def test_to_rr(self):
ppg = import_ppg().ppg.to_numpy()
signal, peaks = oxi_peaks(ppg)
rr = to_rr(peaks)
assert rr.mean() == 874.2068965517242
rr = to_rr(np.where(peaks)[0])
assert rr.mean() == 874.2068965517242
def plot_oximeter(x, sfreq=75, ax=None):
"""Plot PPG signal.
Parameters
----------
x : 1d array-like or `systole.recording.Oximeter`
The ppg signal, or the Oximeter instance used to record the signal.
sfreq : int
Signal sampling frequency. Default is 75 Hz.
ax : `Matplotlib.Axes` or None
Where to draw the plot. Default is *None* (create a new figure).
Returns
-------
ax : `Matplotlib.Axes`
The figure.
"""
if isinstance(x, (list, np.ndarray)):
times = np.arange(0, len(x) / sfreq, 1 / sfreq)
recording = np.asarray(x)
signal, peaks = oxi_peaks(x, new_sfreq=sfreq)
threshold = None
label = 'Offline estimation'
else:
times = np.asarray(x.times)
recording = np.asarray(x.recording)
peaks = np.asarray(x.peaks)
threshold = np.asarray(x.threshold)
label = 'Online estimation'
if ax is None:
fig, ax = plt.subplots(figsize=(13, 5))
ax.set_title('Oximeter recording', fontweight='bold')
if threshold is not None:
ax.plot(times,
threshold,
linestyle='--',
color='gray',
label='Threshold')
ax.fill_between(x=times,
y1=threshold,
y2=recording.min(),
alpha=0.2,
color='gray')
ax.plot(times, recording, label='Recording', color='#4c72b0')
ax.fill_between(x=times, y1=recording, y2=recording.min(), color='w')
ax.plot(times[np.where(peaks)[0]],
recording[np.where(peaks)[0]],
'o',
color='#c44e52',
label=label)
ax.set_ylabel('PPG level')
ax.set_xlabel('Time (s)')
ax.legend()
return ax
def test_norm_triggers(self):
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
peaks[np.where(peaks)[0] + 1] = 1
peaks[np.where(peaks)[0] + 2] = 1
y = norm_triggers(peaks)
assert sum(y) == 378
peaks = -peaks
y = norm_triggers(peaks, threshold=-1, direction='lower')
assert sum(y) == 378
def test_to_angle(self):
"""Test to_angles function"""
rr = import_rr().rr.values
# Create event vector
events = rr + np.random.normal(500, 100, len(rr))
ang = to_angles(list(np.cumsum(rr)), list(np.cumsum(events)))
assert ~np.any(np.asarray(ang) < 0)
assert ~np.any(np.asarray(ang) > np.pi * 2)
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
ang = to_angles(peaks, peaks)
def test_heart_rate(self):
"""Test heart_rate function"""
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
heartrate, time = heart_rate(peaks)
assert len(heartrate) == len(time)
heartrate, time = heart_rate(list(peaks))
assert len(heartrate) == len(time)
heartrate, time = heart_rate(peaks,
unit='bpm',
kind='cubic',
sfreq=500)
assert len(heartrate) == len(time)
def test_norm_triggers(self):
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
peaks[np.where(peaks)[0] + 1] = 1
peaks[np.where(peaks)[0] + 2] = 1
peaks[-1:] = 1
y = norm_triggers(peaks)
assert sum(y) == 379
peaks = -peaks.astype(int)
y = norm_triggers(peaks, threshold=-1, direction='lower')
assert sum(y) == 379
with pytest.raises(ValueError):
norm_triggers(None)
with pytest.raises(ValueError):
norm_triggers(peaks, direction='invalid')
def test_heart_rate(self):
"""Test heart_rate function"""
ppg = import_ppg().ppg.to_numpy() # Import PPG recording
signal, peaks = oxi_peaks(ppg)
heartrate, time = heart_rate(peaks)
assert len(heartrate) == len(time)
heartrate, time = heart_rate(list(peaks))
assert len(heartrate) == len(time)
heartrate, time = heart_rate(peaks,
unit='bpm',
kind='cubic',
sfreq=500)
assert len(heartrate) == len(time)
with pytest.raises(ValueError):
heartrate, time = heart_rate([1, 2, 3])
def find_peaks(self, **kwargs):
"""Find peaks in recorded signal.
Returns
-------
Oximeter instance. The peaks occurences are stored in the `peaks`
attribute.
