#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
from biosppy import utils
import pandas as pd
def read_ecg(file,result):
""" Preprocesses an ECG signal.
Parameters
----------
file : numpy.ndarray
Raw ECG signal.
result : numpy.ndarray
Subject data extracted from the DataSet.csv file
Returns
-------
ID : numpy.ndarray
Age : numpy.ndarray
Weight: numpy.ndarray
Height:numpy.ndarray
Gender:numpy.ndarray
Observations field:numpy.ndarray
A1 : numpy.ndarray
ECG signal extracted from sensor A1 (with flat electrode texture).
A2 : numpy.ndarray
ECG signal extracted from sensor A2 (with sinusoidal electrode texture).
A3 : numpy.ndarray
ECG signal extracted from sensor A2 (with pyramidal electrode texture).
A4 : numpy.ndarray
ECG signal extracted from sensor A4 (with trapezoidal electrode texture).
"""
def convert_raw_mV(raw):
sig=list(map(int,(raw)))
sig=np.subtract(1024, sig)
sig=(np.divide(sig,1024.)-0.5)*(33/11)#Unit -mV
return sig
with open(file, "r") as f:
aux = f.readlines()
signal = np.loadtxt(file)
lista1=[str(x) for x in [int(x) for x in signal[:, 5]]]
A1=convert_raw_mV(lista1)
lista2=[str(x) for x in [int(x) for x in signal[:, 6]]]
A2=convert_raw_mV(lista2)
lista3=[str(x) for x in [int(x) for x in signal[:, 7]]]
A3=convert_raw_mV(lista3)
lista4=[str(x) for x in [int(x) for x in signal[:, 8]]]
A4=convert_raw_mV(lista4)
args = (
result[0][0],result[0][1],result[0][2],result[0][3],result[0][4],result[0][5],A1,A2,A3,A4)
names = (
"ID",
"Age",
"Weight ",
"Height",
"Gender",
"Observations_field",
"A1",
"A2",
"A3",
"A4"
)
return utils.ReturnTuple(args, names)
if __name__ == "__main__":
data_ecg=[]
folder='ECG_EXP'
df = pd.read_csv('DataSet.csv', sep=';')
ind_files=utils.walktree(r''+folder+'', r'\.txt$');
for i in ind_files:
result = df[df['ID'].astype(str) == (utils.fileparts(i)[1])].values
data_ecg.append(read_ecg(i,result))