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systolic.py
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systolic.py
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"""
This is a program which acts as a controller and interpreter for my ultra-low-cost ECG Systolic.
Copyright 2020 OskarCodes
This file is part of Systolic
Systolic is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Systolic is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with Systolic. If not, see <https://www.gnu.org/licenses/>.
"""
import sys
import time
import csv
from configparser import ConfigParser, NoOptionError, NoSectionError
from PyQt5 import QtWidgets, uic
from PyQt5.QtWidgets import QMessageBox
import matplotlib.pyplot as plt
import serial
import serial.tools.list_ports
import ecg_plot
import numpy as np
from tqdm import tqdm
from scipy import signal
from mathtools import mean_downscaler
# These are the two files for if the ADS1293's SDM is running at 204.8 kHz or at 102.4 kHz
# CSV_FILE = 'csv/sampling_1024.csv' # 102.4 kHz
CSV_FILE = 'csv/sampling_2048.csv' # 204.8 kHz
CONFIG_REG = "0x00"
R2_REG = "0x21"
R3CH1_REG = "0x22"
R3CH2_REG = "0x23"
R3CH3_REG = "0x24"
CM_REG = '0x0B'
RLD_REG = '0x0C'
AFE_REG = '0x13'
FILTER_REG = '0x26'
def __butter_filter(order, critical_freq, filter_type, sampling_freq, data):
"""
Butter filter with adjustable type, etc.
:param order: Filter order
:type order: int
:param critical_freq: Critical frequencies (-3 dB points)
:type critical_freq: scalar or sequence (len 2)
:param filter_type: Type of filter, e.g. 'lowpass', 'highpass', 'bandpass', etc.
:type filter_type: string
:param sampling_freq: Sampling frequency
:type sampling_freq: float
:param data: Input data to be filtered
:type data: array
:return: Filtered data
:rtype: array
"""
# Create butter filter with sos output
sos = signal.butter(order, critical_freq, btype=filter_type, output='sos', fs=sampling_freq)
# Apply sos parameters to input data
f_data = signal.sosfilt(sos, data)
# Return filtered data
return f_data
def pan_tompkins(waveform, sampling_freq, order=2, plot=False):
"""
:param plot: Should a graph of the filtered ECG data be produced?
:type plot: bool
:param waveform: Waveform data, Lead II is used
:type waveform: ndarray
:param sampling_freq: Sampling Frequency (Hz)
:type sampling_freq: float
:param order: Order of notch filter applied from 5-15 Hz
:type order: int
:return: Heart rate
:rtype: int
"""
# Here I attempt to implement the Pan–Tompkins algorithm, as shown in:
# https://en.wikipedia.org/wiki/Pan%E2%80%93Tompkins_algorithm
# It is not complete as of now, e.g. there is no threshold calculation as of now
# Use Lead II
waveform = waveform[1]
# Calculate sampling time
sample_time = len(waveform) / sampling_freq
# Firstly 5-15 Hz bandpass is applied
low = 5
high = 15
waveform_filt = __butter_filter(order, [low, high], 'bandpass', sampling_freq, waveform)
# Derivative filter
waveform_filt = np.gradient(waveform_filt)
# Square signal
waveform_filt = waveform_filt ** 2
# Calculate moving average
average_window = 0.15 # seconds
sample_amount = int(average_window * sampling_freq)
waveform_filt = mean_downscaler(waveform_filt, sample_amount)
"""
If point in moving average is greater than 0.4, then it is a beat.
Wait refractory period (approximately) Right now I've gone the lazy way
of just using a constant value to count as a beat, but in future I
will do it properly like discussed in the article I linked before.
