Know Labs Study Published in IEEE Sensors Journal

Know Labs, Inc. (NYSE American: KNW), a leading developer of non-invasive medical diagnostic technology, today announced the publication of its peer-reviewed study in IEEE Sensors Journal titled, “Non-Invasive Blood Glucose Measurement Using RF Spectroscopy and a lightGBM AI Model.” IEEE Sensors is the leading scientific journal in the U.S. that focuses on the theory, design, fabrication and applications of sensing devices, with an emphasis on emerging sensor innovations.

The article details historical developments and limitations with RF-based sensing technologies, and the distinctiveness of Know Labs’ sensor architecture and trade-secret prediction machine learning algorithm. Where most other RF-based non-invasive blood glucose monitoring technologies focus on a narrow band of frequencies, Know Labs’ RF sensing device applies broadband dielectric spectroscopy – rapidly scanning a large range of RF frequencies and recording voltage values detected at each frequency – to quantify blood glucose continuously. This technique enables Know Labs to use thousands of data points to identify and measure the material being scanned, rather than being limited to a small number of “resonant” frequencies used in resonance techniques.

“I am very proud of the Know Labs technical team’s publication of their peer-reviewed work in the prestigious IEEE Sensors Journal, which asserts the novelty of our approach to developing the next generation of blood glucose monitoring devices,” said Ron Erickson, CEO and Chairman at Know Labs. “We will continue to execute on our rigorous research and development roadmap to clinically validate our technology on our mission to deliver accurate, affordable and accessible non-invasive diabetes management solutions.”

Results from this study, conducted in a lab setting using a first generation device, were first announced in May 2023 and published as a preprint in MedRxiv. Since these results, Know Labs has published several studies that indicate improved accuracy of its RF sensor within similar clinical research protocols among healthy participants using a continuous glucose monitor (CGM) comparator, as well as within protocols validating the medical application of its technology among people with diabetes and using venous blood as a comparative reference.