A Unified XML based Description of the Contents of Brain Computer Interfaces (original) (raw)
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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.
Optimization of Brain Computer Interface systems by means of XML and BF++ Toys
The optimization of Brain Computer Interface systems is of great importance for the purpose of making them more usable and adjustable according to the needs of the end users. However, when evaluating their performances, it is evident the lack of a standard metric and of a common way to describe or represent the behavior, characteristics and data relative to the functional modules that compose them. The need of sharing data virtually everywhere and of making them usable by every researcher has inspired the work described in this paper: a set of tools, the BF++ Toys, which simulate and optimize the behavior of BCI systems, were implemented. They made wide use of the XML technology for describing and documenting all the main entities involved in BCI. Finally it will be shown how BF++ Toys and XML represent a versatile and reliable mean for the purpose of optimizing BCI systems.
Brain Computer Interfaces for inclusion
Proceedings of the 1st Augmented Human International Conference on - AH '10, 2010
In this paper, we describe an intelligent graphical user interface (IGUI) and a User Application Interface (UAI) tailored to Brain Computer Interface (BCI) interaction, designed for people with severe communication needs. The IGUI has three components; a two way interface for communication with BCI2000 concerning user events and event handling; an interface to user applications concerning the passing of user commands and associated device identifiers, and the receiving of notification of device status; and an interface to an extensible mark-up language (xml) file containing menu content definitions. The interface has achieved control of domotic applications. The architecture however permits control of more complex 'smart' environments and could be extended further for entertainment by interacting with media devices. Using components of the electroencephalogram (EEG) to mediate expression is also technically possible, but is much more speculative, and without proven efficacy. The IGUI-BCI approach described could potentially find wider use in the augmentation of the general population, to provide alternative computer interaction, an additional control channel and experimental leisure activities.
The BciAi4SLA Project: Towards a User-Centered BCI
Electronics, 2023
The brain–computer interfaces (BCI) are interfaces that put the user in communication with an electronic device based on signals originating from the brain. In this paper, we describe a proof of concept that took place within the context of BciAi4Sla, a multidisciplinary project involving computer scientists, physiologists, biomedical engineers, neurologists, and psychologists with the aim of designing and developing a BCI system following a user-centered approach, involving domain experts and users since initial prototyping steps in a design–test–redesign development cycle. The project intends to develop a software platform able to restore a communication channel in patients who have compromised their communication possibilities due to illness or accidents. The most common case is the patients with amyotrophic lateral sclerosis (ALS). In this paper, we describe the background and the main development steps of the project, also reporting some initial and promising user evaluation results, including real-time performance classification and a proof-of-concept prototype.
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.
BCIO: Brain Computer Interface Ontology
International Journal of …, 2012
Brain Computer Interface (BCI) enable paralyze peoples to interact and control their environment by defining the direct communication between human feelings (brain) and technological aspects (external device). The feature extraction and translation of commands in BCI are the critical tasks, which are the key of BCI system. Using the semantic method will enhance the both of these features. Nowadays ontology for representing knowledge is becoming more popular in researchers to describe, share and integrate their scientific data. If the information, algorithms and results are stored in the form of ontological content, it will provide the efficient way to use and reuse the data related to BCI and will help to BCI researchers for standardization. Adding semantic in BCI will also improve the efficiency of current BCI system.
A UML model for the description of different brain-computer interface systems
2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 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. I. INTRODUCTION RAIN Computer Interface (BCI) systems are a subset of the Assistive Technologies as they try to assist all those people that, after some severe pathology or trauma, have lost the control on their muscles and so the ability to communicate with the external environment [1]. Thanks to BCI systems, cerebral signals spontaneously or voluntary evoked after some external stimulus, can be translated into commands towards an external peripheral such as a robotic arm rather than a cursor on a screen or a speller. This allows the subject to be able to communicate by means of his "thought". Functionally a BCI system is based on two main blocks, the Transducer and the Control Interface [2] (Fig. 1).
User-centered design of brain-computer interfaces: OpenBCI.pl and BCI Appliance
Bulletin of the Polish Academy of Sciences: Technical Sciences, 2000
Brain-Computer Interface (BCI) allows for non-muscular communication with external world, which may be the only way of communication for patients in a locked-in state. This paper presents a complete software framework for BCI, a novel hardware solution for stimuli rendering in BCIs based on Steady State Visual Evoked Potentials (SSVEP), and a univariate algorithm for detection of SSVEP in the EEG time series.