Eduardo Ianez

article

Effect of tDCS stimulation of motor cortex and cerebellum on EEG classification of motor imagery and sensorimotor band power

Irma N. Angulo-Sherman, Marisol Rodríguez-Ugarte, Nadia Sciacca, Eduardo Iáñez, more

Journal of NeuroEngineering and Rehabilitation > 2017 > 14 > 1 > 1-16

Background Transcranial direct current stimulation (tDCS) is a technique for brain modulation that has potential to be used in motor neurorehabilitation. Considering that the cerebellum and motor cortex exert influence on the motor network, their stimulation could enhance motor functions, such as motor imagery, and be utilized for brain-computer interfaces (BCIs) during motor neurorehabilitation....

chapter

Analysis of EEG Mapping Images to Differentiate Mental Tasks in Brain-Computer Interfaces

Andrés Úbeda, Eduardo Iáñez, José M. Azorín, Eduardo Fernández

Lecture Notes in Computer Science > Foundations on Natural and Artificial Computation > 246-255

This paper describes a study of a new classifier based on EEG mapping analysis in order to develop a Brain-Computer Interface (BCI) through computer vision techniques. To this end, the data from three different subjects (BCI Competition Data Set V) have been studied to show proper EEG maps of the three mental tasks registered. A new classifier based on image analysis of the EEG maps has been presented...

chapter

Detection of intention of pedaling start cycle through EEG signals

Marisol Rodriguez-Ugarte, Enrique Hortal, Alvaro Costa, Eduardo Ianez, more

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) > 1496 - 1499

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Recovery from cerebrovascular accident (CVA) is a growing research topic. Exoskeletons are being used for this purpose in combination with a volitional control algorithm. This work studied the intention of pedaling initiation movement, based on previous work, with different types of electrode configuration and different processing time windows. The main characteristic is to find alterations in the...

chapter

Brain-Robot Interface for Controlling a Remote Robot Arm

Eduardo Iáñez, M. Clara Furió, José M. Azorín, José Alejandro Huizzi, more

Lecture Notes in Computer Science > Bioinspired Applications in Artificial and Natural Computation > 353-361

This paper describes a technique based on electroencephalography (EEG) to control a robot arm. This technology could eventually allow people with severe disabilities to control robots that can help them in daily living activities. The EEG-based Brain Computer Interface (BCI) developed consists in register the brain rhythmic activity through a electrodes situated on the scalp in order to differentiate...

chapter

P300-Based Brain-Computer Interface for Internet Browsing

José L. Sirvent, José M. Azorín, Eduardo Iáñez, Andrés Úbeda, more

Advances in Intelligent and Soft Computing > Trends in Practical Applications of Agents and Multiagent Systems > Workshop on Systems, Man, & Cybernetics: SMC-Workshop.- IEEE.- SPANISH CHAPTER > 615-622

This paper describes the implementation of a Brain-Computer Interface (BCI) for controlling Internet browsing. The system uses electroencephalographic (EEG) signals to control the computer by evoked potentials through the P300 paradigm. This way, using visual stimulus, the user is able to control the Internet navigation via a virtual mouse and keyboard. The system has been developed under the BCI2000...

article

Combining a Brain–Machine Interface and an Electrooculography Interface to perform pick and place tasks with a robotic arm

Enrique Hortal, Eduardo Iáñez, Andrés Úbeda, Carlos Perez-Vidal, more

Robotics and Autonomous Systems > 2015 > 72 > Complete > 181-188

This paper presents a multimodal Human–Machine Interface system that combines an Electrooculography Interface and a Brain–Machine Interface. This multimodal interface has been used to control a robotic arm to perform pick and place tasks in a three dimensional environment. Five volunteers were asked to pick two boxes and place them in different positions. The results prove the feasibility of the system...

chapter

Studying Cognitive Attention Mechanisms during Walking from EEG Signals

Alvaro Costa, Rocio Salazar-Varas, Eduardo Ianez, Andres Ubeda, more

2015 IEEE International Conference on Systems, Man, and Cybernetics > 882 - 886

2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

On this work several studies related to the analysis of electroencephalographically signals to evaluate the cognitive mechanisms during human gait are compiled. This research is performed in the framework of an European project (BioMot project) oriented to the development of a lower limb exoskeleton controlled by signals from physiological and kinematic sources. The project includes the study of the...

chapter

Single joint movement decoding from EEG in healthy and incomplete spinal cord injured subjects

