The Raspberry Pi is being used to save the eyesight of people in India thanks to the Open Indirect Ophthalmoscope (OIO) project.

Inside the OIO, machine learning technology is used to spot eye problems. Subsequently, the OIO becomes better at checking for problems over long-term use.

“The Open Indirect Ophthalmoscope is a portable retinal camera that uses machine learning to make diagnosis not only affordable but also accurate and reliable,” says Sandeep Vempati, a mechanical engineer at the Srujana Center for Innovation, a part of the L V Prasad Eye Institute (LVPEI).

The heart of the OIO is a Raspberry Pi. Our low-cost computer drives down the cost of taking high-quality photos of the retina.

“Currently, visual impairment affects 285 million people worldwide,” said Sandeep. “What’s more surprising is the fact that 80 percent of all visual impairment can be prevented or cured, if diagnosed correctly.”

Open Indirect Ophthalmoscope (OIO) An open-source, ultra-low cost, portable screening device for retinal diseases. OIO(OWL) is an idea conceived in Srujana Innovation Centre at the L V Prasad Eye Institute, Hyderabad, India. It is an open source retinal image capturing device with dynamic diabetic retinopathy grading system.

“India is the diabetes capital of the world,” explained Dr Jay Chhablani, a specialist in retinal disease at the LVPEI. “Diabetes leads to something called diabetic retinopathy”.

For that reason, it’s important to remove barriers to treatment. “If we see the patient at an early stage,” says Dr Chhablani, “we can treat them by controlling diabetes and applying laser treatment”.

“Although eye care services have become increasingly available,” said Sandeep, “diagnosing diseases like diabetic retinopathy is still a problem in many parts of the world.”

Sandeep’s team strove to build an open device. As a result, OIO can be 3D printed and assembled anywhere in the world.

“3D printing creates the OIO for a fraction of the cost of conventional devices, and yet maintains the same quality,” explains Sandeep.

Compared to professional devices, the OIO costs just $800 to build. In contrast, professional retinal cameras can cost around ten times as much.

Over on OIO’s Hackaday page you will find the components. Inside is a Raspberry Pi 3, a Camera Module, a 20 dioptre lens, front-end mirrors, and a 5-inch touchscreen.

“Engineering feels great when you see a product being useful in the real world,” says Sandeep.