Я пытаюсь запустить код на волнах ЭЭГ, импортируя набор данных в файл edf.
Для запуска этого кода в Matlab вам потребуется загрузить функцию edffile в Matlab. Затем запустите код. Этот код требуется для извлечения полосы частот ЭЭГ, и мы получили ошибку, как указано ниже:
Длина сегментов не может быть больше длины входного сигнала.
Error in welchparse (line 32)
[L,noverlap,win] = segment_info(M,win,noverlap);
Error in spectrogram (line 172)
[x,nx,~,~,~,win,~,~,noverlap,~,~,options] = welchparse(x,esttype,varargin{:});"
to download the function to read edf file and to run the program i have also provided the link below
"https://blogs.mathworks.com/pick/2018/10/12/edf-read/?s_tid=srchtitle" you can download this
And to download the dataset the link given below:
"https://blogs.mathworks.com/pick/2018/10/12/edf-read/?s_tid=srchtitle"
to run the code you need to download one subject and get the output.
Я также предоставлю код для этих наборов данных.
Пожалуйста, помогите мне запустить этот код и предоставьте мне любую возможную помощь. Спасибо,
%[Noyono,fs]=audioread('vlc-record-2016-09-17-23h00m28s-Noyono_demo.mp3-.mp3');
[Header,S1] = edfread('Subject12_1.edf');
%Extract Channel O2 and perform epoching to get 1280 samples
data=S1;
% loading 1-channel data
Sampling_time_period=2; % sampling time period
sampling_frequency=500; % sampling frequency
[n,m]=size(data); % obtain size of data
t=(1:n)*Sampling_time_period; % generates time vector
h=figure
plot(t,data,'p');
title('EEG Data')
grid on % plot with grid
h1=figure
plot(t,data(:,1), 'b-') % plot without grid
%-----------------------------------------------------------------------%
%POWER SPECTRUM USING FFT
%-----------------------------------------------------------------------%
y=fft(data); % fast fourier transform
power_spectrum=abs(y).^2; % power spectrum using fft
frequency=(1:n)*sampling_frequency/n; % frequency vector
h2=figure
plot(frequency,20*log(power_spectrum),'b') % plotting frequency
title('Power spectrum using fft')
%------------------------------------------------------%
%SPECTROGRAM of channel 1
%------------------------------------------------------%
[S1,F,T] = spectrogram(data(:,1),chebwin(128,100),0,sampling_frequency);
%--------------------------------------------------------------------------------%
%w=chebwin(L,r)returns the column vector w containing length L chebyshev window ;
%r is sidelobe attenuation ;
%gives 128 point chebyshev window. r = 100 dB here
%--------------------------------------------------------------------------------%
S1=abs(S1);
h4=figure
mesh(T,F,S1);
xlabel('Time (sec)','FontSize',14);
ylabel('Frequency (Hz)','FontSize',14);
zlabel('S1','FontSize',14);
%-------------------------------------------------------------------------%
%FREQUENCY AND SINGLE SIDED AMPLITUDE SPECTRUMS OF APLHA BETA GAMA DELTA
%-------------------------------------------------------------------------%
%-------------------------------------------------------------------------%
%DELTA BAND-PASS FILTER (0-4)
%-------------------------------------------------------------------------%
sampling_frequency = 500; % Sampling Frequency
Fpass = 0; % Passband Frequency
Fstop = 4; % Stopband Frequency
Dpass = 0.057501127785; % Passband Ripple
Dstop = 0.0001; % Stopband Attenuation
density = 20; % Density Factor
% Calculating the order from the parameters using FIRPMORD.
[n, fo, ao, w] = firpmord([Fpass, Fstop]/(sampling_frequency/2), [1 0], [Dpass, Dstop]);
% fo is the frequency ao is the amplitude response vector
% Calculating the coefficients using the FIRPM function.
b1 = firpm(n, fo, ao, w, {density});
Hd1 = dfilt.dffir(b1); %discrete time direct form fir filter
x1=filter(Hd1,data);
h9=figure
plot(t,x1,'k')
title('waveform for DELTA band')
%================================================================%
%FREQUENCY SPECTRUM OF DELTA
%================================================================%
L=10;
sampling_frequency=500;
N_point_fft = 2^nextpow2(L); % Next power of 2 from length of x1
y1 = fft(x1,N_point_fft)/L; % for N point fft
f = sampling_frequency/2*linspace(0,1,N_point_fft/2); % N_point_fft/2 points b/w 0 and 1
%================================================================%
%SINGLE SIDED AMPLITUDE SPECTRUM
%================================================================%
h10=figure
plot(f,2*abs(y1(1:N_point_fft/2)))
title('Single-Sided Amplitude Spectrum of DELTA x1(t)')
xlabel('Frequency (Hz)')
ylabel('|Y1(f)|')
%-----------------------------------------------------------------%
%THETA- BAND PASS FILTER (4-7)
%-----------------------------------------------------------------%
sampling_frequency = 500; % Sampling Frequency
Fstop1 = 3.5; % First Stopband Frequency
Fpass1 = 4; % First Passband Frequency
Fpass2 = 7; % Second Passband Frequency
Fstop2 = 7.5; % Second Stopband Frequency
Dstop1 = 0.0001; % First Stopband Attenuation
Dpass = 0.057501127785; % Passband Ripple
Dstop2 = 0.0001; % Second Stopband Attenuation
density = 20; % Density Factor
% Calculating the order from the parameters using FIRPMORD.