Andres Ubeda, Alvaro Costa, Eduardo Ianez, Elisa Pinuela-Martin, more

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) > 6179 - 6183

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

In this paper, linear regression models will be used to decode individual joint angles from low frequency EEG components. To that end, isotonic flexion/extension knee movements will be analyzed. Particularly, the decoding performance of healthy and incomplete spinal cord injured subjects will be assessed to determine the behavior of this methodology with motor disabled people. When studying cortical...

chapter

Active learning for adaptive brain machine interface based on Software Agent

Javier Castillo-Garcia, Enrique Hortal, Teodiano Bastos, Eduardo Ianez, more

2015 23rd Mediterranean Conference on Control and Automation (MED) > 44 - 48

2015 23rd Mediterranean Conference on Control and Automation (MED)

Brain Machine Interface (BMI) and Software Agent (SA) can provide some new adaptive strategies for robust BMI implementations. In this work, a non-invasive Adaptive BMI is introduced, which has been designed to discriminate four mental tasks. The SA allows tracking features to contribute for an adaptive process, while the user's engagement state provides a feedback between BMI and the environment...

chapter

Nonlinear bilateral control of teleoperators by state convergence

Jose Maria Azorin, Jose Angel Berna, Eduardo Ianez

2009 European Control Conference (ECC) > 2815 - 2820

2009 European Control Conference (ECC)

This paper presents a new nonlinear bilateral control method for telerobotics based on the state convergence framework. Considering the nonlinear systems of the master and slave, the exact linearization is applied in order to obtain the equivalent linear systems. This way, the convergence methodology is used to design the control scheme considering the equivalent linear systems. Then, the control...

chapter

Selection of the best mental tasks for a SVM-based BCI system

Enrique Hortal, Eduardo Ianez, Andres Ubeda, Daniel Planelles, more

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) > 1483 - 1488

2014 IEEE International Conference on Systems, Man and Cybernetics - SMC

In this work, a study that analyzes the best combinations of mental tasks in a Brain-Computer Interface (BCI) using a classifier based on Support Vector Machine (SVM) is presented. To that end, 12 mental tasks of different nature are analyzed and the results of the classification for the combinations of two, three and four tasks are obtained. Four volunteers performed registers of the 12 tasks. The...

chapter

Decoding knee angles from EEG signals for different walking speeds

Andres Ubeda, Daniel Planelles, Alvaro Costa, Enrique Hortal, more

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) > 1475 - 1478

2014 IEEE International Conference on Systems, Man and Cybernetics - SMC

Recent studies have hypothesized that the motor cortex is particularly active during specific phases of gait cycle. It has been found that cortical coherence appearance differs in time depending on walking speed. In this work, we analyze the influence of walking speed by decoding knee angles from low frequency EEG components. Linear regression models are applied to show significant correlations between...

article

Control of a 2 DoF robot using a Brain–Machine Interface

Enrique Hortal, Andrés Úbeda, Eduardo Iáñez, José M. Azorín

Computer Methods and Programs in Biomedicine > 2014 > 116 > 2 > 169-176

In this paper, a non-invasive spontaneous Brain–Machine Interface (BMI) is used to control the movement of a planar robot. To that end, two mental tasks are used to manage the visual interface that controls the robot. The robot used is a PupArm, a force-controlled planar robot designed by the nBio research group at the Miguel Hernández University of Elche (Spain). Two control strategies are compared:...

chapter

Online classification of two mental tasks using a SVM-based BCI system

Enrique Hortal, Andres Ubeda, Eduardo Ianez, Daniel Planelles, more

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) > 1307 - 1310

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)

A Brain-Computer Interface (BCI) can be very useful to help people with several movement disabilities to improve their independence or to assist them in rehabilitation tasks. In this paper, the results of the online classification of two mental tasks from electroencephalographic signals (EEG) are shown. The objective of this paper is to determine whether the accuracy in the online differentiation...

chapter

Passive robot assistance in arm movement decoding from EEG signals

Andres Ubeda, Enrique Hortal, Eduardo Ianez, Daniel Handles, more

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) > 895 - 898

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)

The past decade has seen the rapid development of upper limb kinematic decoding techniques by performing intracortical recordings of brain signals. However, the use of non-invasive approaches to perform similar decoding procedures is still in its early stages. Previous works show that there is a correlation between electroencephalographic signals and position/velocity hand movement parameters. In...

