Professor leads research on e-senses technology

By Sneha Subhash •

Srika Talanki, sophomore biology major, has a family history of several diseases. She is hopeful for noninvasive technology that could detect them earlier.

“I recently experienced a loss from cancer, and it has deeply impacted me and my family,” Talanki said. “The idea that we could use noninvasive technologies to detect cancer earlier and more accurately gives me a lot of hope for the future.”

Current medical diagnostic tools rely on invasive procedures and costly equipment. However, developing research from NSU College of Computing and Engineering has provided a potential use of e-senses technology, where diagnoses can become as simple as breathing, tasting or seeing. A single device can analyze health through scent, taste and color without any need for needles or complex procedures.

With his research team, José Ramos, professor in the College of Computing and Engineering, has been exploring the use of e-senses technology in medical diagnostics, using three devices: the electronic nose (e-nose), the electronic tongue (e-tongue) and the electronic eyes (e-eyes).

Ramos started his education at the University of Puerto Rico at Mayagüez in civil engineering, before completing both a master’s and Ph.D. at Georgia Institute of Technology in hydrosystems engineering.

“E-senses technology leverages a combination of different instruments to analyze chemical signatures,” Ramos said. “We use an electronic nose, which features eight gas sensors to detect volatile organic compounds, much like a fingerprint for odors.”

The electronic nose works by capturing data from these sensors, which are then processed to recognize patterns associated with different smells. This data is analyzed using machine learning models to achieve high accuracy in odor detection.

In addition to the electronic nose, Ramos’ research incorporates the electronic tongue and electronic eye. The electronic tongue, equipped with an array of eight electrodes, mimics the human sense of taste through electrochemical analysis. Meanwhile, the electronic eye uses a combination of small spectrometers to analyze color variations, which also feeds into machine learning models for further analysis.

“By combining data from the electronic nose and electronic tongue, we can create a comprehensive machine learning model,” Ramos said.

But the technology is not without its challenges.

One of the primary limitations is the variation in sensor readings due to environmental factors like temperature and humidity. Newer smart sensors have been developed to address these issues, improving the accuracy of the readings.

“The non-invasive nature of these tests is a major advantage,” Ramos said. “Patients undergo less stress and discomfort compared to traditional methods, and the lower cost of the technology means that it can be integrated into more diagnostic settings.”

The use of this technology is currently undergoing further research and development.