Design of an Integrated Subretinal Implant using Cellular Neural Networks for Binary Image Generation in a 130 nm BiCMOS Process

Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul:2019:5268-5273. doi: 10.1109/EMBC.2019.8856941.

Abstract

Blindness caused by the eye diseases Retinitis-Pigmentosa and Age-Related-Macular-Degeneration leads to a degeneration of the photoreceptor layer while postsynaptic cells mostly stay intact. In this Paper a new concept for retinal implants is proposed. Instead of converting the incident light to a gray-scale picture with corresponding continuous-value stimulation levels, we here suggest to produce a binary image picture that only highlight edges in order to stimulate the retina solely at points which belong to an edge. An integrated test circuit is designed with a 130 nm BiCMOS process by using cellular neural networks for binary image generation. The circuit yields a simulated maximum rated power consumption of 2.61 mW for a 1000 information processing cells.

MeSH terms

  • Animals
  • Blindness
  • Macular Degeneration* / therapy
  • Prostheses and Implants
  • Retina
  • Retinitis Pigmentosa* / therapy
  • Visual Prosthesis*