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Proceedings Paper

A low-power imager and compression algorithms for a brain-machine visual prosthesis for the blind
Author(s): L. Turicchia; M. O'Halloran; D. P. Kumar; R. Sarpeshkar
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Paper Abstract

We present a synchronous time-based dual-threshold imager that experimentally achieves 95.5 dB dynamic range, while consuming 1.79 nJ/pixel/frame, making it one of the most wide-dynamic-range energy-efficient imagers reported. The imager has 150×256 pixels, with a pixel pitch of 12.5μm × 12.5μm and a fill factor of 42.7%. The imager is intended for use in a brain-machine visual prosthesis for the blind where energy efficiency and power are of paramount importance. Such prostheses will also need to convey visual information to patients with relatively few electrodes and in a manner that minimizes electrode interactions, just as cochlear implants have accomplished for deaf subjects. To achieve these goals, we present a strategy that compresses visual information into the basis coefficients of a few image kernels that encode enough information to provide reasonably good image reconstruction with 60 electrodes. The strategy also uses time-multiplexed stimulation of electrodes to minimize channel interactions like the continuous interleaved sampling (CIS) strategy used in cochlear implants. Some of the image kernels that we employ are similar to the receptive fields observed in biology and may thus be natural to learn, just as cochlear-implant subjects have learned to reconstruct sound from a few filter basis coefficients.

Paper Details

Date Published: 29 August 2008
PDF: 13 pages
Proc. SPIE 7035, Biosensing, 703510 (29 August 2008); doi: 10.1117/12.797211
Show Author Affiliations
L. Turicchia, Massachusetts Institute of Technology (United States)
M. O'Halloran, Massachusetts Institute of Technology (United States)
D. P. Kumar, Massachusetts Institute of Technology (United States)
R. Sarpeshkar, Massachusetts Institute of Technology (United States)


Published in SPIE Proceedings Vol. 7035:
Biosensing
Manijeh Razeghi; Hooman Mohseni, Editor(s)

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