Optimization of Brain Computer Interface systems by means of XML and BF++ Toys (original) (raw)
Related papers
A Novel Approach for Configuring the Stimulator of a Bci Framework Using XML
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2009
Dalam BCI (Brain-Computer Interface), setiap aspek harus diperhatikan demi keberhasilan operasional dari sistem BCI tersebut. Termasuk didalamnya adalah proses pembuatan stimulator BCI yang handal dan fleksibel, terutama stimulator yang berkaitan erat dengan umpan balik dalam bentuk aplikasi dari sistem BCI. Makalah ini menjelaskan pendekatan baru untuk membuat stimulator visual yang fleksibel dengan memanfaatkan format XML (Extensible Markup Language) yang dapat diterapkan pada sebuah unit sistem BCI. Dengan menggunakan format XML untuk mengatur konfigurasi dari stimulator visual sebuah unit BCI, kita dapat mengembangkan aplikasi BCI yang mampu mengakomodasi banyak strategi percobaan dalam penelitian tentang BCI. Unit BCI dan platform konfigurasinya dibuat dengan menggunakan bahasa pemrograman C++ dan memanfaatkan XML parser dari Qt yang bernama QXmlStream. Dari hasil implementasi dan pengujian terlihat bahwa file konfigurasi XML dapat dieksekusi dengan baik oleh sistem BCI yang digunakan. Selain kemampuannya dalam menghasilkan frekuensi kedipan yang fleksibel serta pengaturan format teks untuk sistem BCI berbasis SSVEP, file konfigurator tersebut juga memberikan pilihan pemakaian hingga 3 bentuk bangun, 16 warna, dan 5 indikator umpan balik yang berbeda. Metode yang dipaparkan dalam makalah ini dapat dipergunakan untuk meningkatkan kegunaan dari unit BCI yang telah ada saat ini seperti BF++ Toys dan BCI 2000.
A Unified XML based Description of the Contents of Brain Computer Interfaces
In the past decades, a variety of applications and devices were interfaced with EEG based Brain Computer Interfaces (BCIs) with the aim to offer assistive technology to severely handi-capped users. Nevertheless, up to now no standardized description of the possible interaction options (i.e. the tasks a user can perform with the aid of the BCI) was available. Each func-tion provided by an application or device connected to the BCI had to be hard–coded. In this contribution, we propose a new platform–independent XML based description of the interac-tion options. The scheme is interpreted by a middleware layer which connects applications and devices to the BCI. In its current version, scheme and middleware layer are designed for a BCI which provides graphical feedback to the user.
From model to methods: on the Evaluation and the Optimization of Brain Computer Interface Systems
Brain Computer Interface (BCI) systems have gained great visibility in the last years for the possibility they give to severly disabled people to have a normal interaction with the external environment. However every group implements its own BCI system and this leads to a lack of a common language concerning methods, names of BCI components, file formats, tools etc…, with an obvious difficulty in sharing data and resources among labs. This is the reason which induced us to develop a set of methods and tools for the optimization and dissemination of resources dealing with BCI systems.
Describing Different Brain Computer Interface Systems Through a Unique Model: A UML Implementation
Neuroinformatics, 2008
All the protocols currently implemented in brain computer interface (BCI) experiments are characterized by different structural and temporal entities. Moreover, due to the lack of a unique descriptive model for BCI systems, there is not a standard way to define the structure and the timing of a BCI experimental session among different research groups and there is also great discordance on the meaning of the most common terms dealing with BCI, such as trial, run and session. The aim of this paper is to provide a unified modeling language (UML) implementation of BCI systems through a unique dynamic model which is able to describe the main protocols defined in the literature (P300, μ-rhythms, SCP, SSVEP, fMRI) and demonstrates to be reasonable and adjustable according to different requirements. This model includes a set of definitions of the typical entities encountered in a BCI, diagrams which explain the structural correlations among them and a detailed description of the timing of a trial. This last represents an innovation with respect to the models already proposed in the literature. The UML documentation and the possibility of adapting this model to the different BCI systems built to date, make it a basis for the implementation of new systems and a mean for the unification and dissemination of resources. The model with all the diagrams and definitions reported in the paper are the core of the body language framework, a free set of routines and tools for the implementation, optimization and delivery of cross-platform BCI systems.
