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Static Helps the Deaf to Hear

Posted by timothy on from the pssssh-bad-connection-pssshhhh dept.

OmegaGeek writes: "Jay Rubinstein, a researcher at the University of Iowa, has found a way to improve the signal processing algorithms of cochlear implants (and he's writing in FORTRAN - is this a leading indicator of a FORTRAN revival?). Adding static to the signal actually increases the dynamic hearing range in patients with a cochlear implant."

5 of 20 comments (clear)

  1. excellent work by Sir+Elton+John · · Score: 3, Interesting

    As a person with a considerable dedication to music, I am heartened by any progress in the area of hearing restoration. Too often the hearing abled take for granted what surely is the most emotive of the senses. This is a step in the right direction, and a strong step at that.

    As for FORTRAN, that doesn't surprise me. FORTRAN has always been the language of choice for low-level signal processing, where the overhead of C libraries makes anything else impractical.

    Carry on!

    --
    "I'm a rocket man / Rocket man burning out his fuse up here alone." - Sir Elton John
  2. Re:ummm... - Fortran in scientific computing by Ilari · · Score: 4, Interesting

    Actually, Fortran still is quite popular in the field of scientific computing. Fortran90/95 and High Performance Fortran that is, definitely NOT Fortran77. F90/95 is actually a rather easy language to program in, it is very similar to Matlab (the leading choise of many scientists for numerical analysis) in many ways, which makes porting from Matlab to Fortran easy. (Many projects start with a rough "first draft" code in Matlab and then move on to more powerful languages as the project advances and computational requirement increase.) Memory management, vector and matrix manipulation is also definitely a lot easier in Fortran than in C.

    It still doesn't mean that Fortran is making a comeback. It just fills a particular niche.

  3. Re:This is equally amazing.. by Anonymous Coward · · Score: 2, Interesting

    It didn't make it on the front page..

    Bio-engineering is nifty stuff. From intro undergraduate DSP if the brain doesn't treat each ear independently (kind of like stereo vision) I wonder if the brain is doing any covolution or difference between the signals to increase sensitivity.

  4. Stochastic resonance? by dpp · · Score: 3, Interesting

    Is this perhaps the same thing as stochastic resonance ? I remember reading about it once; it relies on the idea that by adding white noise to a system you can push its behaviour over some detection threshold, and thus convey the signal better, even though you're actually adding noise. Quite interestingly counter-intuitive at first!

    From the linked site above:

    In fact, there is an optimal amount of noise for doing this: too little noise and the signal doesn't get through, too much noise and the signal gets swamped.
    --
    This post is strictly my own opinion and not necessarily that of my employer.
    1. Re:Stochastic resonance? by mph · · Score: 2, Interesting

      A similar technique, called pre-flashing, was sometimes used for photographic astronomical plates. Photographic emulsions have a nonlinear response, and so you would briefly expose the plate to light (which is a source of noise... we fight light pollution and sky glow all the time) to bring faint sources up to a better part of the response curve.

      Ansel Adams also discusses this technique in his books, for improving tonal separation in the shadows.