The Unlock Project: a Python-based framework for practical brain-computer interface communication "app" development.
The Unlock Project: a Python-based framework for practical brain-computer interface communication "app" development.
复制标题
DOI：
10.1109/embc.2012.6346473
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Guenther FH
中科院分区：
文献类型：
--
作者：
Brumberg JS;Lorenz SD;Galbraith BV;Guenther FH
在本文中，我们提出了一个框架，以减少开发时间所需的非侵入性脑机接口（BCI）中使用的应用程序。我们的框架主要侧重于促进快速软件“应用程序”的开发，类似于目前在消费者便携式计算（如智能手机和平板电脑）的努力。这是通过处理模块间通信而实现的，而不是直接的用户或开发人员实现，而是依赖于核心子系统进行标准内部数据格式的通信。我们还为常见的移动的EEG平台提供了一个硬件接口库，以便在BCI应用中立即使用。描述了一个用例示例，其中患有肌萎缩侧索硬化症的用户参与了使用所提出的框架开发的基于脑电图的BCI协议。我们表明，我们的软件环境能够实时运行，每秒更新50-60次，计算开销有限（5 ms系统滞后），同时提供准确的数据采集和信号分析。
In this paper we present a framework for reducing the development time needed for creating applications for use in non-invasive brain-computer interfaces (BCI). Our framework is primarily focused on facilitating rapid software “app” development akin to current efforts in consumer portable computing (e.g. smart phones and tablets). This is accomplished by handling intermodule communication without direct user or developer implementation, instead relying on a core subsystem for communication of standard, internal data formats. We also provide a library of hardware interfaces for common mobile EEG platforms for immediate use in BCI applications. A use-case example is described in which a user with amyotrophic lateral sclerosis participated in an electroencephalography-based BCI protocol developed using the proposed framework. We show that our software environment is capable of running in real-time with updates occurring 50–60 times per second with limited computational overhead (5 ms system lag) while providing accurate data acquisition and signal analysis.