BCI Meeting 2005--workshop on BCI signal processing: feature extraction and translation.

This paper describes the outcome of discussions held during the Third International BCI Meeting at a workshop charged with reviewing and evaluating the current state of and issues relevant to brain-computer interface (BCI) feature extraction and translation. The issues discussed include a taxonomy of methods and applications, time-frequency spatial analysis, optimization schemes, the role of insight in analysis, adaptation, and methods for quantifying BCI feedback.     

BCI Meeting 2005--workshop on signals and recording methods.

This paper describes the highlights of presentations and discussions during the Third International BCI Meeting in a workshop that evaluated potential brain-computer interface (BCI) signals and currently available recording methods. It defined the main potential user populations and their needs, addressed the relative advantages and disadvantages of noninvasive and implanted (i.e., invasive) methodologies, considered ethical issues, and focused on the challenges involved in translating BCI systems from the laboratory to widespread clinical use. The workshop stressed the critical importance of developing useful applications that establish the practical value of BCI technology.     

BCI Meeting 2005--workshop on clinical issues and applications.

This paper describes the outcome of discussions held during the Third International BCI Meeting at a workshop charged with reviewing and evaluating the current state of and issues relevant to brain-computer interface (BCI) clinical applications. These include potential BCI users, applications, validation, getting BCIs to users, role of government and industry, plasticity, and ethics.     

脑电BCI系统的软硬件开发平台发展现状

脑-机接口系统(brain-computer interface,BCI)是一种将大脑活动信息直接转换为人工输出的系统,允许用户通过思维 活动直接控制外部设备。 脑电图技术(electroencephalogram,EEG)可以实时获取大脑活动产生的神经生理电信息,具有无创、低 廉、高时间分辨率等优点,是 BCI 获取大脑活动信息的主流方式之一。 脑电 BCI 系统具有脑电信号采集、处理和输出结果的功 能,能够诱发特征脑电,并控制外部设备,在康复、医疗诊断和神经科学研究等领域具有巨大的应用价值。 随着脑电 BCI 系统应 用需求不断增加,确保其快速高效地部署和应用的技术越来越重要。 结合近些年脑电 BCI 系统研究和应用,综合论述目前用于 开发脑电采集和编解码的硬件和软件平台的技术,分析归纳其当前现状与未来趋势,以促进开发脑电 BCI 系统软硬件平台的有 效发展。     

DNA: hardware and software of life

In this introductory paper I will first go back in history and endeavor to explain in simple terms, with the support of optical diffraction experiments, just how X-ray fiber diffraction pictures lead Watson and Crick to discover the DNA double helix. Second I will present the geometrical and chemical structures of the molecule, the “hardware of life”, emphasizing in some detail the nature of the hydrogen bonding in the Watson–Crick (WC) base pairs A–T, G–C formed by the natural bases of the genetic alphabet. I will then discuss a class of twelve artificial analogues to these bases, some of which have been successfully synthesized by organic chemists by rearranging the pattern of hydrogen bonds of the base pairs. Adopting the perspective of theoretical computer science and error-coding theory, I will finally present DNA as the “software of life”, by discussing Mac Dónaill’s recent interpretation of the optimality of the natural genetic cipher as compared to other possible alphabets selected from the artificial analogues.     

Change in computer hardware and software paradigms

The change in the paradigm of the development of processors and software for the processors is considered. This change is caused by the continuous progress in the technology of semiconductor microchips that is described by Moore’s law.     

The Wadsworth BCI Research and Development Program: at home with BCI.

The ultimate goal of brain-computer interface (BCI) technology is to provide communication and control capacities to people with severe motor disabilities. BCI research at the Wadsworth Center focuses primarily on noninvasive, electroencephalography (EEG)-based BCI methods. We have shown that people, including those with severe motor disabilities, can learn to use sensorimotor rhythms (SMRs) to move a cursor rapidly and accurately in one or two dimensions. We have also improved P300-based BCI operation. We are now translating this laboratory-proven BCI technology into a system that can be used by severely disabled people in their homes with minimal ongoing technical oversight. To accomplish this, we have: improved our general-purpose BCI software (BCI2000); improved online adaptation and feature translation for SMR-based BCI operation; improved the accuracy and bandwidth of P300-based BCI operation; reduced the complexity of system hardware and software and begun to evaluate home system use in appropriate users. These developments have resulted in prototype systems for every day use in people's homes.     

基于软硬件保护的锂离子蓄电池安全控制电路

针对锂离子蓄电池在充放电过程中容易出现的过充、过放、过流、过温问题,设计了基于软硬件保护的锂离子蓄电池保护电路。电路使用软件和硬件双重保护,并通过红外探测技术实现电池表面过高温度保护。电路特点是结构简单。通过实验证明了该电路安全、高效,有着良好的应用前景。     

The BCI competition. III: Validating alternative approaches to actual BCI problems.

A brain-computer interface (BCI) is a system that allows its users to control external devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major challenge. Success requires the effective interaction of two adaptive controllers: the user's brain, which produces brain activity that encodes intent, and the BCI system, which translates that activity into device control commands. In order to facilitate this interaction, many laboratories are exploring a variety of signal analysis techniques to improve the adaptation of the BCI system to the user. In the literature, many machine learning and pattern classification algorithms have been reported to give impressive results when applied to BCI data in offline analyses. However, it is more difficult to evaluate their relative value for actual online use. BCI data competitions have been organized to provide objective formal evaluations of alternative methods. Prompted by the great interest in the first two BCI Competitions, we organized the third BCI Competition to address several of the most difficult and important analysis problems in BCI research. The paper describes the data sets that were provided to the competitors and gives an overview of the results.     

