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Design and development of BCI for online acquisition, monitoring and digital processing of EEG waveforms

机译:在线脑电波形采集,监测和数字处理的BCI设计与开发

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Abstract: Commercially available EEG acquisition units provide ability to acquire and view EEG signals in real time using their proprietary user interface software. Analysis of such EEG data is limited to the capabilities provided within these acquisition units, thereby making it necessary to process data in multi-paradigm computing environment. Offline uploading of the data into standard tools for further analysis may cause loss of information. This paper gives details of a simple and robust mechanism for online acquisition and real time processing of EEG signals in MATLAB without any loss of information, using custom developed API. Resulting wave decomposition into discrete samples and channels also reduce complexity in processing data. The designed system, using portable wireless Emotiv EEG neuroheadset, can easily be adopted for web-based remote monitoring of live EEG for applications in the field of mobile health. Moreover, developed BCI can be miniaturised and designed as SoC (System on Chip).
机译:摘要:市售的EEG采集单元可使用其专有的用户界面软件实时采集和查看EEG信号。对此类EEG数据的分析仅限于这些采集单元内提供的功能,因此有必要在多范式计算环境中处理数据。将数据离线上传到标准工具中进行进一步分析可能会导致信息丢失。本文详细介绍了使用自定义开发的API在MATLAB中在线采集和实时处理EEG信号而又不造成任何信息丢失的简单而强大的机制。将波分解为离散的样本和通道也会降低处理数据的复杂性。使用便携式无线Emotiv EEG神经耳机设计的系统可以轻松地用于基于Web的实时EEG远程监控,以用于移动医疗领域。而且,可以将开发的BCI小型化并设计为SoC(片上系统)。

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