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Ricardo Andres Chavarriaga Lozano

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Publications associées (138)

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

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

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future

Ricardo Andres Chavarriaga Lozano, Robert Leeb

The Fifth International Brain-Computer Interface (BCI) Meeting met on 3rd June 2013 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 19 workshops covering topics in brain-computer interface and brain-machine inter ...

2014

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

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

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

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

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

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

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

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

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

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

Robust Activity Recognition Combining Anomaly Detection and Classifier Retraining

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

IEEE2013

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

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

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