José del Rocio Millán Ruiz

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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 ...

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 ...

We describe error-related potentials generated while a human user monitors the performance of an external agent and discuss their use for a new type of Brain-Computer Interaction. In this approach, single trial detection of error-related EEG potentials is ...

The objective of this study is to assess the feasibility of controlling an asynchronous and non-invasive brain-actuated wheelchair by human EEG. Three subjects were asked to mentally drive the wheelchair to 3 target locations using 3 mental commands. These ...

The brain mechanism of embodiment in a virtual body has grown a scientific interest recently, with a particular focus on providing optimal virtual reality (VR) experiences. Disruptions from an embodied state to a less- or non-embodied state, denominated Br ...

Several studies describe evoked EEG potentials elicited when a subject is aware of an erroneous decision either taken by him or by an external interface. This paper try to detect Error-related potentials (ErrP) elicited when a human user want to monitors a ...

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 ...

Objective. Event Related Potentials (ERPs) reflecting cognitive response to external stimuli, are widely used in brain computer interfaces. ERP waveforms are characterized by a series of components of particular latency and amplitude. The classical ERP dec ...

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 ...

Real-time workload estimation can be an important tool to improve human-machine interaction. Despite multiple efforts in this sense, most studies focused on tasks designed to have extreme conditions of workload (high vs low), and these levels remain rather ...

One of the most popular methods in non-invasive brain machine interfaces (BMI) relies on the decoding of sensorimotor rhythms associated to sustained motor imagery. Although motor imagery has been intensively studied, its termination is mostly neglected. O ...

Background: One of the current challenges in brain-machine interfacing is to characterize and decode upper limb kinematics from brain signals, e.g. to control a prosthetic device. Recent research work states that it is possible to do so based on low freque ...

Current non-invasive Brain Machine interfaces commonly rely on the decoding of sustained motor imagery activity. This approach enables a user to control brain-actuated devices by triggering predetermined motor actions. However, despite of its broad range o ...

Objective: This study investigated the effect of multimodal (visual and auditory) continuous feedback with information about the uncertainty of the input signal on motor imagery based BCI performance. A liquid floating through a visualization of a funnel ( ...

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 ...

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 ...

The articles in this special issue focus on brain-computer interfacing. The papers are dedicated to this growing and diversifying research enterprise, and features important review articles as well as some important current examples of research in this are ...

The aim of this work is to present the development of a hybrid Brain-Computer Interface (hBCI) which combines existing input devices with a BCI. Thereby, the BCI should be available if the user wishes to extend the types of inputs available to an assistive ...

Brain responses to visual stimuli can provide information about visual recognition processes. Several studies have shown stimulus-dependent modulation of the evoked neural responses after gaze shifts (i.e. eye fixation related potentials, EFRP) depending o ...

José del Rocio Millán Ruiz

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

Brain–machine interface: closer to therapeutic reality?

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

Learning from EEG Error-related Potentials in Noninvasive Brain-Computer Interfaces

Continuous Brain-Actuated Control of an Intelligent Wheelchair by Human EEG

EEG signature of breaks in embodiment in VR

EEG Error-related Potentials Detection with a Bayesian Filter

BMI: Lessons from Tests with Impaired Users

Spatial covariance improves BCI performance for late ERPs components with high temporal variability

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

Analysis of EEG Correlates of Perceived Difficulty in Dynamically Changing Flying Tasks

User Adaptation to Closed-Loop Decoding of Motor Imagery Termination

Classification of upper limb center-out reaching tasks by means of EEG-based continuous decoding techniques

Reliable decoding of motor state transitions during imagined movement

The effect of multimodal and enriched feedback on SMR-BCI performance

Toward online detection of BCI performance degradation

The Birth of the Brain–Controlled Wheelchair

The Plurality of Human Brain-Computer Interfacing

Tools for brain-computer interaction: a general concept for a hybrid BCI

EEG correlates of active visual search during simulated driving: An exploratory study