Source code for pyPPG.ppg_sqi

import numpy as np
from scipy.signal import detrend, find_peaks, correlate

[docs] def get_ppgSQI(ppg: list, fs: int, annotation: list): ''' PPG Signal Quality Index based on beat template correlation. :param ppg: a vector of PPG values :type ppg: int :param fs: Samples frequency :type fs: int :param annotation: PPG annotation time(samples) :type annotation: list :return: psqi: PPG Signal Quality Index Reference: ---------- - `Original Matlab implementation <https://github.com/MIT-LCP/PhysioNetChallengePublic/blob/master/2015/sample-submission/ppgSQI.m>`_: Qiao Li, November 10, 2014. - Python implementation: Márton Áron Goda, PhD, November 11, 2022. ''' Fs = fs # Create PPG template t,v = use_template(ppg, annotation-1, fs) c1 = np.empty(len(annotation)-1) c1[:] = np.NaN psqi = np.empty(len(annotation)-1) psqi[:] = np.NaN for j in range (0,len(annotation) - 1): # Calculate correlation coefficients based on the template length beatbegin = annotation[j]-1 beatend = annotation[j + 1]-1 if beatend - beatbegin > 3 * Fs: beatend = beatbegin + 3 * Fs templatelength = len(t) if (beatbegin + templatelength - 1 > len(ppg)) or (beatend > len(ppg)) or (beatbegin < 1): continue currentb = j cc = np.corrcoef(t, ppg[beatbegin:beatbegin + templatelength]) c1[j] = cc[0, 1] if (c1[j] < 0): c1[j] = 0 psqi[currentb] = c1[j] return psqi
[docs] def use_template(wave, annotation: list, fs: int): ''' PPG waveform template creation. Written by Qiao Li, February 21, 2011 :param wave: a vector of PPG wave :type ppg: int :param fs: Samples frequency :type fs: int :param annotation: PPG annotation time(sample) :type ann_ppg: list :return: - template: PPG waveform template based on normal - length beats - valid: 1 for valid template, 0 for invalid template ''' template = [] valid = 0 # according to heart rate max(300 bpm) and min(20 bpm) to get max and min beat - by - beat interval hr_max = 300 bb_interval_min = fs * 60 / hr_max hr_min = 20 bb_interval_max = fs * 60 / hr_min # Normal beat thresholds normal_beat_length_min = 0.7 normal_beat_lentth_max = 1.5 normal_beat_percent_threshold = 0.5 # using correlate to get the basic period of the PPG as the length of template data = detrend(wave) y = correlate(data, data, 'full', method='fft') lenw = len(wave) lena = len(annotation) i = lenw locs = find_peaks(y[i:])[0] pks = y[locs] if len(pks)==0: return max_v=max(pks) max_i=np.where(pks==max_v)[0][0] i = locs[max_i] cycle = fs if i < lenw - 1: cycle = i # cumulate the beats with reasonable length to get template if lena < 2: return p0 = 1 i = annotation[p0] temp_ahead=0 while i - temp_ahead < 1: p0 = p0 + 1 if (p0 > lena): template = wave valid = 0 return i = annotation[p0] if p0 + 1 >= lena: return beat_interval = np.diff(annotation[p0:len(annotation)]) median_bi = np.median(beat_interval) if median_bi!='NaN': temp_peak = abs(locs - median_bi) m = min(temp_peak) i = np.where(temp_peak==m)[0][0] cycle = locs[i]+1 else: return # the length of template valid detection valid = 1 if (cycle > bb_interval_max) or (cycle < bb_interval_min): valid = 0 template = np.zeros(cycle) return n = 0 d1 = 0 invalidn = 0 currentbeatlength = annotation[p0 + 1] - annotation[p0] if currentbeatlength > 0: d1 = wave[i - temp_ahead:i + cycle] n = 1 else: invalidn = invalidn + 1 d1 = np.zeros(cycle + temp_ahead) p0 = p0 if p0 < lena - 1: i = annotation[p0] n = 1 invalidn = 0 while (i < lenw - cycle) and (p0 < lena - 1): currentbeatlength = annotation[p0 + 1] - annotation[p0] if currentbeatlength > 0: d1 = d1 + wave[i - temp_ahead:i + cycle] n = n + 1 else: invalidn = invalidn + 1 p0 = p0 + 1 i = annotation[p0] d1 = d1/n # normal beat is less than the reasonable percentage of all beats if (n / (n + invalidn)) < normal_beat_percent_threshold: valid = 0 else: valid = 0 else: valid=0 template = d1 return template,valid