Other Parameters
----------------
**kwargs : `~systole.detection.oxi_peaks` properties.
"""
# Peak detection
resampled_signal, peaks = oxi_peaks(self.recording,
new_sfreq=75,
**kwargs)
# R-R intervals (in miliseconds)
self.rr = (np.diff(np.where(peaks)[0]) / self.sfreq) * 1000
# Beats per minutes
self.bpm = 60000 / self.rr
return self
def test_oxi_peaks(self):
"""Test oxi_peaks function"""
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
assert len(signal) == len(peaks)
assert np.all(np.unique(peaks) == [0, 1])
def plot_raw(signal, sfreq=75):
"""Interactive visualization of PPG signal and beats detection.
Parameters
----------
signal : `pd.DataFrame` instance or 1d array-like
Dataframe of signal recording in the long format. Should contain at
least the two following columns: ['time', 'signal']. If an array is
provided, will automatically create the DataFrame using th array as
signal and *sfreq* as sampling frequency.
sfreq : int
Signal sampling frequency. Default is 75 Hz.
"""
if isinstance(signal, pd.DataFrame):
# Find peaks - Remove learning phase
signal, peaks = oxi_peaks(signal.signal, noise_removal=False)
else:
signal, peaks = oxi_peaks(signal, noise_removal=False)
time = np.arange(0, len(signal)) / 1000
# Extract heart rate
hr, time = heart_rate(peaks, sfreq=1000, unit='rr', kind='previous')
#############
# Upper panel
#############
# Signal
ppg_trace = go.Scattergl(x=time,
y=signal,
mode='lines',
name='PPG',
hoverinfo='skip',
showlegend=False,
line=dict(width=1, color='#c44e52'))
# Peaks
peaks_trace = go.Scattergl(x=time[peaks],
y=signal[peaks],
mode='markers',
name='Peaks',
hoverinfo='y',
showlegend=False,
marker=dict(size=8,
color='white',
line=dict(width=2,
color='DarkSlateGrey')))
#############
# Lower panel
#############
# Instantaneous Heart Rate - Lines
rr_trace = go.Scattergl(x=time,
y=hr,
mode='lines',
name='R-R intervals',
hoverinfo='skip',
showlegend=False,
line=dict(width=1, color='#4c72b0'))
# Instantaneous Heart Rate - Peaks
rr_peaks = go.Scattergl(x=time[peaks],
y=hr[peaks],
mode='markers',
name='R-R intervals',
showlegend=False,
marker=dict(size=6,
color='white',
line=dict(width=2,
color='DarkSlateGrey')))
raw = make_subplots(rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=.05,
row_titles=['Recording', 'Heart rate'])
raw.update_layout(plot_bgcolor="white",
paper_bgcolor="white",
margin=dict(l=5, r=5, b=5, t=5),
autosize=True)
raw.add_trace(ppg_trace, 1, 1)
raw.add_trace(peaks_trace, 1, 1)
raw.add_trace(rr_trace, 2, 1)
raw.add_trace(rr_peaks, 2, 1)
return raw
def plot_raw(signal, sfreq=75, type='ppg'):
"""Interactive visualization of PPG signal and beats detection.
Parameters
----------
signal : :py:class:`pandas.DataFrame` or 1d array-like
Dataframe of signal recording in the long format. Should contain at
least one ``'time'`` and one signal colum (can be ``'ppg'`` or
``'ecg'``). If an array is provided, will automatically create the
DataFrame using the array as signal and ``sfreq`` as sampling
frequency.
sfreq : int
Signal sampling frequency. Default is 75 Hz.
type : str
The recording modality. Can be ``'ppg'`` (pulse oximeter) or ``'ecg'``
(electrocardiography).
