annotation

EcgAnnotation

Bases: SignalAnnotation

envelope_filter = signals.envelope_filter instance-attribute

filtered_signals = self.signals_cls.copy_from_signal(Envelope(signals).filter(), fs=self.fs) instance-attribute

qrs_offset_area = None instance-attribute

qrs_offset_window = signals.qrs_offset_window instance-attribute

qrs_offsets = None instance-attribute

qrs_onset_area = None instance-attribute

qrs_onset_window = signals.qrs_onset_window instance-attribute

qrs_onsets = None instance-attribute

r_peak_distance = signals.r_peak_distance instance-attribute

r_peak_height = signals.r_peak_height instance-attribute

r_peaks = None instance-attribute

smoothing_window = signals.smoothing_window instance-attribute

t_offset_area = None instance-attribute

t_offset_window = signals.t_offset_window instance-attribute

t_wave_offsets = None instance-attribute

__init__(signals)

annotate()

get_qrs_offsets()

Calculate qrs offsets.

get_qrs_onsets()

Calculate qrs onsets.

get_r_peaks()

Calculate the position of all R peaks in the ECG. The detection can be improved by setting the r_peak_distance and r_peak_height to the correct value.

Returns:

Name	Type	Description
list	list	A list of R-peaks per signal in self.signals.

get_t_wave_offset()

Calculate t-wave offset

PeakAnnotation

Bases: SignalAnnotation

The peak annotator finds the elements in the signal array that correspond to the peaks in the signal and returns the corresponding indices of these peaks. A minimum periodic distance between peaks can be passed.

min_peak_distance = signals.min_peak_distance instance-attribute

__init__(signals)

Parameters:

Name	Type	Description	Default
signals	Signals	an array of the signals to find peaks in	required

annotate()

Find peaks in the signal. The returned array contains the indexes of the peaks in the signal array. if the signal array is 2D, the shape will be: number of signals x max number of peaks

For signals with less elements than max number of peaks, the remaining elements at the end of the array will be np.nan

Returns:

Type	Description
ndarray	np.ndarray: an array of the signals indexes of the peaks

ThresholdAnnotation

Bases: SignalAnnotation

Annotate the locations in a signal where a threshold value is crossed. Only crossings exceeding the threshold value are considered. This means a signal going from a lower value to a higher value than the threshold.

Attributes:

Name	Type	Description
signals	ndarray	an array of the signals to find peaks in
threshold	number	a threshold value that must be crossed

fs = int(1000 / signals.fs) instance-attribute

threshold = signals.threshold instance-attribute

__init__(signals)

annotate()

Annotate the indices in a signal where a threshold value is crossed.

The returning array will be of shape (len(signals), max_number_of_crossings)

Returns:

Type	Description
ndarray	np.ndarray: an array of the crossing indices