The Washington State University’s researchers have recently established a multi channel smartphone spectrometer that tracks a known cancer biomarker, offering a laboratory-grade authenticity in the palm of the clinicians’ hands.
Portable diagnoses in the office physician, ambulance and rural places are potential uses for the mobile device, which gives the similar quality results as much more costly bio-detection technologies utilized in laboratories, but at a fraction of the price—$150 for the smartphone-based optical sensor.
“In contrast to the standard laboratory tools and instruments, the outcomes sufficiently indicated that this multi channel smartphone spectrometer can acquire the comparative analysis detection limits, precision and sensitivity,” conclude researchers in the journal Biosensors and Bioelectronics. “We envision that this multi channel smartphone optical biosensor will be helpful in high-throughput point-of-care diagnostics with its minimizing size, light weight, low-price and information transmission function.”
While other smartphone-based spectrometers can just measure a single sample at one time, the multi-channel spectrometer established with partial funding from the National Science Foundation can measure as many as 8 different samples at once utilizing a common test known as ELISA—or colorimetric test enzyme-linked immune sorbent assay—and the smartphone’s camera sensor that recognizes antibodies and color change as cancer/disease markers.
“The spectrometer would be particularly helpful in clinics and hospitals that have a major number of samples without on-site labs, or for doctors who practice in foreign countries or in remote places,” claims Lei Li, assistant professor in WSU’s School of Mechanical and Materials Engineering. “They cannot carry the entire lab with them. They require portable and effective device.”
Despite the fact that researchers just tested the multi channel smartphone spectrometer with standard lab-controlled samples, they assert that their instrument has been up to 99% correct and are looking to determine it in real-world settings.
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