通用RTU的软硬件设计

分析和讨论了以通用型16位单片机为核心处理单元设计高性能价格比的软硬件方法     

关于两种微机保护软硬件配置问题的探讨

为满足微机继电保护装置的四统一标准,我国研制的第三代微机保护装置多采用MPU+DSP的结构。该文描述了目前常用的MPU+两DSP结构和MPU+单DSP结构两种微机保护结构,分别给出了其保护软件的实现方法。同时在分析其在软硬件配置上的优缺点的基础上,针对两种微机保护结构进行了对比,指出MPU+高性能单DSP的微机保护装置的优越性。     

关于两种微机保护软硬件配置问题的探讨

为满足微机继电保护装置的四统一标准,我国研制的第三代微机保护装置多采用MPU+DSP的结构.该文描述了目前常用的MPU+两DSP结构和MPU+单DSP结构两种微机保护结构,分别给出了其保护软件的实现方法.同时在分析其在软硬件配置上的优缺点的基础上,针对两种微机保护结构进行了对比,指出MPU+高性能单DSP的微机保护装置的优越性.     

一种新型的继电保护软硬件平台

结合微机继电保护现状 ,提出了一种新型的继电保护软硬件平台 ,介绍了主要的实现方法 ,它具有技术起点高、通用性强、可靠性好等优点     

一种新型的继电保护软硬件平台

结合微机继电保护现状,提出了一种新型的继电保护软硬件平台,介绍了主要的实现方法,它具有技术起点高、通用性强、可靠性好等优点.     

探讨微机保护软硬件冗余设计的必要性

通过几起运行中微机保护误动事故的分析,指出须重新认识微机保护软硬件的冗余设计,尤其须加强微机保护“三取二”闭锁功能及设置多ＣＰＵ结构,进一步说明微机保护软硬件冗余设计的必要性,为此就软硬件冗余设计的具体方式及目前存在的问题进行了探讨。     

Brain-computer interface technology: a review of the first international meeting.

Over the past decade, many laboratories have begun to explore brain-computer interface (BCI) technology as a radically new communication option for those with neuromuscular impairments that prevent them from using conventional augmentative communication methods. BCI's provide these users with communication channels that do not depend on peripheral nerves and muscles. This article summarizes the first international meeting devoted to BCI research and development. Current BCI's use electroencephalographic (EEG) activity recorded at the scalp or single-unit activity recorded from within cortex to control cursor movement, select letters or icons, or operate a neuroprosthesis. The central element in each BCI is a translation algorithm that converts electrophysiological input from the user into output that controls external devices. BCI operation depends on effective interaction between two adaptive controllers, the user who encodes his or her commands in the electrophysiological input provided to the BCI, and the BCI which recognizes the commands contained in the input and expresses them in device control. Current BCI's have maximum information transfer rates of 5-25 b/min. Achievement of greater speed and accuracy depends on improvements in signal processing, translation algorithms, and user training. These improvements depend on increased interdisciplinary cooperation between neuroscientists, engineers, computer programmers, psychologists, and rehabilitation specialists, and on adoption and widespread application of objective methods for evaluating alternative methods. The practical use of BCI technology depends on the development of appropriate applications, identification of appropriate user groups, and careful attention to the needs and desires of individual users. BCI research and development will also benefit from greater emphasis on peer-reviewed publications, and from adoption of standard venues for presentations and discussion.     

Towards a robust BCI: error potentials and online learning.

Recent advances in the field of brain-computer interfaces (BCIs) have shown that BCIs have the potential to provide a powerful new channel of communication, completely independent of muscular and nervous systems. However, while there have been successful laboratory demonstrations, there are still issues that need to be addressed before BCIs can be used by nonexperts outside the laboratory. At IDIAP Research Institute, we have been investigating several areas that we believe will allow us to improve the robustness, flexibility, and reliability of BCIs. One area is recognition of cognitive error states, that is, identifying errors through the brain's reaction to mistakes. The production of these error potentials (ErrP) in reaction to an error made by the user is well established. We have extended this work by identifying a similar but distinct ErrP that is generated in response to an error made by the interface, (a misinterpretation of a command that the user has given). This ErrP can be satisfactorily identified in single trials and can be demonstrated to improve the theoretical performance of a BCI. A second area of research is online adaptation of the classifier. BCI signals change over time, both between sessions and within a single session, due to a number of factors. This means that a classifier trained on data from a previous session will probably not be optimal for a new session. In this paper, we present preliminary results from our investigations into supervised online learning that can be applied in the initial training phase. We also discuss the future direction of this research, including the combination of these two currently separate issues to create a potentially very powerful BCI.     

基于VC++的软硬件交互控制的船舶电站仿真系统

为了增强船舶轮机学员实际操作的能力,本文结合海运学校的实际要求开发了这套船舶电站仿真系统,主要包括2个主配电板、1个应急配电板和1个负载配电板等.运用VC 集成开发环境模拟了船舶电站配电、同步并车、保护、岸电等涉及到的全部功能并利用RS485总线实现与下位机通信.上位机软件部分除和实际配电板具有相同的板面配置外,另外还有相应的动作流程图和原理图与之对应,并具有与硬件的操作相同步的动画显示功能.整个系统既能对现场硬件实物直接操作,也可通过触摸屏操作软件来控制硬件部分运行工作.