Plotting EMG Data

This tutorial covers the plotting functions provided by the intan.plotting module for visualizing EMG and analog data acquired from Intan devices.

You can use these plotting functions on data loaded from .rhd or .dat files using the intan.io module.

First, load your data from an .rhd file:

from intan.io import load_rhd_file
result = load_rhd_file()  # Opens a file dialog to select a .rhd file

emg_data = result['amplifier_data']                # (num_channels, num_samples)
t_s = result['t_amplifier']

# Optional: load analog data if present
analog_data = result.get('board_adc_data')         # (num_channels, num_samples)
t_analog = result.get('t_board_adc')                   # (num_samples,)

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Plot a Single Channel by Name

If you know the channel’s native name (e.g., “A-005”), use plot_channel_by_name:

from intan.plotting import plot_channel_by_name

# Get the name of the 5th channel
ch_name = ch_info[4]['native_channel_name']
plot_channel_by_name(ch_name, result)

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Plot a Single Channel by Index

You can also plot by index directly:

from intan.plotting import plot_channel_by_index

plot_channel_by_index(8, result)   # Plots channel index 8

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Plot Any Signal with plot_figure

The plot_figure function is a generic plotter for any 1D signal, including EMG or analog input:

from intan.plotting import plot_figure

# Plot the first EMG channel
plot_figure(emg_data[0], t_s, "EMG Channel 0", x_label="Time (s)", y_label="Amplitude (µV)")

# If analog data is present, plot the first analog channel
if analog_data is not None:
    plot_figure(analog_data[0], t_s, "Analog Channel 0", x_label="Time (s)", y_label="Voltage (V)")

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Waterfall Plot (Multi-channel Visualization)

To visualize activity across many EMG channels simultaneously, use waterfall:

from intan.plotting import waterfall

# Plot channels 64 to 127 in a waterfall plot
waterfall(emg_data, range(64, 128), t_s, plot_title='Intan EMG data')

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Summary

These functions make it easy to visualize both raw and processed EMG/analog signals from Intan recordings. You can quickly inspect data quality, channel names, and signal characteristics for further analysis.

For more advanced usage (such as real-time streaming plots), see the corresponding tutorials.