José del Rocio Millán Ruiz

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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 ...

Opportunistic sensing can be used to obtain data from sensors that just happen to be present in the user’s surroundings. By harnessing these opportunistic sensor configurations to infer activity or context, ambient intelligence environments become more rob ...

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 ...

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 ...

The promise of Brain-Computer Interfaces (BCI) technology is to augment human capabilities by enabling interaction with computers through a conscious and spontaneous modulation of the brainwaves after a short training period. Indeed, by analyzing brain ele ...

Attentional shifts precede most of the perceptual processes, and therefore their recognition may constitute an interesting process for both the study of human perception as well as the design of EEG-based Brain Computer Interfaces (BCI). Several studies ha ...

Robotic assistance via motorized robotic arm manipulators can be of valuable assistance to individuals with upper-limb motor disabilities. Brain-computer interfaces (BCI) offer an intuitive means to control such assistive robotic manipulators. However, BCI ...

Hand sensorimotor impairments are among the most common consequences of injuries affecting the central and peripheral nervous systems, leading to a drastic reduction in the quality of life for affected individuals. Combining wearable robotic exoskeletons a ...

Brain-machine interfaces (BMIs) have been applied as new rehabilitation tools for motor disabled individuals. Active involvement of cerebral activity has been shown to enhance neuroplasticity and thus to restore mobility. Various studies have focused on th ...

Introduction Diagnosis and prediction of recovery in the acute phase of disorders of consciousness (DOC) are critical for subsequent medical decisions. However, reliable assessment remains elusive due to the inability of current validated clinical scales t ...

Anticipation increases the efficiency of daily tasks by partial advance activation of neural substrates involved in it. Here we develop a method for the recognition of electroencephalogram (EEG) correlates of this activation as early as possible on single ...

Decoding speech from intracranial recordings serves two main purposes: understanding the neural correlates of speech processing and decoding speech features for targeting speech neuroprosthetic devices. Intracranial recordings have high spatial and tempora ...

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 ...

This article introduces the field of brain-computer interfaces (BCI), which allows the control of devices without the generation of any active motor output but directly from the decoding of the user's brain signals. Here we review the current state of the ...

Performance improvement in both humans and artificial systems strongly relies in the ability of recognizing erroneous behavior or decisions. This paper, that builds upon previous studies on EEG error-related signals, presents a hybrid approach for human co ...

This article proposes a novel shared intelligence system for brain-machine interface (BMI) teleoperated mobile robots where user's intention and robot's intelligence are concurrent elements equally participating in the decision process. We designed the sys ...

Upper limb motor deficits in severe stroke survivors often remain unresolved over extended time periods. Novel neurotechnologies have the potential to significantly support upper limb motor restoration in severely impaired stroke individuals. Here, we revi ...

To patients who have lost the functionality of their hands as a result of a severe spinal cord injury or brain stroke, the development of new techniques for grasping is indispensable for reintegration and independency in daily life. Functional Electrical S ...

Single trial recognition of slow cortical potentials (SCPs) from full-band EEG (FbEEG) faces different challenges to classical EEG such as noisy, high magnitude (~±100µV) infra slow oscillations (ISO) with f

Non–Invasive Brain–Computer Interfaces (BCI) convey a great potential in the field of stroke rehabilitation, where the continuous monitoring of mental tasks execution could support the positive effects of standard therapies. In this paper we combine time-f ...

José del Rocio Millán Ruiz

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On-line anomaly detection and resilience in classifier ensembles

The OPPORTUNITY Framework and Data Processing Ecosystem for Opportunistic Activity and Context Recognition

Latency Correction of Event-Related Potentials Between Different Experimental Protocols

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

Non-Invasive Brain-Actuated Interaction

EEG-based Recognition of Covert Attentional Shifts

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

mano: A Wearable Hand Exoskeleton for Activities of Daily Living and Neurorehabilitation

Decoding of Self-paced Lower-Limb Movement Intention: A Case Study on the Influence Factors

EEG paradigms as a supplemental tool to behavioral assessments of DOC

Fast Recognition of Anticipation Related Potentials

The use of intracranial recordings to decode human language: Challenges and opportunities

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

The Human-Computer Connection An Overview Of Brain-Computer Interfaces

Adaptation of Hybrid Human-Computer Interaction Systems using EEG Error-Related Potentials

Shared Intelligence for Robot Teleoperation via BMI

Neurotechnology-aided interventions for upper limb motor rehabilitation in severe chronic stroke

On The Road To A Neuroprosthetic Hand: A Novel Hand Grasp Orthosis Based on Functional Electrical Stimulation

Single Trial Recognition of Anticipatory Slow Cortical Potentials: The Role of Spatio-Spectral Filtering

Combining Discriminant and Topographic Information in BCI: Preliminary Results on Stroke Patients