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Restoring vision to the blind Part II: What will the patients see?. Gislin Dagnelie, Ph.D. Lions Vision Research & Rehabilitation Ctr Wilmer Eye Institute Johns Hopkins Univ Sch of Medicine Department of Veterans Affairs Rehabilitation Center Augusta, GA April 15, 2005. Lines of attack.

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Restoring vision to the blind part ii what will the patients see l.jpg

Restoring vision to the blindPart II: What will the patients see?

Gislin Dagnelie, Ph.D.

Lions Vision Research & Rehabilitation Ctr

Wilmer Eye Institute

Johns Hopkins Univ Sch of Medicine

Department of Veterans Affairs Rehabilitation Center

Augusta, GA

April 15, 2005


Lines of attack l.jpg

Lines of attack

  • Systems engineering (“brute force” or maybe just pragmatic)

  • Electrode/tissue engineering (“remodeling the interface”)

  • Likely limitations (space and time)

  • (Low) vision science/rehab


Spatial limits retinal rewiring robert marc l.jpg

Spatial limits: retinal rewiringRobert Marc

  • Ultrastructural evidence from donor RP/AMD retinas:

    • Extensive rewiring of inner retinal cells

    • Neurite processes spread over long distances (~300 μm)

    • Glial cells migrate into choroid

  • Injected electrical current may spread through neurite tangle

Marc RE, Progr in Retin Eye Res 22:607-655 (2003)


Spatial limits implications of retinal rewiring l.jpg

Spatial limits: implications of retinal rewiring

  • Stimulating degenerated retina may be like writing on tissue paper with a fountain pen:

    • Charge diffusion over distances up to 1o

    • Phosphenes likely to be blurry (Gaussian blobs), not sharp

    • Minor effect if electrodes are widely spaced (>= 2o)

    • Phosphenes from closely spaced electrodes may overlap/fuse

      Retinal prosthetic vision may be pretty blurry…


Temporal limits persistence humayun et al l.jpg

Temporal limits: persistenceHumayun et al.

  • Single electrode, acute testing:

    • Flicker fusion occurs at 25-40 Hz

  • Multi-electrode implant testing:

    • Rapid changes are hard to detect

    • Flicker fusion at lower frequency?

      Maybe prosthetic vision will be not just blurry, but also streaky…


And then there is background noise many blind rp patients see flashes like this l.jpg

And then there is background noise:Many blind RP patients see “flashes” like this…


Or even this l.jpg

…or even this…


So reading with a high resolution retinal prosthesis may look like this l.jpg

so reading with a (high-resolution, retinal) prosthesis may look like this…


Or even this9 l.jpg

…or even this !


Caution l.jpg

Caution

It is naïve to expect that we will

implant a retinal prosthesis,

turn on the camera,

and just send the patient home to practice


Lines of attack11 l.jpg

Lines of attack

  • Systems engineering (“brute force” or maybe just pragmatic)

  • Electrode/tissue engineering (“remodeling the interface”)

  • Likely limitations (space and time)

  • (Low) vision science/rehab


Daily activities how many dots do they take l.jpg

Daily activities:How many dots do they take?…


Developing an implantable prosthesis l.jpg

Developing an implantable prosthesis

  • How does it work?

  • Why should it work?

  • What did blind patients see in the OR?

  • What do the first implant recipients tell us?

  • What could the future look like?

  • What’s up next?


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Simulation techniques

  • “Pixelized” images shown to normally-sighted and low vision observers wearing video headset

  • Images are gray-scale only, no color

  • Layout of dots in crude raster, similar to (current and anticipated) retinal implants

  • Subject scans raster across underlying image through:

    • Mouse/cursor movement, or

    • Head movement (camera or head tracker)


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Performance under “idealized” conditions

Subjects performed the following tasks:

  • Use live video images to perform “daily activities”

  • Walk around an office floor

  • Discriminate a face in 4 alternative forced choice

  • Read meaningful text


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Live test: candy pour, 16x16


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Live test: Mobility


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Live test: Mobility, 6x10


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Live test: spoon in 4x4 view


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Face Identification Procedure


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Face identification: Methods

  • 4 groups (M/F, B/W) of 15 models (Y/M/O, 5 each)

  • Face width 12º

  • Parameters (varied one by one from standard):

    • Dot size: 23-78 arcmin

    • Gap size: 5-41 arcmin

    • Grid size: 10X10, 16X16, 25X25, 32X32

    • Random dropout: 10%, 30%, 50%, 70%

    • Gray levels: 2, 4, 6, 8

  • Tests performed at 98% and 13% contrast

  • Each parameter combination presented 6 times

  • Data from 4 normally-sighted subjects


Face identification dot size l.jpg

Face identification: Dot size


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Face identification: Dot spacing


Face identification grid size l.jpg

Face identification: Grid size


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Face identification: Dropout percentage


Face identification gray levels l.jpg

Face identification: Gray levels


Face identification summary l.jpg

Face identification: Summary

  • Performance well above chance, except for:

    • large dots and/or gaps (i.e., <6 c/fw)

    • small grid or small dots (< 0.5 fw)

    • >50% drop-out

    • <4 gray levels

  • Low contrast does not seriously reduce performance

  • Significant between-subject variability (unfamiliar task?)


