Non Invasive Glucometer

Artificial vision device for glucose measurement capable of classifying glucose levels with greater assertiveness than operating puncture glucometers.

Our Technology

Invest in your health


Our new non-invasive glucometer uses Near-Infrared Spectroscopy (NIR) and applies computer vision to identify glucose information from the interaction of Near-Infrared Light passing through a in vivo tissue, in this case a finger.


NIR has become popular for monitoring physiological parameters because provides simple, economical and safe monitoring. Since no specific reagents are required for measurement, repetitive analysis is thus possible at low cost.


Our NIR technology can pass through different skin layers to subcutaneous space and obtain complex data. It is a spectroscopic method which uses radiation in the infrared region of the electromagnetic spectrum (700–1100nm).


As the light interacts with tissue, it is partially absorbed and scattered due to interaction with chromophores. Such light is then processed using optical systems, statistical analysis and deep learning algorithms, which allows for non-invasive glucose measurement.

If you can measure it, you can control it.

The Problem

Type II Diabetes is one of the most significant problems worldwide. It imposes a heavy global burden on public health as well as socio-economic development. It is estimated that 6 out of 10 people with diabetes do not follow the indications of their physicians due to the pain caused by invasive methods such as conventional glucometers. Lack of continuity in treatment is the major cause of catastrophic deterioration. In addition, the cost of care for diabetes is unsustainable in the medium term, and the disease is growing at an unmanageable rate.

The Solution

A. Establish a mass prevention model based on a non-invasive medical device, which, as a preventive traffic light, provides individual measurement information that can be used and monitored by all people affiliated to public or private healthcare institutions. These metrics offer reliable information on statistical glucose levels, as well as reduction targets, to make prevention commitments achievable by companies and workers in the short term.

B. Establish an individual diabetes prevention model based on a non-invasive device that accurately detects blood sugar in seconds and can be used by people that are susceptible to type II diabetes or currently those who have the disease. It will offer reliable glucose readings and will be interconnected with a physician for remote monitoring.

Help us create a healthier future.


Prediabetics in the U.S.

It is estimated that 1 out of 3 adults has prediabetes, that would mean that 80 million adults in the U.S. may develop a serious condition. All of them could benefit greatly from easy to deploy prevention models.


Diabetics in the U.S.

As of 2020, there were more than 34 million people in the U.S. with diabetes, however, it is estimated that close to 10 million people may be undiagnosed and unaware of their condition. The numbers could be much more accurate if diagnosis were more accessible.


Cost of diagnosis in the U.S.

The cost for diabetes diagnosis in the U.S. was close to $ 245 billion dollars in 2012 and has been rising yearly on account of new cases. If more accesible diagnostic devices were to be implemented, the cost could decrease drastically.


Diabetics in 2030

It is estimated that 578 million people in the world will have diabetes by 2030, that number is expected to rise to 700 million by 2045. We are in urgent need of massive prevention campaigns through improved glucose measurement.

Credentials and Validations


Validation protocol with the Mexican National Metrology Center for observing diluted glucose.


Categorized as a strategic project for Mexico City’s Science and Technology Department.


Joint validation protocols with the Mexican Social Security Institute for glucose identification.


Validation protocols with Mexico City’s Health Department for glucose measurement.


Validation protocol with the Mexican National Institute for Medical Sciences and Nutrition for glucose observation.


Project selection and funding by the Mexican National Council for Science and Technology.

Get in touch

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