用Python中的LombScargle对HRV数据进行光谱分析
我正在使用RR峰值，并希望推导出HRV的频域测量值，以便通过Physionet（WFDB工具）重新创建本机C包的结果。对于我来说，信号处理和频谱分析都是新的领域，但经过长时间的试验和错误之后，我在尝试了其他几个解决方案后，基于Astropy模块将一些代码整合在一起。
from astropy.stats import LombScargle
import random
dy = 0.1 * random.randint(1,100)
t = drive01["time"].values
y = drive01["intervals"].values
frequency, power = LombScargle(t, y,dy).autopower(minimum_frequency=0.0,maximum_frequency=4)
plt.plot(frequency, power)
这会创建一个与Physionets包中的图非常相似的图。
带有代码get_hrv的Physionets HRV工具制作了这个图
然后通过计算常见的频域测量，我得到了截然不同的结果。
Pxx = np.nan_to_num(power)
Fxx = np.nan_to_num(frequency)
ulf = 0.003
vlf = 0.04
lf = 0.15
hf = 0.4
Fs = 15.5 # the sampling rate of the drive file
# find the indexes corresponding to the VLF, LF, and HF bands
vlf_freq_band = (Fxx >= ulf) & (Fxx <= vlf)
lf_freq_band = (Fxx >= vlf) & (Fxx <= lf)
hf_freq_band = (Fxx >= lf) & (Fxx <= hf)
tp_freq_band = (Fxx >= 0) & (Fxx <= hf)
# Calculate the area under the given frequency band
dy = 1.0 / Fs
VLF = np.trapz(y=abs(Pxx[vlf_freq_band]), x=None, dx=dy)
LF = np.trapz(y=abs(Pxx[lf_freq_band]), x=None, dx=dy)
HF = np.trapz(y=abs(Pxx[hf_freq_band]), x=None, dx=dy)
TP = np.trapz(y=abs(Pxx[tp_freq_band]), x=None, dx=dy)
LF_HF = float(LF) / HF
的Python
'HF': 0.10918703853414605,
'LF': 0.050074418080717789,
'LF/HF': 0.45861137689028925,
'TP': 0.20150514290250854,
'VLF': 0.025953350304821571
来自Physionet包：
TOT PWR = 0.0185973
VLF PWR = 0.00372733
LF PWR = 0.00472635
HF PWR = 0.0101436
LF/HF = 0.465944
比较结果时，它看起来像这样：
Python Physionet
TP 0.201505143 0.0185973 Quite similar + decimal dif
HF 0.109187039 0.0101436 Quite similar + decimal dif
LF 0.050074418 0.00472635 Quite similar + decimal dif
VLF 0.02595335 0.00372733 Not similar
LF/HF 0.458611377 0.465944 Quite similar
Python中的计算是基于来自另一个Stackoverflow post的代码，但是他从受访者那里获得的修复是基于我无法工作的python模块而他没有使用Lomb Periodgram。我也非常愿意尝试别的东西，只要它处理不均匀的样品。 我正在使用的数据是drivedb from Physionet，我使用了Physionet包来创建一个带有RR峰值和时间的文本文件，该文件被读入Pandas DataFrame。 The textfile can be found here
1 个答案:
答案 0 :(得分：1)
基于Strationet的C封装（WFDB工具）基于Astropy的LombScargle计算能力有所不同。我用python再次编写了lombscargle，使用Physionet（WFDB工具）的C包得到了相同的结果。
import numpy as np
import os
import math
import csv
from itertools import zip_longest
import time
DATA_PATH = '/home/quangpc/Desktop/Data/PhysionetData/mitdb/'
class FreqDomainClass:
@staticmethod
def power(freq, mag):
lo = [0, 0.0033, 0.04, 0.15]
hi = [0.0033, 0.04, 0.15, 0.4]
pr = np.zeros(4)
nbands = 4
for index in range(0, len(freq)):
pwr = np.power(mag[index], 2)
for n in range(0, nbands):
if (freq[index] >= lo[n]) and freq[index] <= hi[n]:
pr[n] += pwr
break
return pr
@staticmethod
def avevar(y):
var = 0.0
ep = 0.0
ave = np.mean(y)
for i in range(len(y)):
s = y[i] - ave
ep += s
var += s * s
var = (var - ep * ep / len(y)) / (len(y) - 1)
return var
def lomb(self, t, h, ofac, hifac):
period = max(t) - min(t)
z = h - np.mean(h)
f = np.arange(1 / (period * ofac), hifac * len(h) / (2 * period), 1 / (period * ofac))
f = f[:int(len(f) / 2) + 1]
f = np.reshape(f, (len(f), -1))
w = 2 * np.pi * f
lenght_t = len(t)
t = np.reshape(t, (lenght_t, -1))
t = np.transpose(t)
