eeglab的小波变换时频分析程序用什么变换

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&&产​生​一​组​扫​频​信​号​,​采​用​S​T​F​T​进​行​时​频​分​析​,​识​别​结​果​的​不​同​信​号​成​分​,​讨​论​分​析​选​用​参​数​对​分​析​结​果​的​影​响​。
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你可能喜欢EEGLAB使用9问
EEGLAB是个免费的EEG分析工具包,由于它功能强大,更新迅速,是广大科研工作者的不错选择。这个是网址:。下面的很多回答来自网上,我用斜体标出。
1. 参考电极的问题
一个常听到的问题就是如何将自己的数据变成其他电极的参考,以双耳参考为例,如果左右耳的电极序号为31,32,我们可以通过一句简单的matlab代码实现这一功能:
EEG.data=EEG.data-mean(EEG.data([31 32],:));
当然,任何参考都有自己的弊端,最理想的参考应该类似物理学里面的“无穷远参考”。下面这段英文的问题和回复分析得很有道理,我这里就不赘述。他里面提到一个“无穷远参考”,其实,早在2001年,电子科技大学尧德中教授就提出了一个Reference
Electrode Standardization Technique,简称REST
参考文献在这里:
D.Yao. A method to standardize a reference of scalp EEG
recordings to a point at infinity. Physiol. Meas.,
22(4),693-711,2001.
软件下载地址:
推荐采用尧老师教研室的REST技术来统一参考电极的问题
I have some doubts regarding the referencing of the channels. I
have come across many papers which have appreciated average
reference while others have really criticized it. Some papers are
taking linked earlobes as reference while some are using only
ipsilateral ear lobe. Certain papers have referred to Laplacian or
Hjorth transformatio regarding the referencing of the
I'm working on saccade related potentials. I have tried linked
earlobes and average referencing for my studies but the data seems
to be very much contaminated with the saccade.
So I'll be really glad if some one can suggest me which would be
the best way of referencing in my dataset.
Basically, the best “practical” reference would cover the
whole body evenly, or at least the whole head evenly, in order to
approach the “reference-at-infinity”
used in physics. The more channels, the better. The only reason to
exclude any channel is if it is known to have noise on it.
这篇论文值得推荐
Jungh?fer M, Elbert T, Tucker DM & Braun C.
(1999) The polar average reference effect: a bias in estimating the
head surface integral in EEG recording.& Clinical
Neurophysiology 110(6):
由于EEGLAB核心技术是独立成分分析(ICA),我先把关于ICA的若干问题罗列如下:
2. 两任务的时候我是该分别ICA还是把两任务合到一起ICA?
ICA should be run using the concatenated data from both
conditions. The reason is that otherwise it is going to be harder
to compare the ICA components in the two conditions or remove the
ICA artifacts in the two conditions (if you run ICA on each dataset
separately, someone may always argue that the difference you
observe between the two conditions arises because you have selected
or removed different ICA components in each condition).
3.运行ICA总是out of memory怎么办?
no artifactual component activities will only be subtracted
channel you selected. There is a runicalowmem() function which
recently modified so it allows runing ICA with little memory. It
to be run from the command line though. I think it is in the
release of EEGLAB4.
可用来分析gamma频段(高频)的节律吗?
ICA is a linear decomposition that passes through all the
frequencies that are in the data. I believe there is much to be
learned still about how ICA parses gamma EEG (and higher)
5. 我现在采了一批数据,是148导的,我想计算ICA,请问需要多少个采样点?
ICA learns a (channels,channels) unmixing matrix, so the number
of data frames (time points) needed to separate as many components
increases as the square of the number of channels. The faq is a bit
out of date -- in our work with 72-256 channel data in the lab, we
have found that as the channel density becomes high, good ICA
solutions typically require a considerable multiple of the channel
number squared (up to 30 or more for 256-channel data).
For 148-channel data I would like to collect 30*128^2 ~ 650k (~40
min of data at 256 Hz) ... though it could well be that smaller
data sets could also give useful solutions.
两任务的时频分析是分析了再减还是减了再分析?Time-frequency analysis is
just another way of looking at signals,
especially non-stationary signals. Since, the study of non
stationary
signals in time domain is difficult one needs to apply
wavelet/STFT/Time-Frequency analysis to study the time and
frequency at
both time. So, any features can be studied only after converting
time-frequency domain alone and one can do this in many
7. 如何在EEGLAB中导入数据
数据的导入很简单,File==&import data==& from
ASCII/float ... 就可以了,但注意是[电极数*记录点数],而不是相反;同时要记得填采样率 Data sampling
8. 如何在EEGLAB中导入事件标志
时间标准复杂一些,但包括3列:type latency duration
比如我的一个txt文本就如同下面:
hand&38266&0
hand&51067&0
hand&63867&0
hand&74108&0
hand&81788&0
hand&92028&0
hand&97148&0
hand&108193&0
然后在column里填type latency duration,以及时间换算里填1/250
(我的采样为250)就可以了!
