Adding Event Markers to Imported EEG Data - Stacked Plot

Question

Christina Diersing 2021-10-27

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1573168-adding-event-markers-to-imported-eeg-data-stacked-plot

评论： Christina Diersing 2021-11-3

Hello!

I am currently working with Matlab to analyze EEG data from an Emotiv EPOC. I have it all imported and I have several plots made from the csv files. However, is there any way I can add (preferably manually) event markers to these plots? I have a stacked plot with all channels individually shown, a figure with all channels shown in tiled layout, and a plot with all channels shown. I've included the code below and attached the relating data files. I'm grateful for any help you can offer!

%% Importing_and_Plotting_EEG_Example

close all; clear all; clc;

% look to 300 ms for peak after stimulation

% ### EDIT: I commented out the next 4 lines so your code can be run in Answers

% % add folder with csv file to path

% addpath 'C:\Users\chris\Documents\College\Sixth Year\DAGSI\Data\EMOTIV Recordings\Event Marker Try 4'

% % change current directory to where this Matlab file is

% cd 'C:\Users\chris\Documents\College\Sixth Year\DAGSI\Data\EMOTIV Recordings'

% stops Matlab from rounding numbers

format long;

% Importing csv data

T=readtable('Try 4.csv'); %This reads the csv data into a table named T

Warning: Column headers from the file were modified to make them valid MATLAB identifiers before creating variable names for the table. The original column headers are saved in the VariableDescriptions property.
Set 'VariableNamingRule' to 'preserve' to use the original column headers as table variable names.

timestampOrig=T.Timestamp; %this makes timestampOrig equal to the original Timestamp

T.Timestamp=T.Timestamp-T.Timestamp(1); %This changes the official Timestamp column so it is 0 at the start of the recording

% Changes the sensor names from EEG_<sensor> to <sensor>

T.Properties.VariableNames(2:end)=extractAfter(T.Properties.VariableNames(2:end),'_');

T5=head(T, 5) %shows first 5 rows of table T

T5 = 5×15 table

Timestamp AF3 F7 F3 FC5 T7 P7 O1 O2 P8 T8 FC6 F4 F8 AF4 ___________________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ 0 4260.384766 4267.692383 4316.025879 4305.512695 4340 4278.461426 4278.974121 4279.615234 4235.256348 4184.871582 4456.666504 4401.794922 4343.589844 4387.05127 0.00770998001098633 4264.871582 4261.922852 4311.794922 4308.589844 4338.974121 4280.256348 4279.743652 4276.794922 4232.179688 4184.743652 4442.692383 4401.538574 4334.230957 4380.769043 0.0155198574066162 4266.282227 4272.05127 4316.410156 4312.563965 4340.512695 4280.769043 4286.410156 4275.769043 4229.615234 4178.333496 4438.205078 4405.384766 4325.256348 4381.025879 0.0232298374176025 4262.820313 4274.743652 4319.743652 4311.282227 4342.436035 4280.769043 4288.205078 4281.410156 4242.820313 4181.282227 4444.871582 4407.820313 4330.641113 4389.487305 0.0310399532318115 4266.153809 4267.563965 4318.846191 4308.077148 4332.563965 4279.230957 4282.307617 4285.641113 4248.589844 4186.025879 4448.717773 4404.230957 4333.717773 4392.307617

%% Stacked Plot

% Plot all electrode readings on the same plot (vs timestamp)

fig0=figure('Name', 'EEG Signals - Stacked Plot');

%creates a stacked plot with Timestamp as x-axis and the values of the variables in

%columns 2:end as the y-axis

stackedplot(T,T.Properties.VariableNames(2:end),'XVariable','Timestamp')

grid on; xlabel('Timestamp (s)'); %turns on grid and labels the x-axis

title('EEG Signals - Stacked Plot');

fig0.WindowState = 'maximize'; %maximizes the figure window -> easier to see

%% Tiled Layout - Same Prominence

fig1=figure('Name', 'EEG Signals and Peaks (Prominence=100)');

%Sets the plots to have a tiled layout (7 rows, 2 cols) with tight

%spacing

hTL=tiledlayout(7,2,'TileSpacing',"tight");

