Investigation on Vision System: Digital FPGA Implementation in Case of Retina Rod Cells.

Area of Science:

• Biomedical Engineering
• Neuroscience
• Computer Engineering

Background:

• Hardware modeling of biological components is crucial for prostheses and treatments.
• The retina, particularly rod cells, presents unique challenges due to complex nonlinear functions.
• Existing models often require significant hardware resources and may not meet speed constraints.

Purpose of the Study:

• To develop a cost-effective and efficient hardware implementation of retinal rod cells.
• To adapt the Nyquist-Based Approximation of Retina Rod Cell (NBAoRRC) approach using Look-Up Tables (LUTs).
• To reduce hardware complexity and power consumption compared to traditional models.

Main Methods:

• Utilized the Nyquist-Based Approximation of Retina Rod Cell (NBAoRRC) approach.
• Adapted the model to use Look-Up Tables (LUTs) instead of complex nonlinear functions.
• Implemented the rod cell model on a Field-Programmable Gate Arrays (FPGA) Virtex-5 board.

Main Results:

• The proposed NBAoRRC model with LUTs successfully mimics the dynamic behavior of primary rod cell models.
• Hardware implementation on FPGA demonstrated a 30% reduction in power consumption compared to the primary model.
• The model requires significantly fewer hardware resources, enhancing cost-effectiveness.

Conclusions:

• The LUT-based NBAoRRC approach provides a reliable and efficient method for digital implementation of rod cells.
• This method eliminates costly operators, leading to reduced power and hardware resource utilization.
• The findings are significant for developing advanced retinal prostheses and neural simulations.