A note on brain actuated spelling with the Berlin brain-computer interface

Brain-Computer Interfaces (BCIs) are systems capable of decoding neural activity in real time, thereby allowing a computer application to be directly controlled by the brain. Since the characteristics of such direct brain-tocomputer interaction are limited in several aspects, one major challenge in BCI research is intelligent front-end design. Here we present the mental text entry application ‘Hex-o-Spell’ which incorporates principles of Human-Computer Interaction research into BCI feedback design. The system utilises the high visual display bandwidth to help compensate for the extremely limited control bandwidth which operates with only two mental states, where the timing of the state changes encodes most of the information. The display is visually appealing, and control is robust. The effectiveness and robustness of the interface was demonstrated at the CeBIT 2006 (world’s largest IT fair) where two subjects operated the mental text entry system at a speed of up to 7.6 char/min

Augmentative and alternative communication (AAC) advances: A review of configurations for individuals with a speech disability

High-tech augmentative and alternative communication (AAC) methods are on a constant rise; however, the interaction between the user and the assistive technology is still challenged for an optimal user experience centered around the desired activity. This review presents a range of signal sensing and acquisition methods utilized in conjunction with the existing high-tech AAC platforms for individuals with a speech disability, including imaging methods, touch-enabled systems, mechanical and electro-mechanical access, breath-activated methods, and brain–computer interfaces (BCI). The listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. A revelation of the associated AAC signal processing, encoding, and retrieval highlights the roles of machine learning (ML) and deep learning (DL) in the development of intelligent AAC solutions. The demands and the affordability of most systems hinder the scale of usage of high-tech AAC. Further research is indeed needed for the development of intelligent AAC applications reducing the associated costs and enhancing the portability of the solutions for a real user’s environment. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds. The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications

Proposta de uso de estado emocional do indivíduo na automação de ambiente inteligente

A questão de pesquisa que este estudo pretende abordar visa melhorar a qualidade de vida dos usuários, especialmente os portadores de necessidades especiais, adaptando o ambiente ao seu conforto emocional. Nesse contexto, o objetivo da presente pesquisa é a elaboração de um ambiente inteligente controlado passivamente através do estado emocional do usuário, utilizando interface cérebro computador. De forma geral, espera-se com este estudo ser capaz de adaptar um sistema inteligente de acordo com a emoção objetivo, visando o aumentando do rendimento do indivíduo numa dada tarefa, auxiliando em tratamentos terapêuticos ou aumentando o seu conforto. Para validação do trabalho foi utilizada a interface cérebrocomputador da empresa Emotiv com o sistema de automação predial-residencial da empresa Home Systems, utilizando algoritmo genético para buscar a configuração adequada do ambiente tendo o nível de atenção como emoção objetivo. Os resultados preliminares dos nove testes realizados com seis indivíduos comprovam que é viável o controle de ambientes baseado no estado emocional dos usuários. Este trabalho situa-se na interdisciplinaridade de áreas como engenharia elétrica, computação, psicologia comportamental e tecnologias assistivas.The research question that this study aims to approach is to improve the quality of life of individuals with or without special needs, by adapting the environment to their emotional comfort. In this context, the goal of this research is to develop an intelligent system passively controlled trough brain-computer interface. In general, it is expected with this study to be able to adapt a smart environment according to the emotional target, aiming to increase the yield of a given individual task, assisting in therapeutics or increasing the individual’s comfort. In order to validate the experiment, Emotiv’s brain computer interface was used with Home Systems’ home automation system, using genetic algorithm to find the appropriate configuration of the environment and attention level as the emotional target. Preliminary results of the nine tests conducted on six subjects indicate that it is feasible to control a smart environment based on the emotional state of the user. This is an interdisciplinary work in areas such as electrical engineering, computer science, behavioral psychology and assistive technologies