9.如何导入电极位置信息
I want to know how to construct my own chanlocs. I only know the
X,Y and lables of the channels. how to get the theta, radius,
sph_theta, sph_phi, sph_radius, sph_theta_besa, sph_phi_besa
To do so, from the command line:
pop_chanedit([])
then enter manually your channel labels and x and y positions,
press the button "xyz -& polar &
sph". You may then save the result in&
a text file. You may also use the menu "Edit &
Channel locations" from&
EEGLAB although you will need to have a dataset loaded.
已投稿到:
以上网友发言只代表其个人观点,不代表新浪网的观点或立场。[转载]EEGLAB使用9问
EEGLAB是个免费的EEG分析工具包,由于它功能强大,更新迅速,实乃广大穷科研工作者的不错选择。这个是网址:。下面的很多回答来自网上,我会用斜体标出
1. 参考电极的问题
任何参考都有自己的弊端,下面这段英文的问题和回复分析得很有道理,我这里就不赘述。他里面提到一个“无穷远参考”,其实,早在2001年,我的导师尧德中教授就提出了一个Reference
Electrode Standardization Technique,简称REST
参考文献在这里:
D.Yao. A method to standardize a reference of scalp EEG
recordings to a point at infinity. Physiol. Meas.,
22(4),693-711,2001.
软件下载地址:
推荐采用尧老师教研室的REST技术来统一参考电极的问题
I have some doubts regarding the referencing of the channels. I
have come across many papers which have appreciated average
reference while others have really criticized it. Some papers are
taking linked earlobes as reference while some are using only
ipsilateral ear lobe. Certain papers have referred to Laplacian or
Hjorth transformatio regarding the referencing of the
I'm working on saccade related potentials. I have tried linked
earlobes and average referencing for my studies but the data seems
to be very much contaminated with the saccade.
So I'll be really glad if some one can suggest me which would be
the best way of referencing in my dataset.
Basically, the best “practical” reference would cover the
whole body evenly, or at least the whole head evenly, in order to
approach the “reference-at-infinity”
used in physics. The more channels, the better. The only reason to
exclude any channel is if it is known to have noise on it.
这篇论文值得推荐
Jungh?fer M, Elbert T, Tucker DM & Braun C.
(1999) The polar average reference effect: a bias in estimating the
head surface integral in EEG recording.& Clinical
Neurophysiology 110(6):
由于EEGLAB核心技术是独立成分分析(ICA),我先把关于ICA的若干问题罗列如下:
2. 两任务的时候我是该分别ICA还是把两任务合到一起ICA?
ICA should be run using the concatenated data from both
conditions. The reason is that otherwise it is going to be harder
to compare the ICA components in the two conditions or remove the
ICA artifacts in the two conditions (if you run ICA on each dataset
separately, someone may always argue that the difference you
observe between the two conditions arises because you have selected
or removed different ICA components in each condition).
3.运行ICA总是out of memory咋个办?
no artifactual component activities will only be subtracted
channel you selected. There is a runicalowmem() function which
recently modified so it allows runing ICA with little memory. It
to be run from the command line though. I think it is in the
release of EEGLAB4.
可用来分析gamma频段(高频)的节律吗?
ICA is a linear decomposition that passes through all the
frequencies that are in the data. I believe there is much to be
learned still about how ICA parses gamma EEG (and higher)
5. 我现在采了一批数据,是148导的,我想计算ICA,请问需要多少个采样点?
ICA learns a (channels,channels) unmixing matrix, so the number
of data frames (time points) needed to separate as many components
increases as the square of the number of channels. The faq is a bit
out of date -- in our work with 72-256 channel data in the lab, we
have found that as the channel density becomes high, good ICA
solutions typically require a considerable multiple of the channel
number squared (up to 30 or more for 256-channel data).
For 148-channel data I would like to collect 30*128^2 ~ 650k (~40
min of data at 256 Hz) ... though it could well be that smaller
data sets could also give useful solutions.
两任务的时频分析是分析了再减还是减了再分析?Time-frequency analysis is
just another way of looking at signals,
especially non-stationary signals. Since, the study of non
stationary
signals in time domain is difficult one needs to apply
wavelet/STFT/Time-Frequency analysis to study the time and
frequency at
both time. So, any features can be studied only after converting
time-frequency domain alone and one can do this in many
7. 如何在EEGLAB中导入数据
数据的导入很简单,File==&import data==& from
ASCII/float ... 就可以了,但注意是[电极数*记录点数],而不是相反;同时要记得填采样率 Data sampling
8. 如何在EEGLAB中导入事件标志
时间标准复杂一些,但包括3列:type latency duration
比如我的一个txt文本就如同下面:
hand&38266&0
hand&51067&0
hand&63867&0
hand&74108&0
hand&81788&0
hand&92028&0
hand&97148&0
hand&108193&0
然后在column里填type latency duration,以及时间换算里填1/250
(我的采样为250)就可以了!
