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Updated: Jul 6, 2025

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

多频平稳状态视觉唤起的潜在数据集

Jing Mu^1,2, Shuo Liu³, Anthony N Burkitt³

¹Department of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia. jing.mu@unimelb.edu.au.

Scientific data

|January 4, 2024

概括

此摘要是机器生成的。

这项研究引入了一个新的数据集,用于多频稳态视觉唤起潜力 (SSVEP),以推进脑计算机接口 (BCI) 研究. 该数据集支持开发具有众多命令的更复杂的BCI系统.

更多相关视频

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

Published on: May 12, 2019

Visual Evoked Potential Recordings in Mice Using a Dry Non-invasive Multi-channel Scalp EEG Sensor

Visual Evoked Potential Recordings in Mice Using a Dry Non-invasive Multi-channel Scalp EEG Sensor

Published on: January 12, 2018

相关实验视频

Last Updated: Jul 6, 2025

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

Published on: May 12, 2019

Visual Evoked Potential Recordings in Mice Using a Dry Non-invasive Multi-channel Scalp EEG Sensor

Visual Evoked Potential Recordings in Mice Using a Dry Non-invasive Multi-channel Scalp EEG Sensor

Published on: January 12, 2018

科学领域:

神经科学是一个神经科学.
生物医学工程生物医学工程
人与计算机的交互

背景情况:

稳态视觉唤起潜力 (SSVEP) 是一个关键的脑计算机接口 (BCI) 模式.
单频SSVEP对于有限的命令集是有效的.
多频SSVEP为复杂的BCI提供了潜力,但缺乏研究开发.

研究的目的:

促进多频SSVEP方法的研究.
提供SSVEP信号的公开可用的数据集.
促进先进BCI系统的开发.

主要方法:

收集了35名参与者的SSVEP数据.
使用单频,双频和三频刺激模式.
包括三种不同的多频刺激变体.

主要成果:

在各种频率条件下生成了SSVEP信号的综合数据集.
该数据集使不同多频SSVEP方法的比较分析成为可能.
提供未来研究高层BCI开发的基础.

结论:

该数据集对于推进多频SSVEP研究至关重要.
它将加速复杂的大脑与计算机接口的开发.
鼓励进一步研究优化多频SSVEP技术.