tau = np.arctan2(np.sum(np.sin(2 * w * t), axis=1), np.sum(np.cos(2 * w * t), axis=1)) / (2 * w)
tau = np.diag(tau)
tau = np.reshape(tau, (len(tau), -1))
tau = np.tile(tau, (1, lenght_t))
cos = np.cos(w * (t - tau))
sin = np.sin(w * (t - tau))
pc = np.power(np.sum(z * cos, axis=1), 2)
ps = np.power(np.sum(z * sin, axis=1), 2)
cs = pc / np.sum(np.power(cos, 2), axis=1)
ss = ps / np.sum(np.power(sin, 2), axis=1)
p = cs + ss
pwr = self.avevar(h)
nout = len(h)
p = p / (2 * pwr)
p = p / (nout / (2.0 * pwr))
return f, np.sqrt(p)
def lomb_for(self, t, h, ofac, hifac):
period = max(t) - min(t)
f = np.arange(1 / (period * ofac), hifac * len(h) / (2 * period), 1 / (period * ofac))
f = f[:int(len(f) / 2) + 1]
z = h - np.mean(h)
p = np.zeros(len(f))
for i in range(len(f)):
w = 2 * np.pi * f[i]
if w > 0:
twt = 2 * w * t
y = sum(np.sin(twt))
x = sum(np.cos(twt))
tau = math.atan2(y, x) / (2 * w)
wtmt = w * (t - tau)
cs = np.power(sum(np.multiply(z, np.cos(wtmt))), 2) / sum(np.power((np.cos(wtmt)), 2))
ss = np.power(sum(np.multiply(z, np.sin(wtmt))), 2) / sum(np.power((np.sin(wtmt)), 2))
p[i] = cs + ss
else:
p[i] = np.power(sum(np.multiply(z, t)), 1) / sum(np.power(t), 1)
pwr = self.avevar(h)
nout = len(h)
p = p / (2 * pwr)
p = p / (nout / (2.0 * pwr))
return f, np.sqrt(p)
def freq_domain(self, time, rr_intervals):
frequency, mag0 = self.lomb(time, rr_intervals, 4.0, 2.0)
frequency = np.round(frequency, 8)
mag0 = mag0 / 2.0
mag0 = np.round(mag0, 8)
result = self.power(frequency, mag0)
return result[0], result[1], result[2], result[3], result[0] + result[1] + result[2] + result[3], \
result[2] / result[3]
def time_domain(time, rr_intervals, ann):
sum_rr = 0.0
sum_rr2 = 0.0
rmssd = 0.0
totnn = 0
totnnn = 0
nrr = 1
totrr = 1
nnx = 0
nnn = 0
lastann = ann[0]
lastrr = int(rr_intervals[0])
lenght = 300
t = float(time[0])
end = t + lenght
i = 0
ratbuf = np.zeros(2400)
avbuf = np.zeros(2400)
sdbuf = np.zeros(2400)
for x in range(1, len(ann)):
t = float(time[x])
while t > (end+lenght):
i += 1
end += lenght
if t >= end:
if nnn > 1:
ratbuf[i] = nnn/nrr
sdbuf[i] = np.sqrt(((sdbuf[i] - avbuf[i]*avbuf[i]/nnn) / (nnn-1)))
avbuf[i] /= nnn
i += 1
nnn = nrr = 0
end += lenght
nrr += 1
totrr += 1
if ann[x] == 'N' and ann[x-1] == 'N':
rr_intervals[x] = int(rr_intervals[x])
nnn += 1
avbuf[i] += rr_intervals[x]
sdbuf[i] += (rr_intervals[x] * rr_intervals[x])
sum_rr += rr_intervals[x]
sum_rr2 += (rr_intervals[x] * rr_intervals[x])
totnn += 1
if lastann == 'N':
totnnn += 1
rmssd += (rr_intervals[x] - lastrr) * (rr_intervals[x] - lastrr)
# nndif[0] = NNDIF
if abs(rr_intervals[x] - lastrr) - 0.05 > (10 ** -10):
nnx += 1
lastann = ann[x-1]
lastrr = rr_intervals[x]
if totnn == 0:
return 0, 0, 0, 0
sdnn = np.sqrt((sum_rr2 - sum_rr * sum_rr / totnn) / (totnn - 1))
rmssd = np.sqrt(rmssd/totnnn)
pnn50 = nnx / totnnn
if nnn > 1:
ratbuf[i] = nnn / nrr
sdbuf[i] = np.sqrt((sdbuf[i] - avbuf[i] * avbuf[i] / nnn) / (nnn - 1))
avbuf[i] /= nnn
nb = i + 1
sum_rr = 0.0
sum_rr2 = 0.0
k = 0
h = 0
while k < nb:
if ratbuf[k] != 0:
h += 1
sum_rr += avbuf[k]
sum_rr2 += (avbuf[k] * avbuf[k])
k += 1
sdann = np.sqrt((sum_rr2 - sum_rr * sum_rr / h) / (h - 1))
