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PayalLakraPayalLakra
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‎applications/ecgg.py

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# import sys
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# import numpy as np
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# import time
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# from pylsl import StreamInlet, resolve_stream
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# from scipy.signal import butter, lfilter, find_peaks
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# import pyqtgraph as pg # For real-time plotting
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# from pyqtgraph.Qt import QtWidgets, QtCore # PyQt components for GUI
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# import signal # For handling Ctrl+C
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# from collections import deque # For creating a ring buffer
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# # Initialize global variables
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# inlet = None
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# data_buffer = np.zeros(2000) # Buffer to hold the last 2000 samples for ECG data
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# # Function to design a Butterworth filter
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# def butter_filter(cutoff, fs, order=4, btype='low'):
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# nyquist = 0.5 * fs # Nyquist frequency
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# normal_cutoff = cutoff / nyquist
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# b, a = butter(order, normal_cutoff, btype=btype, analog=False)
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# return b, a
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# # Apply the Butterworth filter to the data
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# def apply_filter(data, b, a):
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# return lfilter(b, a, data)
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# # Function to detect heartbeats using peak detection
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# def detect_heartbeats(ecg_data, sampling_rate):
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# peaks, _ = find_peaks(ecg_data, distance=sampling_rate * 0.6, prominence=0.5) # Adjust as necessary
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# return peaks
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# class DataCollector(QtCore.QThread):
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# data_ready = QtCore.pyqtSignal(np.ndarray)
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# def __init__(self):
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# super().__init__()
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# self.running = True
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# self.sampling_rate = None
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# def run(self):
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# global inlet
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# print("Looking for LSL stream...")
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# streams = resolve_stream('name', 'BioAmpDataStream')
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# if not streams:
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# print("No LSL Stream found! Exiting...")
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# sys.exit(0)
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# inlet = StreamInlet(streams[0])
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# self.sampling_rate = inlet.info().nominal_srate()
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# print(f"Detected sampling rate: {self.sampling_rate} Hz")
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# # Create and design filters
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# low_cutoff = 20.0 # 20 Hz low-pass filter
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# self.low_b, self.low_a = butter_filter(low_cutoff, self.sampling_rate, order=4, btype='low')
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# while self.running:
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# # Pull multiple samples at once
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# samples, _ = inlet.pull_chunk(timeout=0.0, max_samples=10) # Pull up to 10 samples
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# if samples:
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# global data_buffer
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# data_buffer = np.roll(data_buffer, -len(samples)) # Shift data left
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# data_buffer[-len(samples):] = [sample[0] for sample in samples] # Add new samples to the end
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# filtered_data = apply_filter(data_buffer, self.low_b, self.low_a) # Low-pass Filter
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# self.data_ready.emit(filtered_data) # Emit the filtered data for plotting
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# time.sleep(0.01)
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# def stop(self):
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# self.running = False
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# class ECGApp(QtWidgets.QMainWindow):
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# def __init__(self):
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# super().__init__()
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# # Create a plot widget
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# self.plot_widget = pg.PlotWidget(title="ECG Signal")
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# self.setCentralWidget(self.plot_widget)
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# self.plot_widget.setBackground('w')
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# # Create a label to display heart rate
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# self.heart_rate_label = QtWidgets.QLabel("Heart rate: - bpm", self)
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# self.heart_rate_label.setStyleSheet("font-size: 20px; font-weight: bold;")
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# self.heart_rate_label.setAlignment(QtCore.Qt.AlignCenter)
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# layout = QtWidgets.QVBoxLayout()
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# layout.addWidget(self.plot_widget)
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# layout.addWidget(self.heart_rate_label)
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# container = QtWidgets.QWidget()
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# container.setLayout(layout)
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# self.setCentralWidget(container)
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# self.ecg_buffer = [] # Buffer to hold the ECG data
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# self.r_peak_times = deque(maxlen=10) # Store up to 20 R-peaks
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# self.last_update_time = time.time()
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# self.data_collector = DataCollector() # Data collector thread
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# self.data_collector.data_ready.connect(self.update_plot)
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# self.data_collector.start()
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# self.time_axis = np.linspace(0, 2000 / 200, 2000) # Store the x-axis time window
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# self.plot_widget.setYRange(0, 700) # Set fixed y-axis limits
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# def update_plot(self, ecg_data):
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# self.ecg_buffer = ecg_data # Update buffer
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# self.plot_widget.clear()