article

Endogenous brain–machine interface based on the correlation of EEG maps

Andrés Úbeda, Eduardo Iáñez, José M. Azorín, Carlos Perez-Vidal

Computer Methods and Programs in Biomedicine > 2013 > 112 > 2 > 302-308

In this paper, a non-invasive endogenous brain–machine interface (BMI) based on the correlation of EEG maps has been developed to work in real-time applications. The classifier is able to detect two mental tasks related to motor imagery with good success rates and stability. The BMI has been tested with four able-bodied volunteers. First, the users performed a training with visual feedback to adjust...

article

Classification method for BCIs based on the correlation of EEG maps

Andrés Úbeda, Eduardo Iáñez, José M. Azorín, José M. Sabater, more

Neurocomputing > 2013 > 114 > Complete > 98-106

This paper describes a new method of classification for a Brain–Computer Interface (BCI) based on a normalized cross-correlation of EEG maps which represent the mental activity of the brain. An optimization protocol has been designed to choose the main parameters of the classifier in order to increase the accuracy on the classification. This protocol has been tested with the registers provided by...

article

Shared control architecture based on RFID to control a robot arm using a spontaneous brain–machine interface

Andrés Úbeda, Eduardo Iáñez, José M. Azorín

Robotics and Autonomous Systems > 2013 > 61 > 8 > 768-774

This paper describes a shared control architecture combining a Brain–Machine Interface (BMI) with Radio-frequency Identification (RFID) technology to control a robot arm in pick and place operations. A non-invasive spontaneous BMI capable of distinguishing between three different mental tasks has been designed. Using the BMI, the user can control the robot in order to perform complex actions (e.g...

chapter

Linear decoding of 2D hand movements for target selection tasks using a non-invasive BCI system

Andres Ubeda, Eduardo Ianez, Enrique Hortal, Jose M. Azorin

2013 IEEE International Systems Conference (SysCon) > 778 - 782

2013 7th Annual IEEE Systems Conference (SysCon)

In this paper, a visual interface showing target selection tasks has been designed to decode 2D velocities from a brain-computer interface (BCI) system during hand movements. Ten healthy volunteers were asked to perform hand movements using a mouse to control a cursor on the screen. Three targets were randomly highlighted and the volunteers were asked to reach them with the cursor. The actual position...

chapter

Mental tasks selection method for a SVM-based BCI system

Eduardo Ianez, Andres Ubeda, Enrique Hortal, Jose M. Azorin

2013 IEEE International Systems Conference (SysCon) > 767 - 771

2013 7th Annual IEEE Systems Conference (SysCon)

In this work, a study that analyzes the best combinations of mental tasks in a Brain-Computer Interface (BCI) using a classifier based on Support Vector Machine (SVM) is presented. To that end, twelve mental tasks of different nature are analyzed and the results of the classification for the combinations of two, three and four tasks are obtained. Four volunteers performed registers of the twelve tasks...

INFONA - science communication portal

Search results for: Eduardo Ianez

Effect of tDCS stimulation of motor cortex and cerebellum on EEG classification of motor imagery and sensorimotor band power

Analysis of EEG Mapping Images to Differentiate Mental Tasks in Brain-Computer Interfaces

Detection of intention of pedaling start cycle through EEG signals

Brain-Robot Interface for Controlling a Remote Robot Arm

P300-Based Brain-Computer Interface for Internet Browsing

Combining a Brain–Machine Interface and an Electrooculography Interface to perform pick and place tasks with a robotic arm

Studying Cognitive Attention Mechanisms during Walking from EEG Signals

Single joint movement decoding from EEG in healthy and incomplete spinal cord injured subjects

Active learning for adaptive brain machine interface based on Software Agent

Nonlinear bilateral control of teleoperators by state convergence

Selection of the best mental tasks for a SVM-based BCI system

Decoding knee angles from EEG signals for different walking speeds

Control of a 2 DoF robot using a Brain–Machine Interface

Online classification of two mental tasks using a SVM-based BCI system

Passive robot assistance in arm movement decoding from EEG signals

Endogenous brain–machine interface based on the correlation of EEG maps

Classification method for BCIs based on the correlation of EEG maps

Shared control architecture based on RFID to control a robot arm using a spontaneous brain–machine interface

Linear decoding of 2D hand movements for target selection tasks using a non-invasive BCI system

Mental tasks selection method for a SVM-based BCI system

Filter options

Publication date

Publication type

Keywords

Data set

Journal

INFONA - science communication portal

Search results for: Eduardo Ianez

Add recipient

Sending message cancelled

Are you sure you want to cancel sending this message?

Send message

Filter options

Publication date

Date range setting

Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.

Publication type

Keywords

Data set

Journal

Reporting an error / abuse

Sending the report failed

Accessibility options