"""
beats = 0
refractory = 0
# For plotting peak graph
x_vals = []
y_vals = []
for i, value in enumerate(waveform_filt):
if (i + 1) >= len(waveform_filt):
break
if value > 0 and waveform_filt[i + 1] <= value and value > 0.002:
x_vals.append(i)
y_vals.append(value)
beats += 1
refractory = i
# I can't exactly wait 200 ms, so I have to just skip 1
if i == (refractory + 1):
continue
heart_rate = round(beats / sample_time * 60)
if plot:
# Below is work in progress
# x_beats_on_normal = np.argsort(waveform)[::-1][:beats]
# y_beats_on_normal = list(map(lambda x: waveform[x], x_beats_on_normal))
plt.plot(waveform_filt)
plt.scatter(x_vals, y_vals, c='red', marker='x')
plt.show()
return heart_rate
def save_data(name, headers, data, sampling_rate):
"""
Saves ECG data to csv
:param name: File name for csv (include .csv)
:type name: string
:param headers: Headers for CSV (e.g. Lead I, Lead II, ...)
:type headers: list
:param data: ECG data
:type data: array
:param sampling_rate: Sampling rate
:type sampling_rate: float
"""
if data is None:
return
with open(name, 'wt', newline='') as csv_object:
csv_writer = csv.writer(csv_object, delimiter=',')
# Settings header
settings = ['sampling_rate', sampling_rate]
# Data headers
csv_writer.writerow(settings)
csv_writer.writerow(headers) # write header
cols_indices = np.arange(len(data[0]))
rows_indices = np.arange(len(data))
row_data = []
"""
I know this is overcomplicating a simple task of iterating over 6 rows, however
I wanted to do it this way just incase in future I wanted to call this function
with just three rows of data. It wouldn't be fun if the function didn't work then!
"""
for column_index in cols_indices:
for row_index in rows_indices:
row_data.append(data[row_index][column_index])
csv_writer.writerow(row_data)
row_data = []
def bin_to_hex(binary_in):
"""
Converts a binary input to a hexadecimal output
:param binary_in: Binary input
:type binary_in: string
:return: Hexadecimal output
:rtype: int
"""
hexb = hex(int(binary_in, 2))[2:]
hexb = hexb.zfill(2)
hexb = "0x" + hexb
# Returns a hex output
return hexb
def R2_to_Hex(R2_val):
"""
R2 Decimation filter input integer to output hexadecimal
"""
if R2_val == 4:
return bin_to_hex('00000001')
if R2_val == 5:
return bin_to_hex('00000010')
if R2_val == 6:
return bin_to_hex('00000100')
if R2_val == 8:
return bin_to_hex('00001000')
raise ValueError("Bad arguments")
def R3_to_Hex(R3_val):
"""
R3 Decimation filter input integer to output hexadecimal
"""
if R3_val == 4:
return bin_to_hex('00000001')
if R3_val == 6:
return bin_to_hex('00000010')
if R3_val == 8:
return bin_to_hex('00000100')
if R3_val == 12:
return bin_to_hex('00001000')
if R3_val == 16:
return bin_to_hex('00010000')
if R3_val == 32:
return bin_to_hex('00100000')
if R3_val == 64:
return bin_to_hex('01000000')
if R3_val == 128:
return bin_to_hex('10000000')
