Muscle Model¶

The spike trains alone are not enough to create EMG signals.

To create EMG signals, we need to create a muscle model that will distribute the motor units and fibers within the muscle volume.

Import Libraries¶

from pathlib import Path

import joblib
import matplotlib.pyplot as plt
import numpy as np

from myogen import load_profile
from myogen.utils.plotting.muscle import plot_innervation_areas_2d, plot_mf_centers

plt.style.use("fivethirtyeight")

Define Parameters¶

The muscle model is a Muscle object. Its main parameters are:

recruitment_thresholds: Recruitment thresholds of the motor units
radius__mm: Radius of the muscle
fiber_density__fibers_per_mm2: Fiber density
skin_thickness__mm, fat_thickness__mm: Layers between the muscle and the electrodes

The fdi_semg profile card holds the FDI values with their sources (radius 6.91 mm, 267 fibres/mm², skin 1.2 mm, fat 1.3 mm, per-unit conduction velocities from recruitment force, ...). card.muscle() builds the muscle with them and the card's recruitment thresholds (regenerated from its seed: those of example 01). Keywords override a card value, e.g. card.muscle(fat_thickness__mm=3 * pq.mm); the card then prints a note on what else that affects.

save_path = Path("./results")
card = load_profile()  # fdi_semg

Create Muscle Model¶

Note

Depending on the parameters, the simulation can take a few minutes to run.

To avoid running the simulation every time, we can save the muscle model using joblib.

# Create muscle model (innervation areas, fibres, fibre-to-unit assignment, fibre properties)
muscle = card.muscle()

# Save muscle model for future use
joblib.dump(muscle, save_path / "muscle_model.pkl")

# Display muscle statistics
total_fibers = sum(muscle.resulting_number_of_innervated_fibers)

print("Muscle model statistics:")
print(f"\tTotal muscle fibers: {total_fibers}")
print(f"\tMean fibers per MU: {total_fibers / len(muscle.resulting_number_of_innervated_fibers):.1f}")
print(f"\tMuscle cross-sectional area: {np.pi * muscle.radius__mm**2:.1f}")

Out:

Muscle model statistics:
        Total muscle fibers: 40051
        Mean fibers per MU: 333.8
        Muscle cross-sectional area: 150.0 mm**2

Visualize Muscle Fiber Centers¶

The fiber centers are the centers of the fibers that are innervated by the motor units.

Note

The fiber centers have been precalculated from a Voronoi tessellation of the muscle volume. Then depending on the fiber density, the fiber centers are distributed within the muscle volume.

plt.figure(figsize=(6, 6))

plot_mf_centers(muscle, ax=plt.gca())
plt.xlabel("X Position (mm)")
plt.ylabel("Y Position (mm)")
plt.axis("equal")
plt.grid(False)

plt.tight_layout()
plt.show()

Muscle fibers' center points

Visualize Motor Unit Innervation Areas¶

Display the spatial organization of motor units and their innervation areas.

Note

The innervation areas are the areas where the motor units are innervated. They are calculated using the recruitment thresholds and the fiber density.

plt.figure(figsize=(6, 6))

plot_innervation_areas_2d(muscle, ax=plt.gca())
plt.xlabel("X Position (mm)")
plt.ylabel("Y Position (mm)")
plt.axis("equal")
plt.grid(False)

plt.tight_layout()
plt.show()

Motor neuron innervation areas

Total running time of the script: ( 2 minutes 33.528 seconds)

Download Python source code: 04_simulate_muscle.py

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