This article presents the study of nonlinear dynamics of cardiac excitation based on the Luo Rudy Phase I (LR-I) model towards numerical solutions of ordinary differential equations (ODE). ) responsible for cardiac excitation on FPGA. As computational modeling requires a lot of simulation time, a real-time hardware implementation using FPGA could be the solution as it provides high configurability and performance. For rapid prototyping, MATLAB Simulink offers a link with the FPGA which is an HDL encoder capable of converting MATLAB Simulink blocks into Very High Description Language (VHDL) and via an FPGA-in-the-loop, the simulation for implementation FPGA work can be done. Here, MATLAB Simulink successfully simulates the LR-I of the excitation model for software simulations. Towards real-time simulation, the HDL Coder function will be used for the hardware implementation of the FPGA. Cardiac excitation controls mechanical contractions of cells via the cardiac excitation-contraction coupling mechanism and is controlled by the entry and exit of transmembrane currents through various types of ion channels. However, abnormalities in cardiac excitation known as cardiac arrhythmias can occur and cause the heart muscle to contract abnormally and prevent the heart from pumping blood effectively and can pose a life-threatening risk [1-3]. In recent decades, experimental studies are generally preferable [3]. Although this approach is preferable, experimental studies have limitations such as the amount of variables to monitor, which requires high resolution data to study larger preparations and high cost. Meanwhile, modeling techniques for computer simulation are not associated with such problems [3]. Therefore, many electrical and...... middle of paper ...... Computer model study. Long Island Jewish Medical Center, New York, United States of America, 341-343, 1995.[11] Yasunori O., Funahashi A., Shibata Y., Kitano H., and Amano H. An FPGA-based multi-model simulation for biochemical systems. Japan. Proceedings of the 19th IEEE International Symposium on Parallel and Distributed Processing, 1-4, 2005.[12] Alireza F., Trong TD, Chedjou JC, and Kyamakya K. New computational modeling for solving higher order ODEs based on FPGA. Alpen-Adria University Klagenfurt, Austria, 1-5, 2012.[13] Huang C., Frank V., and Tony G. A custom FPGA processor for solving ordinary differential equations of physical models, IEE Embedded System Letters, Vol. 3 n° 4, 1-4, December 2011.[14] Siwakoti PY, Graham ET, Design of Power Electronics and FPGA Controlled Drives Using MATLAB Simulink, Macquarie University, Australia, 571- 577, 2013.