9.如何导入电极位置信息
I want to know how to construct my own chanlocs. I only know the
X,Y and lables of the channels. how to get the theta, radius,
sph_theta, sph_phi, sph_radius, sph_theta_besa, sph_phi_besa
To do so, from the command line:
pop_chanedit([])
then enter manually your channel labels and x and y positions,
press the button "xyz -& polar &
sph". You may then save the result in&
a text file. You may also use the menu "Edit &
Channel locations" from&
EEGLAB although you will need to have a dataset loaded.
以上网友发言只代表其个人观点,不代表新浪网的观点或立场。后使用快捷导航没有帐号?
查看: 4141|回复: 12
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& && &&&之前一直听说这两个是脑电数据处理软件,好像还有一个Liveview?(是不是这个,记不清了,知道的可以介绍下,我上网查的都很乱)。EEGlab好像是免费的,Analyzer好像说要用钱买(我们学校就买的是这个),这三个除了免费和收费到底还有什么区别啊??!网上也查不到~!求助!即将入手脑电数据处理,急求介绍!
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Analyzer很好用的 容易上手 傻瓜相机似的 按步骤操作就行&&易用性最好
eeglab的特长是做ica,缺点是运算超级慢,但出图好 可以做所谓的时频分析
Liveview没有这个
推荐你看一下brainstorm这个软件
努力写文章
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Analyzer很好用的 容易上手 傻瓜相机似的 按步骤操作就行&&易用性最好
eeglab的特长是做ica,缺点是运算超 ...[/quote]
恩,非常感谢,很详细的回答!
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Analyzer很好用的 容易上手 傻瓜相机似的 按步骤操作就行&&易用性最好
eeglab的特长是做ica,缺点是运算超 ...[/quote]
brainstorm是干什么用的&&网上查的很多啊&&还有什么游戏,商业赚钱什么的,没看到有脑电数据分析的啊
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WM training
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本帖最后由 lililili 于
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你搜brainstorm eeg啊
努力写文章
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brainstorm是干什么用的&&网上查的很多啊&&还有什么游戏,商业赚钱什么的,没看到有脑电数据分析的啊 ...[/quote]
附件: 你需要才可以下载或查看附件。没有帐号?
努力写文章
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见附件[/quote]
非常感谢&&我再查下!好东西!
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KING of Hearing
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本帖最后由 lililili 于
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还有一个办法,就是自己写code。。。。。。。。也是免费的
研究听觉认知、言语和脑电,同道中人请联系我
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还有一个办法,就是自己写code。。。。。。。。也是免费的[/quote]
目前还没这个能力
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还有一个办法,就是自己写code。。。。。。。。也是免费的[/quote]
版主又来刺激大家了
2011二季度优秀版主
2011一季度优秀版主
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我已经得到了不同频率的power,存为31x1(channel, power)的矩阵中,该如何把这个矩阵带入eeglab中得到脑电地形图呢?
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问一下你们实验室的师兄师姐,他们应该有画脑电地形图的一个代码~~~
明个要挨枪子儿了~~~
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本帖最后由 hcp4715 于
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在eeglab文件夹里找一下,那个函数直接输入也可以用
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EEGLAB中有个topoplot函数,可以画脑地形图,不过需要事先知道电极的位置,EEGLAB里面自带了一些,你可以进行修改后使用
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请问楼主某一时间段某一频段的脑电地形图怎么画的呢?
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请问楼主是怎么得到不同频率的power?
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EEGLAB中有个topoplot函数,可以画脑地形图,不过需要事先知道电极的位置,EEGLAB里面自带了一些,你可以进 ...[/quote]
chao.wang&&
你知道eeglab出的时频图y轴的频率分布不均匀,怎么改吗?谢谢呢。我想弄均匀,但是不会,求指点呢。想发张图给你看,又不会传图,我的q。方便的话帮帮我把。谢谢wang
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chao.wang&&
你知道eeglab出的时频图y轴的频率分布不均匀,怎么改吗?谢谢呢。我想弄均匀,但是不会,求 ...[/quote]
你好,时频分析我没做过,不好意思啊~
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本帖最后由 hcp4715 于
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你好,时频分析我没做过,不好意思啊~[/quote]
还是很谢谢你。
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