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José del Rocio Millán Ruiz

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Related publications (230)

Corticospinal neuroprostheses to restore locomotion after spinal cord injury

José del Rocio Millán Ruiz, Stéphanie Lacour, Silvestro Micera, Grégoire Courtine, Nikolaus Wenger, Ivan Rusev Minev, Marco Bonizzato, Janine Beauparlant, Eduardo Martin Moraud, Pavel Musienko, David Allenson Borton

In this conceptual review, we highlight our strategy for, and progress in the development of corticospinal neuroprostheses for restoring locomotor functions and promoting neural repair after thoracic spinal cord injury in experimental animal models. We spe ...

Elsevier2014

Clinical evaluation of BrainTree, a motor imagery hybrid BCI speller

José del Rocio Millán Ruiz, Michele Tavella, Serafeim Perdikis, Robert Leeb

Objective. While brain-computer interfaces (BCIs) for communication have reached considerable technical maturity, there is still a great need for state-of-the-art evaluation by end-users outside laboratory environments. To achieve this primary objective, i ...

Institute of Physics2014

Prediction of Command Delivery Time for BCI

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Sareh Saeedi, Tom Edward Carlson, Inaki Asier Iturrate Gil

One of the challenges in using brain computer interfaces over extended periods of time is the uncertainty in the system. This uncertainty can be due to the user's internal states, the non stationarity of the brain signals, or the variation of the class dis ...

2014

Towards Implementation of Motor Imagery using Brain Connectivity Features

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

This study aims to explore modulation of the connectivity pattern when people perform left hand versus right hand motor imagery and probe the feasibility of adopting connectivity information to discriminate these tasks. Nine subjects were recorded with 16- ...

2014

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

Single trial prediction of self-paced reaching directions from EEG signals

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

Early detection of movement intention could possibly minimize the delays in the activation of neuroprosthetic devices. As yet, single trial analysis using non-invasive approaches for understanding such movement preparation remains a challenging task. We st ...

Frontiers Research Foundation2014

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

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

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

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

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, 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

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

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, 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

Latency correction of error-related potentials reduces BCI calibration time

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

Calibration of brain-machine interfaces exploiting event-related potentials has to be performed for each experimental paradigm. Even if these signals have been used in previous experiments with different protocols. We show that use of signals from previous ...

2014

BMI: Lessons from Tests with Impaired Users

José del Rocio Millán Ruiz

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 ...

2014

Latency Correction of Event-Related Potentials Between Different Experimental Protocols

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

Objective: A fundamental issue in EEG event-related potentials (ERPs) studies is the amount of data required to have an accurate ERP model. This also impacts the time required to train a classifier for a brain-computer interface (BCI). This issue is mainly ...

Institute of Physics2014

Subject-oriented training for motor imagery brain-computer interfaces

José del Rocio Millán Ruiz, Serafeim Perdikis, Robert Leeb

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

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

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

Detecting Cognitive States for Enhancing Driving Experience

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

Intelligent cars exploit environmental information to support drivers by providing extra information and assisting complex maneouvers. They can also take into account the internal state of the driver by means of decoding cognition-related brain activity. H ...

Graz University of Technology Publishing House2013

Transferring BCI skills to successful application controls

José del Rocio Millán Ruiz, Alberto Molina Arribere, Luca Tonin, Serafeim Perdikis, Robert Leeb, Andrea Biasiucci, Marco Creatura, Tom Edward Carlson

The goal of our research is to enable various end-users to control applications by using a brain-computer interface (BCI). Since applications–like telepresence robots, wheelchairs or text entry systems–are quite demanding a good level of BCI control is nee ...

2013

Transferring brain-computer interfaces beyond the laboratory: Successful application control for motor-disabled users

José del Rocio Millán Ruiz, Alberto Molina Arribere, Luca Tonin, Michele Tavella, Serafeim Perdikis, Robert Leeb, Andrea Biasiucci, Marco Creatura, Tom Edward Carlson

OBJECTIVES: Brain-computer interfaces (BCIs) are no longer only used by healthy participants under controlled conditions in laboratory environments, but also by patients and end-users, controlling applications in their homes or clinics, without the BCI exp ...

Elsevier2013

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

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

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 rotatation), which is the case in many real-lif ...

IEEE2013

Selective Enhancement of Motor Imagery Features Using Transcranial Direct Current Stimulation

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Robert Leeb, Andrea Biasiucci

Transcranial Direct Current Stimulation (tDCS) has been shown to selectively modulate cortical responses in memory, motor and perceptual tasks. Here we show that this type of stimulation results in targeted enhancement of brain patterns elicited during mot ...

Graz University of Technology Publishing House2013

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