A UML model for the description of different brain-computer interface systems
2008
BCI research lacks a universal descriptive language among labs and a unique standard model for the description of BCI systems. This results in a serious problem in comparing performances of different BCI processes and in unifying tools and resources. In such a view we implemented a Unified Modeling Language (UML) model for the description virtually of any BCI protocol and we demonstrated that it can be successfully applied to the most common ones such as P300, μ-rhythms, SCP, SSVEP, fMRI. Finally we illustrated the advantages in utilizing a standard terminology for BCIs and how the same basic structure can be successfully adopted for the implementation of new systems.
xBCI: A Generic Platform for Development of an Online BCI System
Ieej Transactions on Electrical and Electronic Engineering, 2010
A generic platform for realizing an online brain–computer interface (BCI) named xBCI was developed. The platform consists of several functional modules (components), such as data acquisition, storage, mathematical operations, signal processing, network communication, data visualization, experiment control, and real-time feedback presentation. Users can easily build their own BCI systems by combining the components on a graphical-user-interface (GUI) based diagram editor. They can also extend the platform by adding components as plug-ins or by creating components using a scripting language. The platform works on multiple operating systems and supports parallel (multi-threaded) data processing and data transfer to other PCs through a network transmission control protocol/internet protocol or user datagram protocol (TCP/IP or UDP). A BCI system based on motor imagery and a steady-state visual evoked potential (SSVEP) based BCI system were constructed and tested on the platform. The results show that the platform is able to process multichannel brain signals in real time. The platform provides users with an easy-to-use system development tool and reduces the time needed to develop a BCI system. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
UnipaBCI a Novel General Software Framework for Brain Computer Interface
Advances in Intelligent Systems and Computing
The increasing interest in Brain Computer Interface (BCI) requires new fast, reliable and scalable frameworks that can be used by researchers to develop BCI based high performance applications in efficient and fast ways. In this paper is presented "UnipaBCI", a general software framework for BCI applications based on electroencephalography (EEG) that can fulfill these new needs. A visual evoked potentials (VEP) application has also been developed using the proposed framework in order to test the modular architecture and the overall performance. Different types of users (beginners and experts in BCI) have been involved during the "UnipaBCI" experimental test and they have exhibited good and comparable results.
2019
Brain-Computer Interfaces (BCIs) are systems that enable a person to manipulate an external device with only brain activity, often using ElectroEncephaloGraphgy (EEG). Although there is great medical potential (communication and mobility assistance, as well as neuro-rehabilitation of those who lost motor functions), BCIs are rarely used outside of laboratories. This is mostly due to users’ variability from their brain morphologies to their changeable psychological states, making it impossible to create one system that works with high success for all. The success of a BCI depends tremendously on the user’s ability to focus to give mental commands, and the machine’s ability to decode such mental commands. Most approaches consist in either designing more intuitive and immersive interfaces to assist the users to focus, or enhancing the machine decoding properties. The latest advances in machine decoding are enabling adaptive machines that try to adjust to the changeable EEG during the B...
BCI2000: A general purpose brain-computer interface
2000
Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods, processing algorithms, output formats, and operating protocols. However, the typical BCI system is designed specifically for one particular BCI method and is, therefore, not suited to the systematic studies that are essential for continued progress. In response to this problem, we have developed a documented general-purpose BCI research and development platform called BCI2000. BCI2000 can incorporate alone or in combination any brain signals, signal processing methods, output devices, and operating protocols. This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BCI2000 system is based upon and gives examples of successful BCI implementations using this system. To date, we have used BCI2000 to create BCI systems for a variety of brain signals, processing methods, and applications. The data show that these systems function well in online operation and that BCI2000 satisfies the stringent real-time requirements of BCI systems. By substantially reducing labor and cost, BCI2000 facilitates the implementation of different BCI systems and other psychophysiological experiments. It is available with full documentation and free of charge for research or educational purposes and is currently being used in a variety of studies by many research groups. University of New York, Albany. His research interests include use of operant conditioning of spinal reflexes as a new model for defining the plasticity underlying a simple form of learning in vertebrates and development of EEG-based communication and control technology for people with severe motor disabilities.