signals with at least one brain signal for control purposes, i.e. communication and environme ...

De Gruyter2013

On the Need for Both Internal and External Context Awareness for Reliable BCIs

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi, Tom Edward Carlson

In this paper we argue that for brain-computer interfaces (BCIs) to be used reliably for extended periods of time, they must be able to adapt to the user’s evolving needs. This adaptation should not only be a function of the environmental (external) contex ...

2013

An Iterative Framework for EEG-based Image Search: Robust Retrieval with Weak Classifiers

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Marija Uscumlic

We revisit the framework for brain-coupled image search, where the Electroencephalography (EEG) channel under rapid serial visual presentation protocol is used to detect user preferences. Extending previous works on the synergy between content-based image ...

Public Library of Science2013

On-line anomaly detection and resilience in classifier ensembles

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

Detection of anomalies is a broad field of study, which is applied in different areas such as data monitoring, navigation, and pattern recognition. In this paper we propose two measures to detect anomalous behaviors in an ensemble of classifiers by monitor ...

Elsevier2013

Unsupervised adaptation for acceleration-based activity recognition: Robustness to sensor displacement and rotation

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

A common assumption in activity recognition is that the system remains unchanged between its design and its posterior operation. However, many factors affect the data distribution between two different experimental sessions. One of these factors is the pot ...

Springer Verlag2013

Personalized neuroprosthetics

José del Rocio Millán Ruiz, Silvestro Micera, Grégoire Courtine, David Allenson Borton

Decades of technological developments have populated the field of neuroprosthetics with myriad replacement strategies, neuromodulation therapies, and rehabilitation procedures to improve the quality of life for individuals with neuromotor disorders. Despit ...

American Association for the Advancement of Science2013

Error Potentials for Brain-Computer Interfaces

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

The idea to use EEG correlates of errors to correct or reinforce BCI operation has been proposed over a decade ago. Since then a body of evidence has corroborated this approach. In this paper we give an overview of our recent work exploring the possibiliti ...

Graz University of Technology Publishing House2013

Steering Timing Prediction in a Driving Simulator Task

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

In this paper we present the preliminary results of a pioneering attempt to predict the timing of steering actions in a driving task from non-invasive EEG measurements. The experiment took place with the subjects driving a car at a constant speed on a simu ...

2013

Inverse Solutions for Brain Computer Interface

José del Rocio Millán Ruiz, Mohit Kumar Goel

Inverse solution allows to estimate sources that generate a given scalp EEG topography. Recently, it has been used in Brain Computer Interfaces (BCIs) to extract robust features based on the hypothesis that projection onto the source space (high dimensiona ...

EPFL2013

Feel the BCI vibe – vibrotactile BCI feedback

José del Rocio Millán Ruiz, Robert Leeb

Controlling a device via a brain-computer interface (BCI) requires the participant to look and to split the attention between the device and the BCI feedback, which is partly contradictory. Therefore, a stimulation system based on 6 coin-motors is develope ...

Graz University of Technology Publishing House2013

Iterative EEG-based Natural Image Search under RSVP

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Marija Uscumlic

This work extends previous studies on using EEG decoding for automatic image retrieval. We propose an iterative way to integrate the information obtained from the EEG decoding and image processing methods. In the light of real-world BCI applications, we de ...

Graz University of Technology Publishing House2013

Opportunistic human activity and context recognition

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

Although the Internet of Things allows seamless access to billions of sensors readily deployed throughout the world, current context- and activity-recognition approaches restrict ambient intelligence to domains where dedicated sensors are deployed. The big ...

Institute of Electrical and Electronics Engineers2013

Motor Recovery After Stroke by Means of BCI-Guided Functional Electrical Stimulation

José del Rocio Millán Ruiz, Robert Leeb, Andrea Biasiucci

Brain-Computer Interfaces (BCIs) provide a mean to access the damaged motor network of the brain after stroke, and could be used to drive and promote beneficial plasticity. Among the available therapeutic approaches, Functional Electrical Stimulation (FES) ...

2013

Brain–machine interface: closer to therapeutic reality?

José del Rocio Millán Ruiz, Silvestro Micera, Grégoire Courtine

Elsevier Science Inc2013

Brain-Controlled Wheelchairs: A Robotic Architecture

José del Rocio Millán Ruiz, Tom Edward Carlson

Independent mobility is core to being able to perform activities of daily living by oneself. However, powered wheelchairs are not an option for a large number of people who are unable to use conventional interfaces, due to severe motor–disabilities. Non-in ...

Institute of Electrical and Electronics Engineers2013

Brain-Actuated Assistive Mobility For Disabled End-User

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

Brain-Computer Interfaces (BCIs) have been successfully used to control assistive mobility devices (like a telepresence robot or an electric wheelchair) using only motor imagery. Importantly, disabled end-users are able to achieve similar performances as h ...

De Gruyter2013

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