# Not good!
raise ValueError("Bad arguments")
def CM_to_Hex(bandwidth, drive):
"""
Common-mode (CM) drive input bool and integer to hexadecimal output
"""
binary = '00000'
if bandwidth:
binary = binary + '1'
else:
binary = binary + '0'
if drive == 0:
binary = binary + '00'
elif drive == 1:
binary = binary + '01'
elif drive == 2:
binary = binary + '10'
elif drive == 3:
binary = binary + '11'
return bin_to_hex(binary)
def RLD_to_Hex(toggle, bandwidth, drive):
"""
Right-leg-drive (RLD) integer and bool inputs to hexadecimal output
"""
binary = '0'
if bandwidth:
binary = binary + '1'
else:
binary = binary + '0'
if drive == 0:
binary = binary + '00'
elif drive == 1:
binary = binary + '01'
elif drive == 2:
binary = binary + '10'
elif drive == 3:
binary = binary + '11'
if toggle:
# Not shutdown
binary = binary + '0'
else:
# Shutdown
binary = binary + '1'
# Default to IN4
binary = binary + '100'
return bin_to_hex(binary)
def AFE_to_Hex(C1, C2, C3):
"""
Analog-front-end (AFE) bool inputs to hexadecimal output
"""
binary = '00'
# Default Clock
binary = binary + '000'
if C1:
binary = binary + '1'
else:
binary = binary + '0'
if C2:
binary = binary + '1'
else:
binary = binary + '0'
if C3:
binary = binary + '1'
else:
binary = binary + '0'
return bin_to_hex(binary)
def filter_to_hex(C1, C2, C3):
"""
Digital filter binary inputs to hexadecimal output
"""
binary = '00000'
if C3:
binary = binary + '0'
else:
binary = binary + '1'
if C2:
binary = binary + '0'
else:
binary = binary + '1'
if C1:
binary = binary + '0'
else:
binary = binary + '1'
return bin_to_hex(binary)
def send_data(register, raw_data, ser):
"""
Sends data to ECG in format 'register,data'
:param register: Register address
:type register: int (Hex)
:param raw_data: Data
:type raw_data: int (Hex)
:param ser: Serial object
:type ser: serial
"""
raw_data = str(raw_data)
register = str(register)
# Puts data into format as expected by the ECG
raw_data = register + "," + raw_data
# Adds newline to not cause any issues
data = raw_data + "\r\n"
# Encodes data and sends it to the ECG! Yay
ser.write(data.encode())
print("Sent: %s" % raw_data)
def has_numbers(input_string):
"""
This function returns a boolean representing if the input string contains a number
This is used in the ECG reading process, and is probably overcomplicating it.
:param input_string: The input string
:type input_string: string
:return: Boolean representing if input has numbers
:rtype: bool
"""
return any(char.isdigit() for char in input_string)
def adc_voltage(raw_data, adc_max=0x800000):
"""
Function returns the analog voltage value converted from the digital received value
:param raw_data: digital output
:type raw_data: string
:param adc_max: This value is from the lookup table
:type adc_max: int
:return:
:rtype:
"""
try:
raw_data = (float(raw_data) / adc_max)
except ValueError:
# This often occurs with just the first piece of data.
# No real way I can fix it right now.
return 0
# Calculated voltage as shown by equation in ADS1293 datasheet (page 36 or 8.4.3):
# https://www.ti.com/lit/gpn/ads1293
raw_data -= (1 / 2)
raw_data *= 4.8
raw_data /= 3.5
return raw_data
def ecg_read(adc_max, ser, data_limit):
"""
Reads data from ECG
:param adc_max: Value used to calculate voltage from adc output
:type adc_max: int (Hex)
:param ser: Serial object
:type ser: serial
:param data_limit: Amount of data to receive
:type data_limit: integer
"""
data_limit = round(data_limit)
run_enable = True
# Prepares array for reading
y_vals = np.empty([6, data_limit])
# Sends sampling start command
send_data(CONFIG_REG, bin_to_hex('00000001'), ser)
# Need to consider if this sleep below is actually needed
time.sleep(1)
ser.reset_input_buffer()
start = time.time()
for i in tqdm(range(0, data_limit)):
# run_enable probably isn't needed
while run_enable:
data_to_read = ser.inWaiting()
data = ser.read(data_to_read)
data = data.decode('utf-8')
data = data.strip()
if has_numbers(data):
try:
data = data.split(",")
except Exception as what_went_wrong:
print(what_went_wrong)
break
data[0] = adc_voltage(data[0], adc_max)
data[1] = adc_voltage(data[1], adc_max)
data[2] = adc_voltage(data[2], adc_max)
y_vals[0][i] = data[0]
y_vals[1][i] = data[1]
y_vals[2][i] = data[2]
break
end = time.time()
data_amount = len(y_vals[0])
