Towards a Brain-Controlled Wheelchair by discrimination of two mental states

En este artículo se presentan los trabajos preliminares del grupo UMA-BCI de la Universidad de Málaga relacionados con la posibilidad de controlar una silla de ruedas motorizadas a través de una Interfaz Cerebro Computadora, siendo esto parte de los objetivos del proyecto TEC2011-26395.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Interfaz cerebro-computadora : pensamientos al servicio

Las señales que emite el encéfalo abren muchas posibilidades a personas con deficiencias en sus funciones motoras. Un paso adelante en su calidad de vida y donde, con el correcto entrenamiento, imaginación y realidad pueden interactuar

Brain-computer interface for communication and control purpose

Brain-computer interfaces (BCI) are a type of assistive technology (AT) that uses the brain signals of users to establish a communication and control channel between them and an external device (usually a computer). BCI systems may be a suitable tool to restore communication skills in severely motor-disabled patients, as BCI do not rely on muscular control. There are several diseases that cause severe impairment of motor skills in affected patients, such as amyotrophic lateral sclerosis (ALS). The loss of communication (mainly with family and caregivers) is considered by ALS patients as even more negative than the loss of physical aspects. Another interesting assistive technology to improve the quality of life of these patients is the control of a domotic system through a BCI. Therefore, the objective of this work is to present the latest developed application of the UMA BCI group to provide communication and control system through brain activity for ALS patients. This application will focus on the use of a BCI that could allow patient communication through some of the most common messaging applications on a smartphone (WhatsApp, e-mail and SMS), and domotic control for controlling device such as a TV, air conditioner, music and lights. The control of the BCI is achieved through the well-known visual P300 row-column paradigm (RCP), allowing the user to select control commands as well as spelling characters.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Usability study of different platforms to Develop Communication Systems based on P300-Brain-Computer Interface (BCI).

People suffering from neurodegenerative disorders, such as Amyotrophic Lateral Sclerosis (ALS), can eventually present great disabilities. In some cases, these patients lose all possibility to communicate with the external world via common muscular channels, being the only alternative the use of a Brain-Computer Interface (BCI) system, which transforms brain activity into external commands. A P300-speller is a typical Brain-Computer Interface system for communication purpose. In order to facilitate the communication, it is very important to adapt the speller to each patient. The most popular platforms to develop P300 speller are BCI2000, OpenVibe and UMA-BCI Speller. The goal of this study was to evaluate the usability of the three proposed platforms in terms of effectiveness, efficiency and satisfaction. To this end, three participants had to configure a specific speller layout using the 3 platforms. The obtained results indicated that the UMA-BCI Speller platform presented the highest level of usability, following by the BCI2000 and finally, the OpenVibe platform. In this sense, the UMA-BCI Speller seems to be an easy application to use, providing many options and allowing to configure any speller layout in an easy way.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Proposal of a P300-based BCI Speller using a predictive Text system

This paper presents a P300-based BCI speller system that uses a virtual 4 x 3 keyboard based on the T9 interface developed on mobile phones in order to increase the writing speed. To validate the effectiveness of the proposed BCI, we compared it with two adaptations of the classical Farwell and Donchin speller, which is based on a 6 x 6 symbol matrix. Three healthy subjects took part in the experiment. The preliminary results confirm the effectiveness of T9-based speller, since the time needed to spell words and complete sentences was considerably reduced.This work was partially supported by the Innovation, Science and Enterprise Council of the Junta de Andalucía (Spain), project P07-TIC-03310, the Spanish Ministry of Science and Innovation, project TEC 2011-26395 and by the European fund ERDF

Review of real brain-controlled wheelchairs

This paper presents a review of the state of the art regarding wheelchairs driven by a brain-computer interface (BCI). Using a brain-controlled wheelchair (BCW), disabled users could handle a wheelchair through their brain activity, granting autonomy to move through an experimental environment. A classification is established, based on the characteristics of the BCW, such as the type of electroencephalographic (EEG) signal used, the navigation system employed by the wheelchair, the task for the participants, or the metrics used to evaluate the performance. Furthermore, these factors are compared according to the type of signal used, in order to clarify the differences among them. Finally, the trend of current research in this field is discussed, as well as the challenges that should be solved in the future

