clear all % clears all active variables

close all

clc

load('ecg_Noisy');

L = length(x);

T = 1/fs; %sampling interval

t=[0:L-1]*T;

figure

plot(t, x)

axis tight;

xlabel('Time in seconds');

ylabel('ECG Amplitude');

X= abs(fftshift(fft(x))); %fourier transfrom of the ECG signal

fo=fs/L;

f= [-L/2:L/2-1]*fo;

figure

plot(f, X)

axis tight;

xlabel('frequency in Hz');

ylabel('ECG Spectrum');

Wod w Project The ECG signal, shown in Figure 1 below, and saved in ecg_Noisy. mat file has various types of noises (Respiration Baseline wandering, powerline interference, and high-frequency noise). Design an appropriate filters to remove those different noises. Use "Noisy ECG_Project.m" file to start writing your code. ECO Ante Timeconds Noisy ECG_Project.mx + #clears all active variables clear all close all clc load('ecg_Noisy'); L = length(x): T-1/ts: sampling interval =[0:L-1]*T. figure plot(t, x) axis tight: wlabel('Time in seconds) ylabel('ECG Amplitude'); X= abs(fftshift(ft (x))), fourier transfrom of the ECG signal fo=fs/L: f= [-L/2:L/2-11 fo: figure plot(t, x) axis tight #label (deequency in HP) ylabel (EG Spectrum); Workspace Name Value Min Max fs 1000 1000 9519x1 double 1000 -3.0449 3.2868 Wod w Project The ECG signal, shown in Figure 1 below, and saved in ecg_Noisy. mat file has various types of noises (Respiration Baseline wandering, powerline interference, and high-frequency noise). Design an appropriate filters to remove those different noises. Use "Noisy ECG_Project.m" file to start writing your code. ECO Ante Timeconds Noisy ECG_Project.mx + #clears all active variables clear all close all clc load('ecg_Noisy'); L = length(x): T-1/ts: sampling interval =[0:L-1]*T. figure plot(t, x) axis tight: wlabel('Time in seconds) ylabel('ECG Amplitude'); X= abs(fftshift(ft (x))), fourier transfrom of the ECG signal fo=fs/L: f= [-L/2:L/2-11 fo: figure plot(t, x) axis tight #label (deequency in HP) ylabel (EG Spectrum); Workspace Name Value Min Max fs 1000 1000 9519x1 double 1000 -3.0449 3.2868