delta_time = end - start
sampling_rate = data_amount / delta_time
# Definitely not needed, but good for testing!
print(f"Time taken = {delta_time}")
print(f"Time per sample = {delta_time / sampling_rate}")
print(f"Sampling rate = {sampling_rate}")
# Sends sampling stop command
send_data(CONFIG_REG, bin_to_hex('00000000'), ser)
# Calculates average of each of the three basic leads
average_i = np.average(y_vals[0])
average_ii = np.average(y_vals[1])
average_iii = np.average(y_vals[2])
for i in range(0, data_limit):
# Subtracts average from each point in lead
y_vals[0][i] = (y_vals[0][i] - average_i) * pow(10, 3)
y_vals[1][i] = (y_vals[1][i] - average_ii) * pow(10, 3)
y_vals[2][i] = (y_vals[2][i] - average_iii) * pow(10, 3)
# Calculates augmented leads
y_vals[3][i] = -1 * (float(y_vals[0][i]) + float(y_vals[1][i])) / 2 # aVR
y_vals[4][i] = (float(y_vals[0][i]) - float(y_vals[1][i])) / 2 # aVL
y_vals[5][i] = (float(y_vals[1][i]) - float(y_vals[0][i])) / 2 # aVF
# Same process as before, although I wonder if I can condense both while loops into one
average_aVR = np.average(y_vals[3])
average_aVL = np.average(y_vals[4])
average_aVF = np.average(y_vals[5])
for i in range(0, data_limit):
y_vals[3][i] = y_vals[3][i] - average_aVR
y_vals[4][i] = y_vals[4][i] - average_aVL
y_vals[5][i] = y_vals[5][i] - average_aVF
# Sampling frequency (Hz), set from calculated value
samp_freq = sampling_rate
# Frequency to be removed from signal (Hz) in notch filter
notch_freq = 50.0 # For usage in areas with 50 Hz mains power
# notch_freq = 60.0 # For usage in areas with 60 Hz mains power
# Quality factor of notch filter, not really sure what this does...
quality_factor = 30.0
#TODO: See if I can get sos output for iirnotch instead of b,a
b_notch, a_notch = signal.iirnotch(notch_freq, quality_factor, samp_freq)
# Notch filter applied to all 6 leads at previously set frequency
y_vals[0] = signal.filtfilt(b_notch, a_notch, y_vals[0])
y_vals[1] = signal.filtfilt(b_notch, a_notch, y_vals[1])
y_vals[2] = signal.filtfilt(b_notch, a_notch, y_vals[2])
y_vals[3] = signal.filtfilt(b_notch, a_notch, y_vals[3])
y_vals[4] = signal.filtfilt(b_notch, a_notch, y_vals[4])
y_vals[5] = signal.filtfilt(b_notch, a_notch, y_vals[5])
return y_vals, samp_freq
def view_data(waveforms, sampling_rate, title='ECG 6 Lead'):
"""
Displays ECG data using the awesome ecg-plot package
:param waveforms: ECG Data
:type waveforms: array
:param sampling_rate: Sampling rate
:type sampling_rate: float
:param title: Title of plot
:type title: string
"""
# Uses the awesome ecg-plot library to display the waveforms
ecg_plot.plot(waveforms, sample_rate=sampling_rate, title=title, columns=2)
ecg_plot.show()
def value_lookup(bandwidth):
"""
Looks for corresponding values in lookup table when given a bandwidth value
:param bandwidth: Input val
:type bandwidth: string
:return: R2, R3, adc_max, odr, noise
:rtype: string, string, string, string, string
"""
with open(CSV_FILE, newline='') as parameters:
read = csv.reader(parameters, delimiter=',', quotechar='"')
header = True
for row in read:
if header:
header = False
continue
if row[4] == bandwidth:
return row[0], row[1], row[2], row[3], row[6]
return None, None, None, None, None
class _ECGWindow(QtWidgets.QMainWindow):
def __init__(self):
super().__init__()
uic.loadUi("mainwindow.ui", self)