% for loop to establish the plots

for i=2:width(T) %1 plot for each sensor

nexttile %moves to next plot

%finds the peaks for each sensor. The peak is currently defined as as

%point that is at least 100 uV above the values directly to the left

%and right of the peak value; this also plots the peaks

findpeaks(T{:,i},T.Timestamp, 'MinPeakProminence', 100)

%creates ylabel as the sensor names, in bold font

ylabel(T.Properties.VariableNames(i), 'FontWeight', 'bold')

xticklabels('') %removes x-tick labels from the plots

if i==14 %for the bottom left plot

xticklabels(xticks) %x-tick labels are present

xlabel('Timestamp (s)'); %xlabel is present

end %ends if loop

end %ends for loop

xticklabels(xticks) %adds x-tick labels to bottom right graph

grid on;

xlabel('Timestamp (s)');

fig1.WindowState = 'maximize';

%% Reg Plot - all EEG Signals and peaks on same plot

%Plot EEG signals on same plot and find their peaks (when the peak is at

%least 100 above the nearest values

fig2=figure('Name', 'EEG Signals and Peaks - Same Plot');

%sets color order to 14 different colors

newcolors={'#0072BD', '#D95319', '#EDB120', '#7E2F8E','#77AC30','#4DBEEE', '#A2142F', '#FF0000', '#00FF00', '#0000FF', '#00FFFF', '#FF00FF', '#FFFF00', '#000000'};

colororder(newcolors); %sets the new color order to use

%Next 15 lines plot findpeaks for all sensors on the same plot - can

%adjust each prominence as desired

findpeaks(T.AF3, T.Timestamp,'MinPeakProminence',100);

grid on; hold on; %turns on grid and plots all peaks on same plot

findpeaks(T.F7, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.F3, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.FC5, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.T7, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.P7, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.O1, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.O2, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.P8, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.T8, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.FC6, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.F4, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.F8, T.Timestamp,'MinPeakProminence',100);

findpeaks(T.AF4, T.Timestamp,'MinPeakProminence',100);

%Creates legend for the plot

legend({'AF3', 'AF3 Peaks', 'F7', 'F7 Peaks', 'F3', 'F3 Peaks', 'FC5', 'FC5 Peaks', 'T7', 'T7 Peaks', 'P7', 'P7 Peaks', 'O1', 'O1 Peaks', 'O2', 'O2 Peaks', 'P8', 'P8 Peaks', 'T8', 'T8 Peaks', 'FC6', 'FC6 Peaks', 'F4', 'F4 Peaks', 'F8', 'F8 Peaks', 'AF4', 'AF4 Peaks'}, 'NumColumns', 2);

title('All Peaks on Same Graph');

xlabel('Timestamp (s)');

ylabel('EEG Value (uV)');

fig2.WindowState = 'maximize';

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Answer 1

Cris LaPierre 2021-10-27

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链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1573168-adding-event-markers-to-imported-eeg-data-stacked-plot#answer_818193

编辑：Cris LaPierre 2021-10-27

I guess it depends on what you want your markers to be, and how you want to select them. You can manually annotate your plot using the Figure Palette

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Christina Diersing 2021-10-28

在 MATLAB Online 中打开

The xline function is exactly what I'm looking for, at least for most of these. Do you know how I can use it on stacked plots? I'm trying to import the interval marker csv file, but it keeps coming up with an error stating "Error using xline (line 35). Error setting property 'Label' of class 'ConstantLine': Cell array can contain only non-empty character vectors, string vectors, or numbers."

I've inserted the relevant code below and attached the interval marker file I used.

