Cataract Maps with Snap-on Eyepiece for Mobile Phones

MIT labs has developed  device to map cataract with Snap-on  Eyepiece for Mobile Phones.

Cataracts are the leading cause of blindness worldwide.  Existing diagnostic methods require Slit-lamps. We propose (CATRA) a new solution to detect and quantify cataracts with a compact eyepiece attached to a cell phone. With no moving parts and built from off-the-shelf components, our solution is well suited for the developing world.

A cataract-affected eye scatters and refracts light before it reaches the retina, caused by a fogging or clouding of the lens. We measure this deformation or (clouding) by allowing one to compare a good light path with a light path blocked by the cataract. Current methods for cataract detection require costly equipment and highly trained clinicians. They utilize back-scattering which is observed and subjectively diagnosed. However, this does not address the early onset of cataract affected vision, as early opacities are difficult to detect. Back scattering can be misleading as it does not account for what the patient actually sees.  Existing techniques present a simple grading of severity, while our technique presents a full map of opacity and scattering.  Our technique allows for a coupling of quantifiable data with the users visual experience.

CATRA utilizes a forward scattering technique, which allows the user to respond to what they visually experience.  Our device scans the lens section by section. The user sees our projected patterns and presses a few buttons to map the light attenuation in each section of the eye.  This information is collected by the device creating an attenuation map of the entire lens.  This allows individuals to monitor the progression of the severity of the cataract.  Our maps capture a full point spread function of the lens, allowing us to simulate the visual perception of a cataract affected subject over time.  Early cataract onset is difficult to diagnose.  We present a device for measuring cataracts, which is highly portable and collects quantifiable data to help tackle a global health problem making it ideal for the developing world

 

 

For more details visit: http://www.media.mit.edu/