mne.simulation.add_ecg#

mne.simulation.add_ecg(raw, head_pos=None, interp='cos2', n_jobs=None, random_state=None, verbose=None)[source]#

Add ECG noise to raw data.

Parameters:

rawinstance of Raw

The raw instance to modify.

head_posNone | str | dict | tuple | array

Name of the position estimates file. Should be in the format of the files produced by MaxFilter. If dict, keys should be the time points and entries should be 4x4 dev_head_t matrices. If None, the original head position (from info['dev_head_t']) will be used. If tuple, should have the same format as data returned by head_pos_to_trans_rot_t. If array, should be of the form returned by mne.chpi.read_head_pos().

interpstr

Either ‘hann’, ‘cos2’ (default), ‘linear’, or ‘zero’, the type of forward-solution interpolation to use between forward solutions at different head positions.

n_jobsint | None

The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_backend() context manager that sets another value for n_jobs.

random_stateNone | int | instance of RandomState

A seed for the NumPy random number generator (RNG). If None (default), the seed will be obtained from the operating system (see RandomState for details), meaning it will most likely produce different output every time this function or method is run. To achieve reproducible results, pass a value here to explicitly initialize the RNG with a defined state. The random generator state used for blink, ECG, and sensor noise randomization.

verbosebool | str | int | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns:

rawinstance of Raw

The instance, modified in place.

See also

add_chpi

add_eog

add_noise

simulate_raw

Notes

The ECG artifacts are generated by:

1. Random inter-beat intervals are drawn from a uniform distribution of times corresponding to 40 and 80 beats per minute.

2. The activation function is the sum of three Hanning windows with varying durations and scales to make a more complex waveform.

3. The activated dipole is located one (estimated) head radius to the left (-x) of head center and three head radii below (+z) head center; this dipole is oriented in the +x direction.

4. Activations only affect MEG channels.

The scale-factor of the activation function was chosen based on visual inspection to yield amplitudes generally consistent with those seen in experimental data. Noisy versions of the activation will be stored in the first EOG channel in the raw instance, if it exists.

New in version 0.18.

Examples using mne.simulation.add_ecg#

Generate simulated raw data

Generate simulated raw data

Simulate raw data using subject anatomy

Simulate raw data using subject anatomy