%% Importing_and_Plotting_EEG_Example
close all; clear all; clc;
% look to 300 ms for peak after stimulation
% add folder with csv file to path
addpath 'C:\Users\chris\Documents\College\Sixth Year\DAGSI\Data\EMOTIV Recordings\Event Marker Try 4'
% change current directory to where this Matlab file is
cd 'C:\Users\chris\Documents\College\Sixth Year\DAGSI\Data\EMOTIV Recordings'
% stops Matlab from rounding numbers
format long;
% Importing csv data
    T=readtable('Try 4.csv'); %This reads the csv data into a table named T
    timestampOrig=T.Timestamp; %this makes timestampOrig equal to the original Timestamp
    T.Timestamp=T.Timestamp-T.Timestamp(1); %This changes the official Timestamp column so it is 0 at the start of the recording 
    % Changes the sensor names from EEG_<sensor> to <sensor>
    T.Properties.VariableNames(2:end)=extractAfter(T.Properties.VariableNames(2:end),'_');
    T5=head(T, 5) %shows first 5 rows of table T
        Int=readtable('Event Marker Try 4_EPOCX_126368_2021.06.04T15.42.31.04.00_intervalMarker.csv');
    EvtMar=Int.latency;
    EvtMarLab=Int.type;
%% Stacked Plot
    % Plot all electrode readings on the same plot (vs timestamp)
    fig0=figure('Name', 'EEG Signals - Stacked Plot');
    %creates a stacked plot with Timestamp as x-axis and the values of the variables in
    %columns 2:end as the y-axis
    stackedplot(T,T.Properties.VariableNames(2:end),'XVariable','Timestamp')
    xline(EvtMar, '-', {EvtMarLab})
    grid on; xlabel('Timestamp (s)'); %turns on grid and labels the x-axis
    title('EEG Signals - Stacked Plot');
    fig0.WindowState = 'maximize'; %maximizes the figure window -> easier to see

Christina Diersing 2021-10-29

在 MATLAB Online 中打开

Perfect! Thank you so much for your help! I'm looking to add labels to the lines so I asked on that thread. If you can help with that or direct me to an answers post that covers that, that would be great!

For anyone who is interested, this is what it currently looks like:

%% Importing_and_Plotting_EEG_007
close all; clear all; clc;
% look to 300 ms for peak after stimulation
% stops Matlab from rounding numbers
format long;
% Importing csv data
    T=readtable('Subject 007.csv'); %This reads the csv data into a table named T
    timestampOrig=T.Timestamp; %this makes timestampOrig equal to the original Timestamp
    T.Timestamp=T.Timestamp-T.Timestamp(1); %This changes the official Timestamp column so it is 0 at the start of the recording 
    % Changes the sensor names from EEG_<sensor> to <sensor>
    T.Properties.VariableNames(2:end)=extractAfter(T.Properties.VariableNames(2:end),'_');
    %T5=head(T, 5) %shows first 5 rows of table T
    Int=readtable('Subject 007_EPOCX_140710_2021.10.20T16.08.16.04.00_intervalMarker.csv');
    EvtMar=Int.latency;
    EvtMarLab=Int.type;
    
%% Stacked Plot
    % Plot all electrode readings on the same plot (vs timestamp)
    fig0=figure('Name', 'Subject 007 EEG Signals - Stacked Plot');
    %creates a stacked plot with Timestamp as x-axis and the values of the variables in
    %columns 2:end as the y-axis
    sp=stackedplot(T,T.Properties.VariableNames(2:end),'XVariable','Timestamp')
    ax = findobj(sp.NodeChildren, 'Type','Axes');
    arrayfun(@(sp)xline(sp,EvtMar,'LineWidth',1),ax);
    grid on; xlabel('Timestamp (s)'); %turns on grid and labels the x-axis
    title('Subject 007 EEG Signals - Stacked Plot');
    fig0.WindowState = 'maximize'; %maximizes the figure window -> easier to see
%% Tiled Layout - Same Prominence
    fig1=figure('Name', 'Subject 007 EEG Signals and Peaks (Prominence=400)');
    %title('Subject 007 EEG Signals and Peaks (Prominence=400)'); %have to
    %add title manually
    fig1.WindowState = 'maximize';
    %Sets the plots to have a tiled layout (7 rows, 2 cols) with tight
    %spacing
    hTL=tiledlayout(7,2,'TileSpacing',"tight");
    % for loop to establish the plots
    for i=2:width(T) %1 plot for each sensor
      nexttile %moves to next plot
      %finds the peaks for each sensor. The peak is currently defined as as
      %point that is at least 400 uV above the values directly to the left
      %and right of the peak value; this also plots the peaks
      findpeaks(T{:,i},T.Timestamp, 'MinPeakProminence', 400) 
      xline(EvtMar, '-', {EvtMarLab})
      %xline(EvtMar, '-');
      %creates ylabel as the sensor names, in bold font
      ylabel(T.Properties.VariableNames(i), 'FontWeight', 'bold')
      xticklabels('') %removes x-tick labels from the plots
      if i==14 %for the bottom left plot
          xticklabels(xticks) %x-tick labels are present
          xlabel('Timestamp (s)'); %xlabel is present
      end %ends if loop
    end %ends for loop
    xticklabels(xticks) %adds x-tick labels to bottom right graph
    grid on;
    xlabel('Timestamp (s)');
    
