My visit to the Lions Sight Research Foundation’s eye clinic (read more here) “opened my eyes” to the world of visual impairments. Although I’d experienced my own visual impairment as a personal reality, I didn’t notice that it occurred on a much larger scale until witnessing this firsthand at the eye clinic. From the stream of patients waiting at the door, I realized that providing free diagnostic services was a critical aspect of the public health chain; if patients were aware that they had a condition, they would be better-informed about eye disorders and be more likely to seek professional care in the future.
Hence, over the next several months, I continued to volunteer at the clinic whenever I could, but not nearly as often as I’d like to have; the four-hour round trip between Austin and San Antonio meant that I could only come on certain weekends, and often, I found that my debate team’s schedule often clashed with my plans. I began exploring other options: Were there other ways I could help in diagnosing visual impairments?
For me, I soon realized that one way I could do so was through computer programming. Ever since my childhood, programming has been an art that enables me to contribute to the world around me in a meaningful way. Over the years, I have become proficient in Java, C, C++, and plenty of other languages. My passion for programming has grown from writing a few simple lines of code to creating programs and apps for my school and community, such as a 3-D world simulator, scripts to analyze gene transcription data, and more recently, an evidence collector for debate. I love the feeling of problems clicking in my head as I work to a solution. While programming one evening, I had the idea to create a digital tool that would provide the functionality of the clinic’s screening tools in an app format.
I began to delve into this topic to research if something similar had already been done. Indeed, I found several apps which claimed to diagnose refractive errors. To my surprise, however, I came across a recent study revealing that such iPhone apps weren’t nearly as accurate as advertised, which could potentially lead to misdiagnosis. In addition, in the Android marketplace, the wide variety of screen resolutions and device manufacturers meant that Android apps were often incorrect as well. However, even if these apps were diagnostically accurate, many still needed features for use beyond the clinical setting as tools for the general public.
I felt that if one were to make an app that filled in these “holes”, it would fulfill the needs of a large population. Hence, over the next several months, I began programming a prototype to do just this, focusing on a few core features:
- Diagnostic accuracy: The visual acuity measurements from the app should be medically accurate by using industry standards as to not misdiagnose patients.
- No internet usage: Internet access is often unavailable in rural/remote regions, so the app should work both offline and online.
- Auditory guides: If users are too visually impaired to read the instructions, they may listen to auditory guides instead.
- Device compatibility: Many low-income families can’t afford the latest phone models, so having older device compatibility is a must.
- Translations: English often isn’t the first language of disadvantaged groups, so the app should accommodate their needs.
With these features in mind, I eagerly learned how to program for Android and iOS using the Java and Swift programming languages. Within a few months, I had created a working prototype for my vision.
You can download OcularCheck on Android and iOS app stores free-of-charge.
To me, developing this app was an internally rewarding process, as I was able to dedicate my passions towards a greater cause; I became inspired to continue this venture in public health. As I continued researching visual impairments, I found out that of the 2.2 billion people who are visually impaired, 90% of them live in developing countries, where one may not have access to the same quality of care as one would in the United States. Hence, I decided to focus OcularCheck on mitigating the factors responsible for visual health inequalities.
- Awareness: Due to the gradual onset of myopia, many families may not be aware of its presence until the condition worsens—however, detecting its early onset is crucial to preventing further progression. However, OcularCheck tries to make diagnosis a simple process by providing an easy-to-use tool that can be used to regularly check for refractive errors.
- Distance: People may have to travel long distances for care, which can be difficult for remote and rural regions. As OcularCheck can be used from any location, worldwide, families no longer need to worry about the burden of travel.
- Cost: Diagnosis and treatment can be cost-prohibitive for low-income households, so OcularCheck provides accurate visual acuity measurements for free.
This journey has been incredibly rewarding for me, and I’ve learned so much about the world of public health. In my next post, I will continue sharing my story of developing OcularCheck by describing how the app is being used today.