Wireless Healthcare reports that startup Biosigns Technologies successfully validated the accuracy of their noninvasive continuous glucose meter in a study including 120 participants with blood glucose levels ranging between 3.5 and 27.4 mmol/L. The Biosign device, called the UFIT, also measures heart rate and blood pressure, but the released study results do not include accuracy data for those additional parameters. The unit is apparently part of a wireless remote patient monitor, providing access to patient data for patients, physicians, pharmacists, insurers and pharmaceutical companies.
UFIT(R), which uses a non-invasive, web-enabled device that straps around a patient’s wrist, responds to the need for an easy-to-use self-monitoring system that reliably and simultaneously captures key data on heart and blood, including heart rate, blood pressure, blood oxygen and blood glucose. The system is intended to optimize the management of chronic diseases such as high blood pressure, heart disease and diabetes.
The developments at the MeMeA workshop represent important steps in enabling UFIT(R) to comprehensively serve the multi-billion dollar personal health monitoring market. Ninety percent of chronic disease management takes place in the home.
Uh, actually the personal health monitoring market is not a multi-billion dollar market, since there’s no reimbursement for the kind of monitoring Biosigns describes. But the device sounds pretty cool.
This Biosign-sponsored study assumed that the arterial pulse, a rich source of clinically relevant information (e.g., rate, rhythm, pattern, pressure and oxygen), could also provide information on blood glucose.The study gathered glucose measurements from 120 participants with blood glucose levels ranging between 3.5 and 27.4 mmol/L.
The results show a tight statistical correlation (0.998, Pearson substantial equivalence) between UFIT(R) and laboratory analysis of blood glucose, with a low (1.63%) average of the mean percent difference between the UFIT(R) measurements and the laboratory analysis. The correlation was obtained post-hoc by comparing a feature extracted from the radial artery pulse with laboratory blood glucose data. The methodology resembles that used to correlate HbA1C with the direct measurements of glucose in drawn blood.
There is no discussion of the number of samples compared to the UFIT sensor. Sorry, no photos could be found on the device – perhaps someone can send me one?