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lorforlinuxlorforlinux
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Merge pull request #16 from PayalLakra/bio_amptool
ffteeg and emgenvelope
2 parents 51395fd + 06fd1ad commit 6963895

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+250
-3
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4 files changed

+250
-3
lines changed

‎app_requirements.txt

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pyqtgraph==0.13.7
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PyQt5==5.15.11
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PySide2==5.15.2.1
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keyboard==0.13.5
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scipy==1.14.1

‎applications/emgenvelope.py

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import numpy as np
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from scipy.signal import butter, filtfilt
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from PyQt5.QtWidgets import QApplication, QVBoxLayout, QMainWindow, QWidget
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from pyqtgraph import PlotWidget
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import pyqtgraph as pg
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import pylsl
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import sys
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class EMGMonitor(QMainWindow):
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def __init__(self):
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super().__init__()
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self.setWindowTitle("Real-Time EMG Monitor with EMG Envelope")
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self.setGeometry(100, 100, 800, 600)
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self.plot_widget = PlotWidget(self)
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self.plot_widget.setBackground('w')
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self.plot_widget.showGrid(x=True, y=True)
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layout = QVBoxLayout()
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layout.addWidget(self.plot_widget)
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central_widget = QWidget()
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central_widget.setLayout(layout)
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self.setCentralWidget(central_widget)
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# Set up LSL stream inlet
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streams = pylsl.resolve_stream('name', 'BioAmpDataStream')
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if not streams:
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print("No LSL stream found!")
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sys.exit(0)
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self.inlet = pylsl.StreamInlet(streams[0])
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# Sampling rate
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self.sampling_rate = int(self.inlet.info().nominal_srate())
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print(f"Sampling rate: {self.sampling_rate} Hz")
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# Data and buffers
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self.buffer_size = self.sampling_rate * 10 # Fixed-size buffer for 10 seconds
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self.emg_data = np.zeros(self.buffer_size) # Fixed-size array for circular buffer
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self.time_data = np.linspace(0, 10, self.buffer_size) # Fixed time array for plotting
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self.current_index = 0 # Index for overwriting data
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self.b, self.a = butter(4, 70.0 / (0.5 * self.sampling_rate), btype='high')
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# Moving RMS window size (50 for 250 sampling rate and 100 for 500 sampling rate)
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self.rms_window_size = int(0.1 * self.sampling_rate)
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# Set fixed axis ranges
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self.plot_widget.setXRange(0, 10, padding=0)
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# Set y-axis limits based on sampling rate
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if self.sampling_rate == 250:
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self.plot_widget.setYRange(400,600 ,padding=0) # for R3 & ensuring no extra spaces at end
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elif self.sampling_rate == 500:
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self.plot_widget.setYRange(400, 10000,padding=0) # for R4 & ensuring no extra spaces at end
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# Plot curves for EMG data and envelope
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self.emg_curve = self.plot_widget.plot(self.time_data, self.emg_data, pen=pg.mkPen('b', width=1))
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self.envelope_curve = self.plot_widget.plot(self.time_data, self.emg_data, pen=pg.mkPen('r', width=2))
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# Timer for plot update
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self.timer = pg.QtCore.QTimer()
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self.timer.timeout.connect(self.update_plot)
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self.timer.start(15)
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def calculate_moving_rms(self, signal, window_size):
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# Calculate RMS using a moving window
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rms = np.sqrt(np.convolve(signal**2, np.ones(window_size) / window_size, mode='valid'))
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return np.pad(rms, (len(signal) - len(rms), 0), 'constant')
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def update_plot(self):
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samples, _ = self.inlet.pull_chunk(timeout=0.0, max_samples=30)
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if samples:
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for sample in samples:
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# Overwrite the oldest data point in the buffer
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self.emg_data[self.current_index] = sample[0]
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self.current_index = (self.current_index + 1) % self.buffer_size # Circular increment
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# Filter the EMG data
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filtered_emg = filtfilt(self.b, self.a, self.emg_data)
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# print(filtered_emg)
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# Take absolute value before calculating RMS envelope
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abs_filtered_emg = np.abs(filtered_emg)
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# print(abs_filtered_emg)
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# Calculate the RMS envelope
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rms_envelope = self.calculate_moving_rms(abs_filtered_emg, self.rms_window_size)
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# Update curves
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self.emg_curve.setData(self.time_data, filtered_emg) # Plot filtered EMG in blue
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self.envelope_curve.setData(self.time_data, rms_envelope) # Plot EMG envelope in red
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if __name__ == "__main__":
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app = QApplication(sys.argv)
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window = EMGMonitor()
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window.show()
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sys.exit(app.exec_())