# So many things to initialize!
self.noiseline.setReadOnly(True)
self.ODRline.setReadOnly(True)
self.statusLine.setReadOnly(True)
self.heartrateLine.setReadOnly(True)
self.viewButton.setEnabled(False)
self.saveButton.setEnabled(False)
self.analysisButton.setEnabled(False)
self.statusLine.setText("Disconnected")
self.startButton.clicked.connect(self.start_sampling)
self.paramButton.clicked.connect(self.set_param)
self.refreshButton.clicked.connect(self.refresh_com)
self.conButton.clicked.connect(self.connect)
self.stopButton.clicked.connect(self.stop)
self.saveButton.clicked.connect(lambda: save_data('sample.csv', self.headers,
self.waveforms,
self.sampling_rate))
self.viewButton.clicked.connect(lambda: view_data(self.waveforms, self.sampling_rate))
self.loadButton.clicked.connect(self.load_data)
self.analysisButton.clicked.connect(self.analysis)
self.samplingline.textChanged.connect(self.update_var)
self.samplingrline.currentTextChanged.connect(self.update_var)
self.conn_state(0)
# USED TO DETERMINE UNSAVED CHANGES
self.updated = 0
# CONNECTION PARAMETERS
self.port = 0
self.baud = 115200
self.ser = None
self.connected = 0
# ECG READ DATA & FUNCTIONS
self.waveforms = []
self.sampling_rate = 0
self.heart_rate = 0
self.headers = ['Lead I', 'Lead II', 'Lead III', 'aVR', 'aVL', 'aVF']
# SAMPLING PARAMETERS - USER SET. BELOW ARE THE DEFAULTS
self.bandwidth = 160
self.time = "5"
# ADJUSTED BASED ON BANDWIDTH AND TIME SETTINGS
self.R2 = 0x01
self.R3 = 0x02
self.points = 300
self.adc_max = "0x800000"
self.odr = 0
self.noise = 0
self.odr_arr = []
# MISCELLANEOUS PARAMETERS
self.config_name = 'config.ini'
# SETS TAB TO CONNECTION PAGE, FOR IF THE UI FILE IS SAVED AS TO HAVE ANOTHER TAB AS DEFAULT
self.Tabs.setCurrentIndex(2)
# FINAL FUNCTIONS TO SETUP WINDOW
self.populate_band()
self.refresh_com()
self.config = ConfigParser()
self.load_config()
def analysis(self):
"""
Wrapper for analysis functions, only contains heart rate calculation currently.
"""
self.heart_rate = pan_tompkins(self.waveforms, self.sampling_rate, plot=True)
self.heartrateLine.setText("%s bpm" % self.heart_rate)
def load_data(self):
"""
Loads a selected .csv file into the ECG Window
"""
# Temporary filepath for my testing
path = 'cardiacwaveforms.csv'
with open(path, newline='') as csvfile:
data_reader = csv.reader(csvfile, delimiter=',', quotechar='|')
for i, row in enumerate(data_reader):
if i == 0:
# Sampling settings
self.sampling_rate = float(row[1])
continue
if i == 1:
# Headers
continue
row = list(map(float, row))
self.waveforms.append(row)
self.waveforms = np.array(self.waveforms)
# Transpose array as CSV data isn't in the preferred format
self.waveforms = self.waveforms.T
print("Data read")
self.viewButton.setEnabled(True)
self.analysisButton.setEnabled(True)
def init_config(self):
"""
Creates the config file, and deletes the existing one if possible
"""
open(self.config_name, 'w').close()
self.config = ConfigParser()
self.config.read(self.config_name)
self.config.add_section('main')
self.config.set('main', 'bandwidth', str(self.bandwidth))
self.config.set('main', 'time', str(self.time))
with open('config.ini', 'w') as config_file:
self.config.write(config_file)
def load_config(self):
"""
Loads an existing config file, and creates a new one if not possible.