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# # Set a fixed window (time axis) to ensure stable plotting
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# self.plot_widget.plot(self.time_axis, self.ecg_buffer, pen='#000000') # Plot ECG data with black line
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# self.plot_widget.setXRange(self.time_axis[0], self.time_axis[-1], padding=0)
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# # Detect heartbeats in real time
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# heartbeats = detect_heartbeats(np.array(self.ecg_buffer), self.data_collector.sampling_rate)
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# # Mark detected R-peaks
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# for index in heartbeats:
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# time_point = index / self.data_collector.sampling_rate # Convert index to time
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# self.r_peak_times.append(time_point) # Store the time of the detected R-peak
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# # Plot a red circle at the R-peak position
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# self.plot_widget.plot([self.time_axis[index]], [self.ecg_buffer[index]], pen=None, symbol='o', symbolBrush='r', symbolSize=8)
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# self.calculate_heart_rate() # Calculate heart rate after detecting R-peaks
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# def calculate_heart_rate(self):
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# current_time = time.time()
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# if current_time - self.last_update_time >= 10: # Update every 10 seconds
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# if len(self.r_peak_times) > 1:
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# # Calculate the time intervals between successive R-peaks
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# intervals = np.diff(self.r_peak_times)
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# valid_intervals = intervals[intervals > 0] # Filter positive intervals
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# if len(valid_intervals) > 0:
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# bpm = 60 / np.mean(valid_intervals) # Mean interval is in seconds, converting to bpm
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# self.heart_rate_label.setText(f"Heart rate: {bpm:.2f} bpm")
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# else:
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# self.heart_rate_label.setText("Heart rate: 0 bpm")
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# else:
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# self.heart_rate_label.setText("Heart rate: 0 bpm")
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# self.r_peak_times.clear() # Clear the deque after calculation
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# self.last_update_time = current_time # Update last update time
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# def closeEvent(self, event):
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# self.data_collector.stop() # Stop the data collector thread on close
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# self.data_collector.wait() # Wait for the thread to finish
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# event.accept() # Accept the close event
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# def signal_handler(sig, frame):
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# print("Exiting...")
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# QtWidgets.QApplication.quit()
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# if __name__ == "__main__":
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# signal.signal(signal.SIGINT, signal_handler) # Handle Ctrl+C
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# streams = resolve_stream('name', 'BioAmpDataStream')
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# if not streams:
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# print("No LSL Stream found! Exiting...")
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# sys.exit(0)
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# app = QtWidgets.QApplication(sys.argv)
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# window = ECGApp()
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# window.setWindowTitle("Real-Time ECG Monitoring")
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# window.resize(800, 600)
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# window.show()
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# sys.exit(app.exec_())
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import sys
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import numpy as np
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import time
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from pylsl import StreamInlet, resolve_stream
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from scipy.signal import butter, lfilter, find_peaks
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import pyqtgraph as pg # For real-time plotting
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from pyqtgraph.Qt import QtWidgets, QtCore # PyQt components for GUI
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import signal # For handling Ctrl+C
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from collections import deque # For creating a ring buffer
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# Initialize global variables
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inlet = None
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data_buffer = np.zeros(2000) # Buffer to hold the last 2000 samples for ECG data
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# Function to design a Butterworth filter
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def butter_filter(cutoff, fs, order=4, btype='low'):
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nyquist = 0.5 * fs # Nyquist frequency
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normal_cutoff = cutoff / nyquist
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b, a = butter(order, normal_cutoff, btype=btype, analog=False)
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return b, a
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# Apply the Butterworth filter to the data
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def apply_filter(data, b, a):
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return lfilter(b, a, data)
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# Function to detect heartbeats using peak detection
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def detect_heartbeats(ecg_data, sampling_rate):
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peaks, _ = find_peaks(ecg_data, distance=sampling_rate * 0.6, prominence=0.5) # Adjust as necessary
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return peaks
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class DataCollector(QtCore.QThread):
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data_ready = QtCore.pyqtSignal(np.ndarray)
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def __init__(self):
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super().__init__()
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self.running = True
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self.sampling_rate = None
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def run(self):
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global inlet
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print("Looking for LSL stream...")
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streams = resolve_stream('name', 'BioAmpDataStream')
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if not streams:
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print("No LSL Stream found! Exiting...")