Proposals of Control Paradigms Applied to a Brain-Controlled Wheelchair

Proposals of Control Paradigms Applied to a Brain-Controlled Wheelchair, Ron-Angevin R., Velasco-Álvarez F., Fernández Rodriguez A., Proceeding og the BITs 4th Annual World Congress of Smart Material 2018, Osaka (Japan), 6-8 March 2018Several of the neurological diseases that human beings can result in severe disabilities. In some cases, people who suffer from such deficiencies lose any chance of communication with their environment, being the only possible alternative to give the brain a new channel not based on muscular activity, allowing these people to send messages and commands to the external world. The systems that allows the latter is what is known as Brain-Computer Interfaces (BCI). Their common feature is to process the brain’s electrical activity for extracting information that can be used to command an external device, as for example, a wheelchair to provide them some mobility. One of the most important limitations of these brain controlled wheelchair is to guarantee that a person can, through his mental activity, safely control the variety of navigation commands that provide control of the wheelchair: advance, turn, move back, and stop. The vast majority of the mobile robot navigation applications that are controlled via a BCI demand that the user performs as many different mental tasks as there are different control commands, worsening the classification accuracy. In order to enable an effective and autonomous wheelchair navigation with a BCI system without worsening user performance, the Brain–Computer Interface (BCI) group of the University of Málaga (UMA-BCI) proposed and later developed a new paradigm based on the discrimination of only two classes (one active mental task versus any other mental activity), which enabled the selection of four commands: move forwards, turn right, move backward and turn left. The final aim of this contribution is to show how to control a robotic wheelchair through the use of only two mental tasks. The mapping of these two mental tasks into several navigation commands allows the Brain-Controlled Wheelchair to be moved and turned in order to achieve effective navigation.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Brain switch mode: an alternative to drive a brain-controlled wheelchair

To date, different control paradigms of low level navigation have been tested for brain-controlled wheelchairs, mainly divided into continuous or discrete control [1]. However, these paradigms have certain drawbacks such as the need to keep the mental tasks active for a long time, as in continuous mode, or the impossibility to freely choose any distance of the movement or the turn, as in the discrete mode. An alternative paradigm to solve these problems could be the use of the brain switch mode [2], which would allow a more flexible control of the distance, requiring a lower workload for the user.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Systèmes de communication basés sur les interfaces cerveaux-ordinateurs

L’objectif des interfaces cerveau-ordinateur est de fournir aux patients d’un nouveau canal de communication et de contrôle non musculaire pour leur permettre de communiquer avec le monde extérieur. Le but de cet article est de présenter les derniers travaux réalisés par le groupe de recherche UMA-BCI de l’Université de Málaga (Espagne), étant l’objectif principal offrir des systèmes de communication, basés sur les paradigmes RCP et RSVP, qui permettent à des patients atteints de la maladie de Charcot de communiquer à travers différentes plateformes.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Retroalimentación en el entrenamiento de una interfaz cerebro computadora usando técnicas basadas en realidad virtual

Una interfaz cerebro-computadora o BCI (Brain-Computer Interface), se basa principalmente en el análisis de las señales electroencefalográficas (señales EEG) captadas durante algún tipo de actividad mental con la finalidad de controlar un componente externo. Sus prestaciones dependerán en gran medida de la capacidad que tenga un sujeto para controlar sus patrones EEG, siendo necesario un adecuado entrenamiento que en algunos casos puede llegar a extenderse en el tiempo, y resultando imprescindible proporcionar algún tipo de retroalimentación (feedback) que le permita conocer su evolución. El objetivo de esta tesis se centra en realizar un estudio sobre las posibles consecuencias de utilizar un feedback basado en técnicas de realidad virtual en el entrenamiento de los sistemas BCI. Para realizar dicho estudio y poder validarlo, ha sido necesario comparar los resultados obtenidos al emplear estas técnicas con aquellos obtenidos a través de un sistema BCI de referencia basado en un feedback convencional como la extensión de una barra horizontal. Dicho estudio comparativo ha obligado por lo tanto a desarrollar dos tipos diferentes de interfaces cerebro-computadora y en definitiva, realizar el trabajo en dos fases diferentes. En una primera fase, se ha desarrollado y evaluado el sistema BCI de referencia permitiendo obtener resultados que pudieran ser comparados con la interfaz objeto de este trabajo. En una segunda fase, se ha desarrollado y evaluado el sistema BCI basado en técnicas de realidad virtual. Los resultados obtenidos muestran un comportamiento distinto en la respuesta de los sujetos logrando un mejor control de las señales EEG, en especial durante el periodo del feedback. Parece que el uso de una interfaz que resulte más familiar y más atractiva a los sujetos permite lograr una mayor motivación e integración de éstos y puede mejorar los resultados de clasificación, al mismo tiempo que permite una mayor y más rápida adaptación del sujeto al paradigma de entrenamiento