Restoring vision to the blind Part II: What will the patients see - PowerPoint PPT Presentation

Title: Restoring vision to the blind Part II: What will the patients see


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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
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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

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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 22607-655 (2003)
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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 (gt
  2o)
• Phosphenes from closely spaced electrodes may
  overlap/fuse
• Retinal prosthetic vision may be pretty blurry

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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

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And then there is background noiseMany blind RP
patients see flashes like this
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or even this
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so reading with a (high-resolution, retinal)
prosthesis may look like this
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or even this !
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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

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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

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Daily activitiesHow many dots do they take?
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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?
• Whats 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

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Face identification Dot size
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Face identification Dot spacing
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Face identification Grid size
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Face identification Dropout percentage
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Face identification Gray levels
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Face identification Summary

• Performance well above chance, except for
• large dots and/or gaps (i.e., lt6 c/fw)
• small grid or small dots (lt 0.5 fw)
• gt50 drop-out
• lt4 gray levels
• Low contrast does not seriously reduce
  performance
• Significant between-subject variability
  (unfamiliar task?)

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Reading test Procedure
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Reading test Sample clips
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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

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Reading speed Font size
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Reading speed Dot size
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Reading speed Dot spacing
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Reading speed Grid size
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Reading speed Dropout percentage
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Reading speed Gray levels
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Reading test Summary

• Reading adequate, but drops off for
• Small fonts (lt6 dots/char)
• Small grid (plateau beyond 25X25 dots)
• gt30 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?)

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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
• Its safe!

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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

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Video Virtual mobility, normal view
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Video Virtual mobility, 6x10 pixelized view
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Prosthetic vision simulationsVisual
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 !

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Video pair Face identification taskFree-viewing
vs. gaze-locked
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Face identification, free-viewing vs.
gaze-locked Learning
FV free viewing, FX fixation controlled
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Video pair Reading taskFree-viewing vs.
gaze-locked
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Prosthetic vision simulationsLow 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)

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Prosthetic vision simulationsRehabilitation

• 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

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So whats 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

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Functional prosthetic visionHow 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

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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

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Towards artificial sight A long, exciting road
ahead!

• 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