‎applications/ffteeg.py

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import numpy as np
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from numpy import hamming
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from PyQt5.QtWidgets import QApplication, QVBoxLayout, QHBoxLayout, QMainWindow, QWidget
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from PyQt5.QtCore import Qt
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from pyqtgraph import PlotWidget
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import pyqtgraph as pg
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import pylsl
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import sys
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from scipy.signal import butter, filtfilt
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from scipy.fft import fft
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class EEGMonitor(QMainWindow):
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def __init__(self):
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super().__init__()
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self.setWindowTitle("Real-Time EEG Monitor with FFT and Brainwave Power")
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self.setGeometry(100, 100, 1200, 800)
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# Main layout split into two halves: top for EEG, bottom for FFT and Brainwaves
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self.central_widget = QWidget()
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self.main_layout = QVBoxLayout(self.central_widget)
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# First half for EEG signal plot
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self.eeg_plot_widget = PlotWidget(self)
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self.eeg_plot_widget.setBackground('w')
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self.eeg_plot_widget.showGrid(x=True, y=True)
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self.eeg_plot_widget.setLabel('bottom', 'EEG Plot')
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self.eeg_plot_widget.setYRange(0, 15000, padding=0)
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self.eeg_plot_widget.setXRange(0, 10, padding=0)
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self.eeg_plot_widget.setMouseEnabled(x=False, y=False) # Disable zoom
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self.main_layout.addWidget(self.eeg_plot_widget)
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# Second half for FFT and Brainwave Power, aligned horizontally
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self.bottom_layout = QHBoxLayout()
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# FFT Plot (left side of the second half)
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self.fft_plot = PlotWidget(self)
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self.fft_plot.setBackground('w')
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self.fft_plot.showGrid(x=True, y=True)
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self.fft_plot.setLabel('bottom', 'FFT')
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self.fft_plot.setYRange(0, 25000, padding=0)
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self.fft_plot.setXRange(0, 50, padding=0) # Set x-axis to 0 to 50 Hz
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self.fft_plot.setMouseEnabled(x=False, y=False) # Disable zoom
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self.bottom_layout.addWidget(self.fft_plot)
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# Bar graph for brainwave power bands (right side of the second half)
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self.bar_chart_widget = pg.PlotWidget(self)
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self.bar_chart_widget.setBackground('w')
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self.bar_chart_widget.setLabel('bottom', 'Brainpower Bands')
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self.bar_chart_widget.setXRange(-0.5, 4.5)
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self.bar_chart_widget.setMouseEnabled(x=False, y=False) # Disable zoom
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# Add brainwave power bars
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self.brainwave_bars = pg.BarGraphItem(x=[0, 1, 2, 3, 4], height=[0, 0, 0, 0, 0], width=0.5, brush='g')
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self.bar_chart_widget.addItem(self.brainwave_bars)
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# Set x-ticks for brainwave types
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self.bar_chart_widget.getAxis('bottom').setTicks([[(0, 'Delta'), (1, 'Theta'), (2, 'Alpha'), (3, 'Beta'), (4, 'Gamma')]])
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self.bottom_layout.addWidget(self.bar_chart_widget)
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# Add the bottom layout to the main layout
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self.main_layout.addLayout(self.bottom_layout)
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self.setCentralWidget(self.central_widget)
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# Set up LSL stream inlet
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streams = pylsl.resolve_stream('name', 'BioAmpDataStream')
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if not streams:
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print("No LSL stream found!")
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sys.exit(0)
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self.inlet = pylsl.StreamInlet(streams[0])
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# Sampling rate
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self.sampling_rate = int(self.inlet.info().nominal_srate())
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print(f"Sampling rate: {self.sampling_rate} Hz")
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# Data and buffers
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self.buffer_size = self.sampling_rate * 10 # Fixed-size buffer for 10 seconds
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self.eeg_data = np.zeros(self.buffer_size) # Fixed-size array for circular buffer
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self.time_data = np.linspace(0, 10, self.buffer_size) # Fixed time array for plotting
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self.current_index = 0 # Index for overwriting data
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# Low-pass filter (4th order, cutoff at 45 Hz)
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self.b_lowpass, self.a_lowpass = butter(4, 45 / (0.5 * self.sampling_rate), btype='low')
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# Timer for updating the plot
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self.timer = pg.QtCore.QTimer()
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self.timer.timeout.connect(self.update_plot)
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self.timer.start(20)
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self.eeg_curve = self.eeg_plot_widget.plot(self.time_data, self.eeg_data, pen=pg.mkPen('b', width=1)) #EEG Colour is blue
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self.fft_curve = self.fft_plot.plot(pen=pg.mkPen('r', width=1)) # FFT Colour is red
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def update_plot(self):
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samples, _ = self.inlet.pull_chunk(timeout=0.0, max_samples=30)
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if samples:
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for sample in samples:
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# Overwrite the oldest data point in the buffer
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self.eeg_data[self.current_index] = sample[0]
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self.current_index = (self.current_index + 1) % self.buffer_size # Circular increment
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# Apply low-pass filter
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filtered_eeg = filtfilt(self.b_lowpass, self.a_lowpass, self.eeg_data)
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# Update the EEG plot with the filtered data
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self.eeg_curve.setData(self.time_data, filtered_eeg)
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# Perform FFT with windowing (Hamming window)
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window = hamming(len(filtered_eeg)) # Apply Hamming window to reduce spectral leakage
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filtered_eeg_windowed = filtered_eeg * window # Element-wise multiply
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eeg_fft = np.abs(fft(filtered_eeg_windowed))[:len(filtered_eeg_windowed) // 2] # Positive frequencies only
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freqs = np.fft.fftfreq(len(filtered_eeg_windowed), 1 / self.sampling_rate)[:len(filtered_eeg_windowed) // 2]
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# Update FFT plot
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self.fft_curve.setData(freqs, eeg_fft)
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# Calculate brainwave power
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brainwave_power = self.calculate_brainwave_power(eeg_fft, freqs)
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self.brainwave_bars.setOpts(height=brainwave_power)
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def calculate_brainwave_power(self, fft_data, freqs):
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delta_power = np.sum(fft_data[(freqs >= 0.5) & (freqs <= 4)])
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theta_power = np.sum(fft_data[(freqs >= 4) & (freqs <= 8)])
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alpha_power = np.sum(fft_data[(freqs >= 8) & (freqs <= 13)])
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beta_power = np.sum(fft_data[(freqs >= 13) & (freqs <= 30)])
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gamma_power = np.sum(fft_data[(freqs >= 30) & (freqs <= 45)])
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return [delta_power, theta_power, alpha_power, beta_power, gamma_power]
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if __name__ == "__main__":
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app = QApplication(sys.argv)
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window = EEGMonitor()
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window.show()
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sys.exit(app.exec_())

