Skip to main content

Fenton-Karma model.

Project description

Fenton-Karma Finitewave model

The Fenton-Karma model is a simplified mathematical representation of cardiac action potentials, designed to reproduce the essential excitation–recovery dynamics of cardiac cells. Unlike detailed ionic models, it does not explicitly describe individual ion currents but instead uses a reduced set of variables and parameters to capture the key features of cardiac electrophysiology. This abstraction makes the model computationally efficient while retaining the ability to simulate wave propagation, spiral wave dynamics, and arrhythmia mechanisms in cardiac tissue.

This model implementation can be used separately from the Finitewave, allowing for standalone simulations and testing of the model dynamics without the need for the entire framework.

Reference

Fenton, F. H., & Karma, A. (1998). Vortex dynamics in three-dimensional continuous myocardium with fiber rotation: Filament instability and fibrillation. Chaos: An Interdisciplinary Journal of Nonlinear Science, 8(1), 20-47.

DOI: https://doi.org/10.1063/1.166311

How to use (quickstart)

python -m examples.fenton_karma_example

How to test

python -m pytest -q

Repository structure

.
├── fenton_karma/                    # equations package (ops.py)
│   ├── __init__.py
│   └── ops.py                       # fill with the model equations (pure functions)
├── implementation/                  # 0D Fenton-Karma implementation
│   ├── __init__.py
│   └── fenton_karma_0d.py
├── example/
│   └── fenton_karma_example.py      # minimal script to run a short trace
├── tests/
│   └── fenton_karma_test.py         # smoke test; extend with reproducibility checks
├── .gitignore
├── LICENSE                          # MIT
├── pyproject.toml                   # placeholders to replace
└── README.md                        # this file

Variables

Model state variables: description, units and ranges (optional)

  • u — Transmembrane potential (mV)
  • v - Initial recovery variable (dimensionless)
  • w - Initial activation variable (dimensionless)

Parameters

Parameters and their default values

  • tau_r = 130 - Recovery time constant (ms)
  • tau_o = 12.5 - Activation time constant (ms)
  • tau_d = 0.172 - Deactivation time constant (ms)
  • tau_si = 127 - Slow inactivation time constant (ms)
  • tau_v_m = 18.2 - Membrane time constant (ms)
  • tau_v_p = 10 - Potential time constant (ms)
  • tau_w_m = 80 - Activation time constant for w (ms)
  • tau_w_p = 1020 - Activation time constant for w (ms)
  • k = 10 - Scaling factor for recovery dynamics
  • u_c = 0.13 - Threshold for recovery variable (dimensionless)
  • uc_si = 0.85 - Slow inactivation threshold (dimensionless)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

finitewave_model_fenton_karma-0.3.0.tar.gz (8.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

finitewave_model_fenton_karma-0.3.0-py3-none-any.whl (5.7 kB view details)

Uploaded Python 3

File details

Details for the file finitewave_model_fenton_karma-0.3.0.tar.gz.

File metadata

File hashes

Hashes for finitewave_model_fenton_karma-0.3.0.tar.gz
Algorithm Hash digest
SHA256 760092b75e3672b37e90513c92cef063b3a1e97634d2de2bc811e743364bde4e
MD5 d24f6156ed6a5b60b5cd8006d47f8318
BLAKE2b-256 5cc16c45fb130658b42d559da8be61a453eb1141183247864ac599036bc2ecca

See more details on using hashes here.

File details

Details for the file finitewave_model_fenton_karma-0.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for finitewave_model_fenton_karma-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 915655485c90ac97603ef6fb8ffb72161a548eeff1c17aea113fa08be6ccf032
MD5 72739d1bc2fc6ebe43fa208c96e45341
BLAKE2b-256 9cca11b5f0026fe459828817db9a158b9b17a3f5e78fbe179bd3f614a4ab3669

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page