def _find_peak(siginfo):
"""
Obtains an estimation of the peak situation of a QRS complex, from the
energy interval that forms the base evidence, a fragment of signal evidence,
a reference time point, and the interval of valid points for the peak.
"""
dist = lambda p : 1.0 + 2.0 * abs(p - C.QRS_BANN_DMAX)/ms2sp(150)
dist = np.vectorize(dist)
peak = None
#For each lead, the peak will be the maximum deviation point wrt the
#baseline, and applying the distance function just defined. We give more
#importance to the first leads, as they supposedly have more quality.
for _, sig, points, baseline, _ in siginfo:
if len(points) < 3:
continue
peaks = points[sig_meas.get_peaks(sig[points])]
if len(peaks) == 0:
continue
peakscore = abs(sig[peaks]-baseline)/dist(peaks)
lpeak = peaks[peakscore.argmax()]
if peak is None:
peak = lpeak
elif abs(peak-lpeak) <= C.TMARGIN:
peak = lpeak if lpeak < peak else peak
return peak
def delineate_qrs(siginfo):
"""
Performs the multi-lead delineation of a QRS complex enclosed in a
specific time interval, returning an instance of the QRS class.
Parameters
----------
siginfo:
List-like structure containing all the necessary information of the
ECG signal in the searching time interval. Each entry in this list
is assumed to be a tuple of the **LeadInfo** class, and the list is
assumed to be ordered by the quality of the signal in each lead.
Returns
-------
out:
QRS object with all the attributes properly set. If the delineation
cannot be performed, an InconsistencyError is raised.
"""
verify(siginfo)
qrs = QRS()
#Peak point estimation.
peak = _find_peak(siginfo)
verify(peak is not None)
#QRS start and end estimation
#For each lead, we first check if it is a paced beat, whose delineation
#process is different. In case of failure, we perform common delineation.
limits = OrderedDict()
for lead, sig, points, baseline, _ in siginfo:
endpoints = _paced_qrs_delineation(sig, points, peak, baseline)
if endpoints is None:
endpoints = _qrs_delineation(sig, points, peak)
if endpoints is None:
continue
limits[lead] = (False, endpoints)
else:
limits[lead] = (True, endpoints)
#Now we combine the limits in all leads.
start, end = _combine_limits(limits, siginfo, peak)
verify(start is not None and end > start)
#QRS waveform extraction for each lead.
for lead, sig, points, baseline, _ in siginfo:
#We constrain the area delineated so far.
sig = sig[start:end+1]
points = points[np.logical_and(points >= start,
points <= end)] - start
if len(points) == 0:
continue
if points[0] != 0:
points = np.insert(points, 0, 0)
if points[-1] != len(sig) - 1:
points = np.append(points, len(sig) - 1)
if len(points) < 3:
continue
#We define a distance function to evaluate the peaks
dist = (lambda p : 1.0 + 2.0 * abs(start + p - C.QRS_BANN_DMAX)
/ms2sp(150))
dist = np.vectorize(dist)
#We get the peak for this lead
pks = points[sig_meas.get_peaks(sig[points])]
if len(pks) == 0:
continue
peakscore = abs(sig[pks]-baseline)/dist(pks)
peak = pks[peakscore.argmax()]
#Now we get the shape of the QRS complex in this lead.
shape = None
#If there is a pace detection in this lead
if lead in limits and limits[lead][0]:
endpoints = limits[lead][1]
shape = _get_paced_qrs_shape(sig, points,
endpoints.start - start,
min(endpoints.end-start,len(sig)))
if shape is None:
limits[lead] = (False, endpoints)
if shape is None:
shape = _get_qrs_shape(sig, points, peak, baseline)
if shape is None:
continue
qrs.shape[lead] = shape
#There must be a recognizable QRS waveform in at least one lead.
verify(qrs.shape)
#The detected shapes may constrain the delineation area.
llim = min(qrs.shape[lead].waves[0].l for lead in qrs.shape)
if llim > 0:
start = start + llim
for lead in qrs.shape:
qrs.shape[lead].move(-llim)
ulim = max(qrs.shape[lead].waves[-1].r for lead in qrs.shape)
if ulim < end-start:
end = start + ulim
#The definitive peak is assigned to the first relevant wave
#(each QRS shapeform has a specific peak point.)
peak = start + min(s.waves[_reference_wave(s)].m
for s in qrs.shape.itervalues())
#Segmentation points set
qrs.paced = any(v[0] for v in limits.itervalues())
qrs.start, qrs.peak, qrs.end = start, peak, end
###################################################################
#Amplitude conditions (between 0.5mV and 6.5 mV in at least one
#lead or an identified pattern in most leads).
###################################################################
verify(len(qrs.shape) > len(siginfo)/2.0 or
C.QRS_MIN_AMP <= max(s.amplitude for s in qrs.shape.itervalues())
<= C.QRS_MAX_AMP)
return qrs
