In [3]:
path = '/content/gdrive/MyDrive/physiological-signals-processing-challenge-2021/data_challenge/training/'
names_list = []
for i in range(1, 551):
pat_filename = '{}.hea'.format(i)
names_list.append(pat_filename)
signals_list = []
for elem in names_list:
pat = loadmat(os.path.join(path, elem[:-4] + '.mat')) # reading the signals' file.
signals_list.append(pat)
for elem in signals_list:
elem = sc.signal.resample(elem['val'], 125) #resampling to 125 Hz.
#plotting a sample
t = np.arange(0, 75000)/125
plt.figure(figsize = (15, 15))
plt.subplot(221)
plt.plot(t, signals_list[1]['val'][0,:75000])
plt.title('II Derivation')
plt.xlim(0, 50)
plt.subplot(222)
plt.plot(t, signals_list[1]['val'][1,:75000])
plt.title('V Derivation')
plt.xlim(0, 50)
plt.subplot(223)
plt.plot(t, signals_list[1]['val'][2, :75000])
plt.title('PLETH Derivation')
plt.xlim(0, 50)
plt.subplot(224)
plt.plot(t, signals_list[1]['val'][3, :75000])
plt.title('ABP Derivation')
plt.xlim(0, 50)
Out[3]:
(0.0, 50.0)
