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.     

Brain-computer interface research at the Wadsworth Center.

Studies at the Wadsworth Center over the past 14 years have shown that people with or without motor disabilities can learn to control the amplitude of mu or beta rhythms in electroencephalographic (EEG) activity recorded from the scalp over sensorimotor cortex and can use that control to move a cursor on a computer screen in one or two dimensions. This EEG-based brain-computer interface (BCI) could provide a new augmentative communication technology for those who are totally paralyzed or have other severe motor impairments. Present research focuses on improving the speed and accuracy of BCI communication.     

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.     

15 years of BCI research at Graz University of Technology: current projects.

Over the last 15 years, the Graz Brain-Computer Interface (BCI) has been developed and all components such as feature extraction and classification, mode of operation, mental strategy, and type of feedback have been investigated. Recent projects deal with the development of asynchronous BCIs, the presentation of feedback and applications for communication and control.     

The Neurochip BCI: towards a neural prosthesis for upper limb function.

The Neurochip BCI is an autonomously operating interface between an implanted computer chip and recording and stimulating electrodes in the nervous system. By converting neural activity recorded in one brain area into electrical stimuli delivered to another site, the Neurochip BCI could form the basis for a simple, direct neural prosthetic. In tests with normal, unrestrained monkeys, the Neurochip continuously recorded activity of single neurons in primary motor cortex for several weeks at a time. Cortical activity was correlated with simultaneously-recorded electromyogram (EMG) activity from arm muscles during free behavior. In separate experiments with anesthetized monkeys, we found that microstimulation of the cervical spinal cord evoked movements of the arm and hand, often involving multiple muscles synergies. These observations suggest that spinal microstimulation controlled by cortical neurons could help compensate for damaged corticospinal projections.     

P300-based BCI mouse with genetically-optimized analogue control.

In this paper we propose a brain-computer interface (BCI) mouse based on P300 waves in electroencephalogram (EEG) signals. The system is analogue in that at no point a binary decision is made as to whether or not a P300 was actually produced in response to the stimuli. Instead, the 2-D motion of the pointer on the screen, using a novel BCI paradigm, is controlled by directly combining the amplitudes of the output produced by a filter in the presence of different stimuli. This filter and the features to be combined within it are optimised by an evolutionary algorithm.     

BCI meeting 2005--workshop on technology: hardware and software.

This paper describes the outcome of discussions held during the Third International BCI Meeting at a workshop to review and evaluate the current state of BCI-related hardware and software. Technical requirements and current technologies, standardization procedures and future trends are covered. The main conclusion was recognition of the need to focus technical requirements on the users' needs and the need for consistent standards in BCI research.     

国内外直接甲醇燃料电池研究进展

甲醇以其能量密度高,来源丰富,价格低廉和储存方便等优点倍受关注,因此直接甲醇燃料电池已成为世界燃料电池研究的一个热点。介绍了二元合金、多元合金阳极催化剂、阴极催化剂和质子膜的研究现状;报导了国内外直接甲醇燃料电池样机达到的技术水平。     

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.     

国内外电动汽车发展及前景预测

1 发展电动汽车可有效解决能源消耗和环境污染问题 电动汽车是指全部或部分用电能驱动电动机作为动力系统的汽车。电动汽车包含纯电动汽车、混合动力电动汽车和燃料电池电动汽车。     

国内外核电发展状况及相关问题

介绍国内外核电发展的最新情况，并就与核电有关的若干问题进行讨论。中国是世界主要的核大国，但核电对我国的电力贡献还很少，仅占全国发电量的1．43％。国家主管部门将于近期批准新的棱电项目，并有可能就2020年前的核电发展做出规划，中国的核电发展即将步入快速、稳定的发展之路。     

国内外动态

五相步进电动机和驱动美国Oriental公司研制的RK五相步进电动机的基本步距角0.72°,可用电子划分成250微步。RK驱动器在微步低速运行和满步高速运行时能提供16档分辨率。电动机有三种基本型式:标准电动机、IP65电动机和齿轮电动机(机座大小为42mm、60mm和85mm)。85mm的步进电动     

国内外动态

右角度齿轮电动机；整体式运动控制器；无霍尔传感器无刷直流驱动器；低电压电动机驱动器；步进电动机驱动器；较小规格无机座电动机；28mm混合步进电动机；普通用途交流电动机；有内置式控制器的伺服电动机；低齿槽效应直流微型电动机。     

国内外动态

拥有直流永久磁铁的无刷电机；行程电感传感器；垂直轴型风车并适于市街区使用；三种长度的步进转矩电机；块状超导磁铁组成的电机迈向实用化；有令人舒适的速度的电动机;具有高比功率及分割磁铁的电机样品试验。     

国内外动态

磁性编码器;微型有刷和无刷齿轮电动机;直线步进伺服电动机;空心轴电动机反馈系统;电子旋转分度头.     

国内外动态

先进的低成本无槽无刷直流电动机驱动韩国Sung KyunKwan大学信息工程学院与电子技术所智能机械研究中心等,利用PLL(锁相环路)算法,共同研制成先进的无槽无刷直流(BLDC)电动机驱动装置。为了提高霍尔一集成电路(Hall-ICs)的性能,开发了位置信号合成的控制算法,还考虑到对永磁(PM     

国内外动态

异步电机驱动的多脉冲AC/DC变换器印度新德里Hauz Khas电力工程局研制的24-脉冲AC/DC变换器,是基于自耦变压器馈电给矢量控制异步电动机驱动(VCIMDs)的多脉冲AC/DC变换器,主要用于在公共耦合点(PCC)改善电能的质量。24-脉冲AC/DC变换器,原理上是按照直流纹波的再注入技术,倍增脉冲和减轻谐波。为此自耦变压器的设计能适合于各种改型应用场合,例如现在使用的6-脉冲二极管桥式整流器。还研究了由负荷变化对VCIMD的影响,以证明AC/DC变换器的效果。仿真结果和实验结果完全证实了24脉冲AC/DC变换器设计与模型的正确性。带VCIMC…