Reading test procedure l.jpg

Reading test: Procedure


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Reading test: Sample clips


Reading test methods l.jpg

Reading test: Methods

  • Novel, meaningful text; grade 6 level

  • Scored for reading rate and accuracy

  • Font size 31, 40, 50, 62 points (2-4º characters)

  • Parameters (varied separately from standard):

    • Dot size: 23-78 arcmin

    • Gap size: 5-41 arcmin

    • Grid size: 10X10, 16X16, 25X25, 32X32

    • Random dropout: 10%, 30%, 50%, 70%

    • Gray levels: 2, 4, 6, 8

  • Tests performed at 98% and 13% contrast


Reading speed font size l.jpg

Reading speed: Font size


Reading speed dot size l.jpg

Reading speed: Dot size


Reading speed dot spacing l.jpg

Reading speed: Dot spacing


Reading speed grid size l.jpg

Reading speed: Grid size


Reading speed dropout percentage l.jpg

Reading speed: Dropout percentage


Reading speed gray levels l.jpg

Reading speed: Gray levels


Reading test summary l.jpg

Reading test: Summary

  • Reading adequate, but drops off for:

    • Small fonts (<6 dots/char)

    • Small grid (plateau beyond 25X25 dots)

    • >30% drop-out (esp. low contrast)

    • Note: even 2 gray levels adequate

  • Low contrast reduces performance, but reading still adequate

  • Much less intersubject variability than for face identification (familiar task?)


Introducing virtual reality l.jpg

Introducing Virtual Reality

  • Flexible tasks:

    • Object and maze properties can be varied “endlessly”

    • Difficulty level can be adjusted (even automatically)

  • Precise response measures:

    • Subjects’ actions can be logged automatically

    • Constant response criteria can be built in

  • It’s safe!


Virtual mobility task l.jpg

Virtual mobility task

  • Ten different “floor plans” in a virtual building

  • Pixelized and stabilized view, 6x10 dots

  • Drop-out percentage and dynamic noise varied

  • Use cursor keys to maneuver through 10 rooms


Video virtual mobility normal view l.jpg

Video: Virtual mobility, normal view


Video virtual mobility 6x10 pixelized view l.jpg

Video: Virtual mobility, 6x10 pixelized view


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Prosthetic vision simulations:Visual inspection/coordination

Playing checkers:

A challenge for visually guided performance


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Introducing Eye Movements

  • Until now, free viewing conditions:

    • Subject can scan eye across dot raster

    • Mouse or camera movement used to scan raster across scene

  • Electrodes will be stabilized on the retina:

    • When the eyes move, dots move along

    • Mouse or camera used to move scene “behind” dots

  • Tough task !


Video pair face identification task free viewing vs gaze locked l.jpg

Video pair: Face identification taskFree-viewing vs. gaze-locked


Face identification free viewing vs gaze locked learning l.jpg

Face identification, free-viewing vs. gaze-locked: Learning

FV= free viewing, FX= fixation controlled


Video pair reading task free viewing vs gaze locked l.jpg

Video pair: Reading taskFree-viewing vs. gaze-locked


Prosthetic vision simulations low vision science l.jpg

Prosthetic vision simulations:Low Vision Science

  • Reading with pixelized vision, stabilized vs. free-viewing:

    • Accuracy falls off a little sooner, and reading rate is 5x lower, BUT

    • Spatial processing properties (dots/charwidth and char/window drop-off) do not change

    • At low contrast, window restriction more severe (not shown)


Prosthetic vision simulations rehabilitation l.jpg

Prosthetic vision simulations:Rehabilitation

  • Learning makes all the difference:

    • Accuracy increases over time, both for high and for low contrast

    • Reading speed increases over time, for high and low contrast

    • Stabilized reading takes longer to learn, but improves relative to free viewing, both in accuracy and speed


So what s the use of simulations l.jpg

So what’s the use of simulations?

Simulating prosthetic vision can help in:

  • Determining requirements for vision tasks

  • Exploring and understanding wearers’ reports

  • Helping to find solutions for wearers’ problems

  • Conveying the “prosthetic experience” to clinicians and public

    AND:

  • Designing rehabilitation programs to help future prosthesis recipients


Functional prosthetic vision how far off l.jpg

Functional prosthetic vision:How far off ?

  • Our subjects perform quite well with 16X16 (or more) electrodes

  • They can learn to perform most tasks with 6X10

  • They can learn to avoid obstacles with 4X4

  • Typical daily living activities will require larger numbers of electrodes (at least 10X10), and intensive rehabilitation


Conclusion l.jpg

Conclusion

Prosthetic vision is not just a technological challenge:

It promises to bring new areas of vision research and rehabilitation

http://lions.med.jhu.edu/lvrc/gd.htm


Towards artificial sight a long exciting road ahead l.jpg

Simulations supported by:

National Eye Institute and Foundation Fighting Blindness

Special thanks to:

  • Anna Cronin-Scott

  • Paul Dagnelie

  • Chris De Marco, Ph.D.

  • Jasmine Hayes

  • Pearse Keane

  • Wentai Liu, Ph.D.

  • Laura Martin

  • Kathy Turano, Ph.D.

  • Matthias Walter

  • Vivian Yin

  • Second Sight, LLC

Towards artificial sight: A long, exciting road ahead!


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