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sys.exit(0)
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inlet = StreamInlet(streams[0])
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self.sampling_rate = inlet.info().nominal_srate()
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print(f"Detected sampling rate: {self.sampling_rate} Hz")
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# Create and design filters
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low_cutoff = 20.0 # 20 Hz low-pass filter
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self.low_b, self.low_a = butter_filter(low_cutoff, self.sampling_rate, order=4, btype='low')
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while self.running:
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# Pull multiple samples at once
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samples, _ = inlet.pull_chunk(timeout=0.0, max_samples=10) # Pull up to 10 samples
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if samples:
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global data_buffer
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data_buffer = np.roll(data_buffer, -len(samples)) # Shift data left
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data_buffer[-len(samples):] = [sample[0] for sample in samples] # Add new samples to the end
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filtered_data = apply_filter(data_buffer, self.low_b, self.low_a) # Low-pass Filter
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self.data_ready.emit(filtered_data) # Emit the filtered data for plotting
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time.sleep(0.01)
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def stop(self):
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self.running = False
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class HeartRateCalculator(QtCore.QThread):
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heart_rate_ready = QtCore.pyqtSignal(float)
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def __init__(self):
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super().__init__()
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self.running = True
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self.r_peak_times = deque(maxlen=20) # Store R-peaks times
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self.last_update_time = time.time()
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def run(self):
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while self.running:
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time.sleep(1) # Check every second
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current_time = time.time()
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if current_time - self.last_update_time >= 10: # Calculate heart rate every 10 seconds
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if len(self.r_peak_times) > 1:
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# Calculate the time intervals between successive R-peaks
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intervals = np.diff(self.r_peak_times)
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valid_intervals = intervals[intervals > 0] # Filter positive intervals
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if len(valid_intervals) > 0:
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bpm = 60 / np.mean(valid_intervals) # Mean interval is in seconds, converting to bpm
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self.heart_rate_ready.emit(bpm)
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else:
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self.heart_rate_ready.emit(0) # No valid intervals, heart rate is 0
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else:
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self.heart_rate_ready.emit(0) # Not enough R-peaks to calculate heart rate
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self.r_peak_times.clear() # Clear R-peaks after calculation
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self.last_update_time = current_time # Update last update time
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def add_r_peak_time(self, time):
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self.r_peak_times.append(time) # Add R-peak time to the deque
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def stop(self):
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self.running = False
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class ECGApp(QtWidgets.QMainWindow):
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def __init__(self):
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super().__init__()
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# Create a plot widget
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self.plot_widget = pg.PlotWidget(title="ECG Signal")
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self.setCentralWidget(self.plot_widget)
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self.plot_widget.setBackground('w')
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# Create a label to display heart rate
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self.heart_rate_label = QtWidgets.QLabel("Heart rate: - bpm", self)
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self.heart_rate_label.setStyleSheet("font-size: 20px; font-weight: bold;")
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self.heart_rate_label.setAlignment(QtCore.Qt.AlignCenter)
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layout = QtWidgets.QVBoxLayout()
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layout.addWidget(self.plot_widget)
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layout.addWidget(self.heart_rate_label)
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container = QtWidgets.QWidget()
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container.setLayout(layout)
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self.setCentralWidget(container)
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self.ecg_buffer = [] # Buffer to hold the ECG data
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self.data_collector = DataCollector() # Data collector thread
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self.data_collector.data_ready.connect(self.update_plot)
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self.data_collector.start()
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self.heart_rate_calculator = HeartRateCalculator() # Heart rate calculation thread
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self.heart_rate_calculator.start()
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self.heart_rate_calculator.heart_rate_ready.connect(self.update_heart_rate)
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self.time_axis = np.linspace(0, 2000 / 200, 2000) # Store the x-axis time window
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self.plot_widget.setYRange(0, 700) # Set fixed y-axis limits
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def update_plot(self, ecg_data):
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self.ecg_buffer = ecg_data # Update buffer
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self.plot_widget.clear()
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# Set a fixed window (time axis) to ensure stable plotting
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self.plot_widget.plot(self.time_axis, self.ecg_buffer, pen='#000000') # Plot ECG data with black line
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self.plot_widget.setXRange(self.time_axis[0], self.time_axis[-1], padding=0)
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# Detect heartbeats in real time
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heartbeats = detect_heartbeats(np.array(self.ecg_buffer), self.data_collector.sampling_rate)
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# Mark detected R-peaks and store in HeartRateCalculator
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for index in heartbeats:
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time_point = index / self.data_collector.sampling_rate # Convert index to time
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self.heart_rate_calculator.add_r_peak_time(time_point) # Store the time of the detected R-peak
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# Plot a red circle at the R-peak position
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self.plot_widget.plot([self.time_axis[index]], [self.ecg_buffer[index]], pen=None, symbol='o', symbolBrush='r', symbolSize=8)
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def update_heart_rate(self, bpm):
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if bpm > 0:
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self.heart_rate_label.setText(f"Heart rate: {bpm:.2f} bpm")
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else:
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self.heart_rate_label.setText("Heart rate: 0 bpm")
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def closeEvent(self, event):
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self.data_collector.stop() # Stop the data collector thread on close
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self.data_collector.wait() # Wait for the thread to finish
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self.heart_rate_calculator.stop() # Stop the heart rate calculator
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self.heart_rate_calculator.wait() # Wait for the thread to finish
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event.accept() # Accept the close event
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def signal_handler(sig, frame):
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print("Exiting...")
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QtWidgets.QApplication.quit()
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if __name__ == "__main__":
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signal.signal(signal.SIGINT, signal_handler) # Handle Ctrl+C
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streams = resolve_stream('name', 'BioAmpDataStream')
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if not streams:
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print("No LSL Stream found! Exiting...")
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sys.exit(0)
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app = QtWidgets.QApplication(sys.argv)
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window = ECGApp()
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window.setWindowTitle("Real-Time ECG Monitoring")
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window.resize(800, 600)
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window.show()
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sys.exit(app.exec_())

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