return sdnn, sdann, rmssd, pnn50
def get_result_from_get_hrv(filename):
with open(filename, 'r') as f:
csv_reader = csv.reader(f, delimiter=',')
index = 0
for row in csv_reader:
if index > 0:
output = [s.strip() for s in row[0].split('=') if s]
# print('output = ', output)
if output[0] == 'SDNN':
sdnn = output[1]
if output[0] == 'SDANN':
sdann = output[1]
if output[0] == 'rMSSD':
rmssd = output[1]
if output[0] == 'pNN50':
pnn50 = output[1]
if output[0] == 'ULF PWR':
ulf = output[1]
if output[0] == 'VLF PWR':
vlf = output[1]
if output[0] == 'LF PWR':
lf = output[1]
if output[0] == 'HF PWR':
hf = output[1]
if output[0] == 'TOT PWR':
tp = output[1]
if output[0] == 'LF/HF':
ratio_lf_hf = output[1]
index += 1
return float(sdnn), float(sdann), float(rmssd), float(pnn50), float(ulf), float(vlf), \
float(lf), float(hf), float(tp), float(ratio_lf_hf)
def save_file():
extension = "atr"
result_all = []
file_process = ['File']
sdnn_l = ['sdnn']
sdann_l = ['sdann']
rmssd_l = ['rmssd']
pnn50_l = ['pnn50']
ulf_l = ['ulf']
vlf_l = ['vlf']
lf_l = ['lf']
hf_l = ['hf']
tp_l = ['tp']
ratio_lf_hf_l = ['ratio_lf_hf']
sdnn_l_p = ['sdnn']
sdann_l_p = ['sdann']
rmssd_l_p = ['rmssd']
pnn50_l_p = ['pnn50']
ulf_l_p = ['ulf']
vlf_l_p = ['vlf']
lf_l_p = ['lf']
hf_l_p = ['hf']
tp_l_p = ['tp']
ratio_lf_hf_l_p = ['ratio_lf_hf']
test_file = ['103', '113', '117', '121', '123', '200', '202', '210', '212', '213',
'219', '221', '213', '228', '231', '233', '234',
'101', '106', '108', '112', '114', '115', '116', '119', '122', '201', '203',
'205', '208', '209', '215', '220', '223', '230',
'105', '100']
file_dis = ['109', '111', '118', '124', '207', '214', '232']
for root, dirs, files in os.walk(DATA_PATH):
files = np.sort(files)
for name in files:
if extension in name:
if os.path.basename(name[:-4]) not in test_file:
continue
print('Processing file...', os.path.basename(name))
cur_dir = os.getcwd()
os.chdir(DATA_PATH)
os.system('rrlist {} {} -M -s >{}.rr'.format(extension, name.split('.')[0], name.split('.')[0]))
time_m = []
rr_intervals = []
ann = []
with open(name.split('.')[0] + '.rr', 'r') as rr_file:
for line in rr_file:
time_m.append(line.split(' ')[0])
rr_intervals.append(line.split(' ')[1])
ann.append(line.split(' ')[2].split('\n')[0])
time_m = np.asarray(time_m, dtype=float)
rr_intervals = np.asarray(rr_intervals, dtype=float)
sdnn, sdann, rmssd, pnn50 = time_domain(time_m, rr_intervals, ann)
if sdnn == 0 and sdann == 0 and rmssd == 0 and pnn50 == 0:
print('No result hrv')
file_dis.append(os.path.basename(name[:-4]))
continue
print('sdnn', sdnn)
print('rmssd', rmssd)
print('pnn50', pnn50)
print('sdann', sdann)
time_m = time_m - time_m[0]
time_m = np.round(time_m, 3)
time_nn = []
nn_intervals = []
for i in range(1, len(ann)):
if ann[i] == 'N' and ann[i - 1] == 'N':
nn_intervals.append(rr_intervals[i])
time_nn.append(time_m[i])
time_nn = np.asarray(time_nn, dtype=float)
nn_intervals = np.asarray(nn_intervals, dtype=float)
fc = FreqDomainClass()
ulf, vlf, lf, hf, tp, ratio_lf_hf = fc.freq_domain(time_nn, nn_intervals)
sdnn_l.append(sdnn)
sdann_l.append(sdann)
rmssd_l.append(rmssd)
pnn50_l.append(pnn50)