[n, fo, ao, w] = firpmord([Fstop1 Fpass1 Fpass2 Fstop2]/(sampling_frequency/2), [0 1 0], [Dstop1 Dpass Dstop2]);
% fo is the frequency ao is the amplitude response vector
% Calculating the coefficients using the FIRPM function.
b2 = firpm(n, fo, ao, w, {density});
Hd2 = dfilt.dffir(b2); %discrete time direct form fir filter
x2=filter(Hd2,data);
h11=figure
plot(t,x2,'r')
title('waveform for THETA band')
%===================================================%
%FREQUENCY SPECTRUM OF THETA
%===================================================%
L=10;
sampling_frequency=500;
N_point_fft = 2^nextpow2(L); % Next power of 2 from length of x2
y2 = fft(x2,N_point_fft)/L; % for N point fft
f = sampling_frequency/2*linspace(0,1,N_point_fft/2); % N_point_fft/2 points b/w 0 and 1
%===================================================%
%SINGLE SIDED AMPLITUDE SPECTRUM
%===================================================%
h12=figure
plot(f,2*abs(y2(1:N_point_fft/2)))
title('Single-Sided Amplitude Spectrum of THETA x2(t)')
xlabel('Frequency (Hz)')
ylabel('|Y2(f)|')
%----------------------------------------------------%
%ALPHA BAND PASS FILTER (8-12)
%----------------------------------------------------%
sampling_frequency = 500; % Sampling Frequency
Fstop1 = 7.5; % First Stopband Frequency
Fpass1 = 8; % First Passband Frequency
Fpass2 = 12; % Second Passband Frequency
Fstop2 = 12.5; % Second Stopband Frequency
Dstop1 = 0.0001; % First Stopband Attenuation
Dpass = 0.057501127785; % Passband Ripple
Dstop2 = 0.0001; % Second Stopband Attenuation
density = 20; % Density Factor
% Calculating the order from the parameters using FIRPMORD.
[n, fo, ao, w] = firpmord([Fstop1 Fpass1 Fpass2 Fstop2]/(sampling_frequency/2), [0 1 0], [Dstop1 Dpass Dstop2]);
% fo is the frequency ao is the amplitude response vector
% Calculating the coefficients using the FIRPM function.
b3 = firpm(n, fo, ao, w, {density});
Hd3 = dfilt.dffir(b3); %discrete time direct form fir filter
x3=filter(Hd3,data);
h13=figure
plot(t,x3,'g')
title('waveform for ALPHA band')
%=========================================================%
%FREQUENCY SPECTRUM OF ALPHA BAND
%=========================================================%
L=10;
sampling_frequency=500;
N_point_fft = 2^nextpow2(L); % Next power of 2 from length of x3
y3 = fft(x3,N_point_fft)/L; % for N point fft
f = sampling_frequency/2*linspace(0,1,N_point_fft/2); % N_point_fft/2 points b/w 0 and 1
%==========================================================%
%SINGLE SIDED AMPLITUDE SPECTRUM
%==========================================================%
h14=figure
plot(f,2*abs(y3(1:N_point_fft/2)))
title('Single-Sided Amplitude Spectrum of ALPHA x3(t)')
xlabel('Frequency (Hz)')
ylabel('|Y3(f)|')
%------------------------------------------------%
%BETA BAND PASS FILTER (12-30)
%------------------------------------------------%
sampling_frequency = 500; % Sampling Frequency
Fstop1 = 11.5; % First Stopband Frequency
Fpass1 = 12; % First Passband Frequency
Fpass2 = 30; % Second Passband Frequency
Fstop2 = 30.5; % Second Stopband Frequency
Dstop1 = 0.0001; % First Stopband Attenuation
Dpass = 0.057501127785; % Passband Ripple
Dstop2 = 0.0001; % Second Stopband Attenuation
density = 20; % Density Factor
% Calculating the order from the parameters using FIRPMORD.
[n, fo, ao, w] = firpmord([Fstop1 Fpass1 Fpass2 Fstop2]/(sampling_frequency/2), [0 1 0], [Dstop1 Dpass Dstop2]);
% fo is the frequency ao is the amplitude response vector
% Calculatng the coefficients using the FIRPM function
b4 = firpm(n, fo, ao, w, {density});
Hd4 = dfilt.dffir(b4); %discrete time direct form fir filter
x4=filter(Hd4,data);
h15=figure
plot(t,x4,'y')
title('waveform for BETA band')
%==========================================================%
%FREQUENCY SPECTRUM OF BETA
%==========================================================%
L=10;
sampling_frequency=500;
N_point_fft = 2^nextpow2(L); % Next power of 2 from length of x4
y4 = fft(x4,N_point_fft)/L; % for N point fft
f = sampling_frequency/2*linspace(0,1,N_point_fft/2); % N_point_fft/2 points b/w 0 and 1
%==========================================================%
%SINGLE SIDED AMPLITUDE SPECTRUM
%==========================================================%
h16=figure
plot(f,2*abs(y4(1:N_point_fft/2)))
title('Single-Sided Amplitude Spectrum of BETA x4(t)')
xlabel('Frequency (Hz)')
ylabel('|Y4(f)|')
%============================================================%
%AMPLITUDE SPECTRUMS TOGETHER
%============================================================%
h17=figure
plot(f,2*abs(y1(1:N_point_fft/2)),'k',f,2*abs(y2(1:N_point_fft/2)),'r',f,2*abs(y3(1:N_point_fft/2)),'g',f,2*abs(y4(1:N_point_fft/2)),'b')
title('Single-Sided Amplitude Spectrums')
xlabel('Frequency (Hz)')
ylabel('|Y(f)|')
legend('DELTA','THETA','APLHA','BETA');