Researchers at the University of Washington have developed a new method of using smartphone images to detect harmful bacteria on human skin and also in the mouth.
In a recently published paper, a new method was shown that can identify microbes and skin that are responsible for acne and not letting wounds heal quickly. The system can also detect bacteria in the oral cavity that leads to gingivitis and dental plaque.
The team of researchers from the University of Washington was led by Ruikand Wang, Professor of bioengineering and ophthalmology. The team combined a smartphone with the image-processing tech to eliminate bacteria from images clicked by a normal smartphone camera.
Cheaper and quicker method
The team believes this method will be relatively cheaper and quick and can be used at home to check for harmful bacteria on the skin and inside the mouth. Wang believes the bacteria on the skin and mouth can slow down the process of wound healing and also aggravate tooth decay.
Since smartphones are very easily accessible, the team wanted to build a low-cost and easy-to-use tool that people can use to check bacteria. Usually, it’s not possible to see bacteria with conventional smartphone images.
Wang notes that normal smartphone cameras are RGB units that funnel different wavelengths of light in red, green, and blue. However, bacteria emit colors beyond RGB, making the smartphone cameras miss them.
Simple yet very effective
The team attached a 3D-printed ring that packed 10 LED black lights around the case’s camera opening. The LED lights excite porphyrins bacteria molecules that cause them to emit red signals, which are captured by the smartphone camera.
Other components such as oily molecules and proteins produced by the body are not visible in the LED lights. Wang says the best part of the new tech is that they can see different components simultaneously.
If the person has bacteria producing a different byproduct, and you want to find it, the same image can be used to look for it using the new approach. This wasn’t possible with conventional imaging systems that are currently in use.