ulf_l.append(ulf)
vlf_l.append(vlf)
lf_l.append(lf)
hf_l.append(hf)
tp_l.append(tp)
ratio_lf_hf_l.append(ratio_lf_hf)
print('ULF PWR: ', ulf)
print('VLF PWR: ', vlf)
print('LF PWR: ', lf)
print('HF PWR: ', hf)
print('TOT PWR: ', tp)
print('LF/HF: ', ratio_lf_hf)
if os.path.exists('physionet_hrv.txt'):
os.remove('physionet_hrv.txt')
os.system('get_hrv -R ' + name.split('.')[0] + '.rr >> ' + 'physionet_hrv.txt')
sdnn, sdann, rmssd, pnn50, ulf, vlf, lf, hf, tp, ratio_lf_hf = \
get_result_from_get_hrv('physionet_hrv.txt')
file_process.append(os.path.basename(name[:-4]))
sdnn_l_p.append(sdnn)
sdann_l_p.append(sdann)
rmssd_l_p.append(rmssd)
pnn50_l_p.append(pnn50)
ulf_l_p.append(ulf)
vlf_l_p.append(vlf)
lf_l_p.append(lf)
hf_l_p.append(hf)
tp_l_p.append(tp)
ratio_lf_hf_l_p.append(ratio_lf_hf)
os.chdir(cur_dir)
result_all.append(file_process)
result_all.append(sdnn_l)
result_all.append(sdnn_l_p)
result_all.append(sdann_l)
result_all.append(sdann_l_p)
result_all.append(rmssd_l)
result_all.append(rmssd_l_p)
result_all.append(pnn50_l)
result_all.append(pnn50_l_p)
result_all.append(ulf_l)
result_all.append(ulf_l_p)
result_all.append(vlf_l)
result_all.append(vlf_l_p)
result_all.append(lf_l)
result_all.append(lf_l_p)
result_all.append(hf_l)
result_all.append(hf_l_p)
result_all.append(tp_l)
result_all.append(tp_l_p)
result_all.append(ratio_lf_hf_l)
result_all.append(ratio_lf_hf_l_p)
print(file_dis)
with open('hrv2.csv', 'w+') as f:
writer = csv.writer(f)
for values in zip_longest(*result_all):
writer.writerow(values)
def main():
extension = "atr"
for root, dirs, files in os.walk(DATA_PATH):
files = np.sort(files)
for name in files:
if extension in name:
if name not in ['101.atr']:
continue
cur_dir = os.getcwd()
os.chdir(DATA_PATH)
os.system('rrlist {} {} -M -s >{}.rr'.format(extension, name.split('.')[0], name.split('.')[0]))
time_m = []
rr_intervals = []
ann = []
with open(name.split('.')[0] + '.rr', 'r') as rr_file:
for line in rr_file:
time_m.append(line.split(' ')[0])
rr_intervals.append(line.split(' ')[1])
ann.append(line.split(' ')[2].split('\n')[0])
time_m = np.asarray(time_m, dtype=float)
rr_intervals = np.asarray(rr_intervals, dtype=float)
sdnn, sdann, rmssd, pnn50 = time_domain(time_m, rr_intervals, ann)
if sdnn == 0 and sdann == 0 and rmssd == 0 and pnn50 == 0:
print('No result hrv')
return 0
print('sdnn', sdnn)
print('rmssd', rmssd)
print('pnn50', pnn50)
print('sdann', sdann)
time_m = time_m - time_m[0]
time_m = np.round(time_m, 3)
time_nn = []
nn_intervals = []
for i in range(1, len(ann)):
if ann[i] == 'N' and ann[i - 1] == 'N':
nn_intervals.append(rr_intervals[i])
time_nn.append(time_m[i])
time_nn = np.asarray(time_nn, dtype=float)
nn_intervals = np.asarray(nn_intervals, dtype=float)
start = time.time()
fc = FreqDomainClass()
ulf, vlf, lf, hf, tp, ratio_lf_hf = fc.freq_domain(time_nn, nn_intervals)
end = time.time()
print('ULF PWR: ', ulf)
print('VLF PWR: ', vlf)
print('LF PWR: ', lf)
print('HF PWR: ', hf)
print('TOT PWR: ', tp)
print('LF/HF: ', ratio_lf_hf)
print('finish', end - start)
os.chdir(cur_dir)
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