"""
import plotly.graph_objs as go
from plotly.subplots import make_subplots
if isinstance(signal, pd.DataFrame):
# Find peaks - Remove learning phase
if type == 'ppg':
signal, peaks = oxi_peaks(signal.ppg, noise_removal=False)
elif type == 'ecg':
signal, peaks = ecg_peaks(signal.ecg,
method='hamilton',
find_local=True)
else:
if type == 'ppg':
signal, peaks = oxi_peaks(signal, noise_removal=False, sfreq=sfreq)
elif type == 'ecg':
signal, peaks = ecg_peaks(signal,
method='hamilton',
sfreq=sfreq,
find_local=True)
time = np.arange(0, len(signal)) / 1000
# Extract heart rate
hr, time = heart_rate(peaks, sfreq=1000, unit='rr', kind='linear')
#############
# Upper panel
#############
# Signal
ppg_trace = go.Scattergl(x=time,
y=signal,
mode='lines',
name='PPG',
hoverinfo='skip',
showlegend=False,
line=dict(width=1, color='#c44e52'))
# Peaks
peaks_trace = go.Scattergl(x=time[peaks],
y=signal[peaks],
mode='markers',
name='Peaks',
hoverinfo='y',
showlegend=False,
marker=dict(size=8,
color='white',
line=dict(width=2,
color='DarkSlateGrey')))
#############
# Lower panel
#############
# Instantaneous Heart Rate - Lines
rr_trace = go.Scattergl(x=time,
y=hr,
mode='lines',
name='R-R intervals',
hoverinfo='skip',
showlegend=False,
line=dict(width=1, color='#4c72b0'))
# Instantaneous Heart Rate - Peaks
rr_peaks = go.Scattergl(x=time[peaks],
y=hr[peaks],
mode='markers',
name='R-R intervals',
showlegend=False,
marker=dict(size=6,
color='white',
line=dict(width=2,
color='DarkSlateGrey')))
raw = make_subplots(rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=.05,
row_titles=['Recording', 'Heart rate'])
raw.update_layout(plot_bgcolor="white",
paper_bgcolor="white",
margin=dict(l=5, r=5, b=5, t=5),
autosize=True,
xaxis_title="Time (s)")
raw.add_trace(ppg_trace, 1, 1)
raw.add_trace(peaks_trace, 1, 1)
raw.add_trace(rr_trace, 2, 1)
raw.add_trace(rr_peaks, 2, 1)
return raw
def report_oxi(signal, file_name='report.png', dpi=600):
"""Generate HRV report.
Parameters
----------
signal : 1d array-like
PPG singal.
file_name : str
Output file name.
dpi : int
Image quality.
"""
from systole import import_ppg
signal = import_ppg('1')[0]
plot_oximeter(signal)
# Find peaks
signal, peaks = oxi_peaks(signal)
# Extract instantaneous heartrate
sfreq = 1000
noisy_hr, time = heart_rate(peaks, sfreq=sfreq, unit='bpm', kind='cubic')
time = np.arange(0, len(signal) / sfreq, 1 / sfreq)
fig = plt.figure(figsize=(8, 13))
gs = fig.add_gridspec(4, 3)
fig_ax1 = fig.add_subplot(gs[0, :])
fig_ax1.plot(time, signal, linewidth=.2)
fig_ax1.set_ylabel('PPG level')
fig_ax1.set_xlim(0, time[-1])
fig_ax1.set_title('Signal', fontweight='bold')
fig_ax2 = fig.add_subplot(gs[1, :])
fig_ax2.plot(time, noisy_hr, linewidth=.8, color='r')
fig_ax2.set_ylabel('BPM')
fig_ax2.set_xlabel('Time (s)')
fig_ax2.set_xlim(0, time[-1])
fig_ax2.set_title('RR time-course', fontweight='bold')
# HRV
rr = np.diff(np.where(peaks)[0])
fig_ax3 = fig.add_subplot(gs[2, 0])
fig_ax3.hist(rr, bins=30, alpha=.5)
fig_ax3.hist(rr[(rr <= 400) | (rr >= 1500)], bins=30, color='r')
fig_ax3.set_title('Distribution', fontweight='bold')
fig_ax3.set_ylabel('Count')
fig_ax3.set_xlabel('RR(s)')
fig_ax4 = fig.add_subplot(gs[2, 1])
plot_psd(rr, show=True, ax=fig_ax4)
fig_ax5 = fig.add_subplot(gs[2, 2])
fig_ax5.plot(rr[:-1], rr[1:], color='gray', markersize=1, alpha=0.8)
fig_ax5.set_title('Pointcare Plot', fontweight='bold')
fig_ax5.set_ylabel('$RR_{n+1}$')
fig_ax5.set_xlabel('$RR_n$')
plt.tight_layout(h_pad=0.05)
if file_name is not None:
plt.savefig(file_name, dpi=dpi)
plt.close()
def test_oxi_peaks(self):
"""Test oxi_peaks function"""
df = import_ppg() # Import PPG recording
signal, peaks = oxi_peaks(df.ppg.to_numpy())
assert len(signal) == len(peaks)
assert np.all(np.unique(peaks) == [0, 1])