clear all;
load('examples.mat');
n = 57;
y = examples(n).data;
figure(1)
grid on;
plot(y);
xlabel('Times');
ylabel('Amplitude');
title('Original Noisy Signal');
fs = 30;
fpass = 3;
yf = lowpass(y, fpass, fs);
figure(2)
grid on;
plot(yf);
xlabel('Times');
ylabel('Amplitude');
title('Filtered Signal');
Prashant Kumar answered . 2024-05-06 13:13:30
D = load('examples.mat');
data = D.ppg.data;
Fs = 30; % Sampling Frequency (Hz)
Fn = Fs/2; % Nyquist Frequency (Hz)
L = numel(data);
t = linspace(0, L, L)/Fs;
figure
plot(t, data)
grid
title('PPG Signal')
xlabel('Time (s)')
ylabel('Amplitude (?)')
datam = mean(data);
FTdata = fft(data - datam)/L;
Fv = linspace(0, 1, fix(L/2)+1)*Fn; % Frequency Vector
Iv = 1:numel(Fv); % Index Vector
figure
plot(Fv, abs(FTdata(Iv))*2)
grid
title('Fourier Transform - Original Signal')
xlabel('Frequency (Hz)')
ylabel('Amplitude (?)')
xlim([0 7])
datafilt = smoothdata(data, 'rlowess', 15);
datam = mean(datafilt);
FTdatafilt = fft(datafilt - datam)/L;
Fv = linspace(0, 1, fix(L/2)+1)*Fn; % Frequency Vector
Iv = 1:numel(Fv); % Index Vector
figure
plot(Fv, abs(FTdatafilt(Iv))*2)
grid
title('Fourier Transform - Filtered Signal')
xlabel('Frequency (Hz)')
ylabel('Amplitude (?)')
xlim([0 7])
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