‎applications/heartbeat_ecg.py

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@@ -59,19 +59,34 @@ def __init__(self):
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# Set y-axis limits based on sampling rate
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if self.sampling_rate == 250:
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self.plot_widget.setYRange(0, 2**10) # for R3
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self.plot_widget.setYRange(0, 2**10,padding=0) # for R3 & ensuring no extra spaces at end
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elif self.sampling_rate == 500:
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self.plot_widget.setYRange(0, 2**14) # for R4
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self.plot_widget.setYRange(0, 2**14,padding=0) # for R4 & ensuring no extra spaces at end
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# Set fixed x-axis range
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self.plot_widget.setXRange(0, 10) # 10 seconds
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self.plot_widget.setXRange(0, 10,padding=0) # ensure no extra spaces
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self.ecg_curve = self.plot_widget.plot(self.time_data, self.ecg_data, pen=pg.mkPen('k', width=1))
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self.r_peak_curve = self.plot_widget.plot([], [], pen=None, symbol='o', symbolBrush='r', symbolSize=10) # R-peaks in red
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self.moving_average_window_size = 5 # Initialize moving average buffer
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self.heart_rate_history = [] # Buffer to store heart rates for moving average
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# Connect double-click event
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self.plot_widget.scene().sigMouseClicked.connect(self.on_double_click)
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def on_double_click(self, event):
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if event.double():
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self.reset_zoom()
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def reset_zoom(self):
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# Reset to default y-axis limits based on the sampling rate
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if self.sampling_rate == 250:
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self.plot_widget.setYRange(0, 2**10, padding=0)
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elif self.sampling_rate == 500:
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self.plot_widget.setYRange(0, 2**14, padding=0)
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self.plot_widget.setXRange(0, 10, padding=0)
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def update_plot(self):
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samples, _ = self.inlet.pull_chunk(timeout=0.0, max_samples=30)
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if samples:

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