InitialReal

HW_1_PNS_EE379K-385V_Neural_Eng/c1_dataVis.m

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+%% 
+clear all
+close all
+clc
+
+%% Import Data
+load('data.mat');
+
+%% Example: Plot the raw signal
+signal=Flex.signal;
+labels=Flex.trigger;
+TRIG = gettrigger(labels,0.5);
+TRIGend = gettrigger(-labels,-0.5);
+
+figure('units','normalized','Position',[0.1,0.1,0.7,0.4])
+plot((1:length(signal))./fs,zscore(signal));
+hold on;
+plot((1:length(signal))./fs,zscore(labels),'y');
+stem(TRIG./fs,ones(length(TRIG),1)*max(zscore(labels)),'Color','g');
+stem(TRIGend./fs,ones(length(TRIG),1)*max(zscore(labels)),'Color','r');
+grid on; grid minor;
+xlim([0,length(signal)./fs])
+xlabel('Time (s)')
+ylabel('Amplitude (uV)')
+title('Raw VF signal with labels for stimulation periods')
+
+%% Example: PSD estimates
+figure('units','normalized','Position',[0.1,0.1,0.5,0.5])
+[rows_act,cols_act,values_act] = find(labels>0);
+[rows_rest1,cols_rest,values_rest] = find(labels==0);
+notOfInterest = signal(rows_rest1);
+signalOfInterest=signal(rows_act);
+h = spectrum.welch; % creates the Welch spectrum estimator
+SOIf=psd(h,signalOfInterest,'Fs',fs); % calculates and plot the one sided PSD
+plot(SOIf); % Plot the one-sided PSD. 
+temp =get(gca);
+temp.Children(1).Color = 'b';
+
+% %% Bandpass Filtering
+% 
+% fc1 = 0; % first cutoff frequency in Hz 
+% fc2 = 100; % second cutoff frequency in Hz 
+% 
+% % normalize the frequencies
+% Wp = [fc1 fc2]*2/fs;
+
+% Build a Butterworth bandpass filter of 4th order
+% check the "butter" function in matlab
+
+% Filter data of both classes with a non-causal filter
+% Hint: use "filtfilt" function in MATLAB
+% filteredSignal = ;
+
+%% 
+
+
+