    
%% Reg Plot - all EEG Signals and peaks on same plot
    %Plot EEG signals on same plot and find their peaks (when the peak is at
    %least 400 above the nearest values
    fig2=figure('Name', 'Subject 007 EEG Signals and Peaks - Same Plot Prominence: 400');
    title('Subject 007 EEG Signals and Peaks - Same Plot Prominence: 400');
    fig2.WindowState = 'maximize';
    %sets color order to 14 different colors
    newcolors={'#0072BD', '#D95319', '#EDB120', '#7E2F8E','#77AC30','#4DBEEE', '#A2142F', '#FF0000', '#9000de', '#0000FF', '#00FFFF', '#FF00FF', '#2fde00', '#8a8a8a'};
    colororder(newcolors); %sets the new color order to use
    mnpkprom=400; %min peak prominence (if you want most/all to be the same)
    %Next 15 lines plot findpeaks for all sensors on the same plot - can
    %adjust each prominence as desired
    findpeaks(T.AF3, T.Timestamp,'MinPeakProminence',mnpkprom);
    grid on; hold on; %turns on grid and plots all peaks on same plot
    findpeaks(T.F7, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.F3, T.Timestamp,'MinPeakProminence',mnpkprom); 
    findpeaks(T.FC5, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.T7, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.P7, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.O1, T.Timestamp,'MinPeakProminence',mnpkprom); 
    findpeaks(T.O2, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.P8, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.T8, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.FC6, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.F4, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.F8, T.Timestamp,'MinPeakProminence',mnpkprom);
    findpeaks(T.AF4, T.Timestamp,'MinPeakProminence',mnpkprom);
    xline(EvtMar, '--', {'Ns','08','15','22','Ns','Ec','Mo','Ns','08','15','22','Ns','Mo','Mt','Ea','Md','Hr','Mt','Mt','Ea','Md','Hr'})
    %Creates legend for the plot
    legend({'AF3', 'AF3 Peaks', 'F7', 'F7 Peaks', 'F3', 'F3 Peaks', 'FC5', 'FC5 Peaks', 'T7', 'T7 Peaks', 'P7', 'P7 Peaks', 'O1', 'O1 Peaks', 'O2', 'O2 Peaks', 'P8', 'P8 Peaks', 'T8', 'T8 Peaks', 'FC6', 'FC6 Peaks', 'F4', 'F4 Peaks', 'F8', 'F8 Peaks', 'AF4', 'AF4 Peaks'}, 'NumColumns', 2);
    xlabel('Timestamp (s)');
    ylabel('EEG Value (uV)');

Cris LaPierre 2021-10-29

You can add a label to an xline.

xline(x,LineSpec,labels)

See on the xline documentation page

Christina Diersing 2021-11-3

在 MATLAB Online 中打开

Thank you!

For most of my plots, I used this line of code:

    xline(EvtMar,'--',{'EO','BE','BE','BE','EC','BE','CE','CE','BE','OM','OM'}); %Vertical Lines as event markers

For the stacked plots, I used these

    sp=stackedplot(T,T.Properties.VariableNames(2:end),'XVariable','Timestamp')
    ax = findobj(sp.NodeChildren, 'Type','Axes');
    arrayfun(@(sp)xline(sp,EvtMar,'--',{'EO','BE','BE','BE','EC','BE','CE','CE','BE','OM','OM'}),ax);
    grid on; xlabel('Timestamp (s)'); %turns on grid and labels the x-axis
    title('EEG Signals - Stacked Plot');
    fig0.WindowState = 'maximize'; %maximizes the figure window -> easier to see

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Adding Event Markers to Imported EEG Data - Stacked Plot

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