"""
data = self.config.read(self.config_name)
if len(data) == 0:
self.init_config()
else:
try:
self.bandwidth = self.config.get('main', 'bandwidth')
self.time = self.config.get('main', 'time')
except NoSectionError:
self.init_config()
except NoOptionError:
self.init_config()
finally:
self.samplingline.clear()
self.samplingline.insert(self.time)
index = np.where(np.array(self.odr_arr) == self.bandwidth)
self.samplingrline.setCurrentIndex(int(index[0]))
self.set_param()
def conn_state(self, num):
"""
Updates the ECG Window based on the connection status
:param num: A boolean representing the connection state
:type num: bool
"""
if num == 0:
self.statusLine.setText("Disconnected")
else:
self.statusLine.setText("Connected")
self.Tabs.setTabEnabled(1, num)
self.connected = num
def connect(self):
"""
Connects or disconnects this program to Systolic
"""
self.port = self.comSel.currentData()
if self.port is None or self.port == 0:
return
if self.connected == 1:
try:
self.ser.close()
self.conn_state(False)
return
except serial.SerialException as exception:
print(exception)
self.conn_state(False)
try:
self.ser = serial.Serial(str(self.port), self.baud) # open serial port
self.conn_state(True)
except serial.SerialException as exception:
error = QMessageBox()
error.setIcon(QMessageBox.Warning)
error.setText("An error occurred when trying to connect.")
error.setWindowTitle("Systolic")
error.setDetailedText(f"{exception}")
error.exec_()
self.conn_state(True)
return
def refresh_com(self):
"""
Refreshes the serial devices list on the window
"""
self.comSel.clear()
avail_ports = serial.tools.list_ports.comports()
for port, desc, _ in sorted(avail_ports):
self.comSel.addItem(desc, port)
def update_var(self):
"""
A function I just soley for updating the updated variable (haha)
"""
self.updated = 1
def populate_band(self):
"""
Populate the bandwidth dropdown with values from the csv lookup table
"""
with open(CSV_FILE, newline='') as parameters:
read = csv.reader(parameters, delimiter=',', quotechar='"')
start = False
last = 0
for row in read:
if not start:
start = True
continue
if row[4] == last:
continue
last = row[4]
self.odr_arr.append(row[4])
self.samplingrline.addItem(row[4] + " Hz", row[4])
def set_param(self):
"""
Gets the sampling parameters from the user's inputted values, and then writes them to config
"""
self.updated = 0
self.time = self.samplingline.text()
self.bandwidth = self.samplingrline.currentData()
self.R2, self.R3, self.adc_max, self.odr, self.noise = value_lookup(self.bandwidth)
self.points = int(self.time) * int(self.odr)
self.R2 = R2_to_Hex(float(self.R2))
self.R3 = R3_to_Hex(float(self.R3))
self.noiseline.setText("%s uV" % self.noise)
self.ODRline.setText("%s Hz" % self.odr)
self.config.set('main', 'bandwidth', str(self.bandwidth))
self.config.set('main', 'time', str(self.time))
with open(self.config_name, 'w') as config_file:
self.config.write(config_file)
def stop(self):
"""
Stops sampling of the ECG by sending stop command
"""
send_data(CONFIG_REG, bin_to_hex('00000000'), self.ser)
def start_sampling(self):
"""
Starts sampling of the ECG by sending start command.
Then it initiates data receiving
"""
print(self.updated)
if self.updated == 1:
ret = QMessageBox.question(self, 'Warning',
"You have modified your sampling parameters but have not set them. Continue?",
QMessageBox.Yes | QMessageBox.No)
if ret == QMessageBox.No:
return
print("ECG Measurement Init")
self.upload()
self.waveforms, self.sampling_rate = ecg_read(int(self.adc_max, 16), self.ser, int(self.points))
self.viewButton.setEnabled(True)
self.saveButton.setEnabled(True)
self.analysisButton.setEnabled(True)
view_data(self.waveforms, self.sampling_rate)
# Move user to sample tab
self.Tabs.setCurrentIndex(0)
self.analysis()
def upload(self):
"""
Uploads sampling parameters to Systolic
"""
print("Uploading decimation rates R2: %s R3: %s" % (self.R2, self.R3))
send_data(R2_REG, self.R2, self.ser)
send_data(R3CH1_REG, self.R3, self.ser)
send_data(R3CH2_REG, self.R3, self.ser)
send_data(R3CH3_REG, self.R3, self.ser)
if __name__ == '__main__':
app = QtWidgets.QApplication(sys.argv)
window = _ECGWindow()
window.show()
sys.exit(app.exec())