Non Invasive Glucose Measurement

Revolutionizing wellness through non invasive technology that can measure blood glucose levels, oxygen saturation and heart rate accurately and affordably using light.

Our Technology

Near Infrared Spectroscopy

Spectroscopy is a branch of physics that deals with the electromagnetic radiation that is absorbed, dispersed, reflected and transmitted by matter. It can be used to analyze different components that can’t be identified or studied through simpler visual processes. We use Near Infrared Spectroscopy to identify the energy footprint of glucose and other biochemical analytes.

Computer Vision

Computer vision is a field of Artificial Intelligence, which uses self-training Machine Learning algorithms (specifically Deep Learning or Neural Networks) to enable computers and systems to derive meaningful information from digital images, videos and other visual inputs. We use Computer Vision to identify glucose levels in live tissue images by processing the image under different parameters.

Recommendation Engine

Recommendation Engines are an application of Machine Learning algorithms that allow to discover trends within relatable data sets. Once we have identified and organized data from our users and their glucose level readings, we correlate their values with external data sets that provide us with the possibility to generate health recommendations according to user preferences and lifestyles.

Invest in your health

Advanced

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.

Accessible

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.

Accurate

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).

Automated

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.

Get Involved

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. Promote the use of a non-invasive, easy-to-use and affordable device to monitor blood glucose levels in the general population, to improve overall wellness and prevent the proliferation of type II diabetes around the world.

B. Deploy mass prevention campaigns using non-invasive technology to monitor general blood glucose levels through a “traffic light” system, which could provide relevant wellness information to participants and alert public or private healthcare institutions about general health conditions.

Help us create a healthier future.

Prediabetics in the U.S.

96 million adults in the U.S. have pre-diabetes (1 in 3) and may develop a serious condition, furthermore, studies estimate that 8 out of 10 pre-diabetics don’t know they may develop a severe condition. All of them could benefit greatly from easy to deploy prevention models.

Diabetics in the U.S.

As of 2021, there were more than 37 million people in the U.S. with diabetes (1 in 10) however, it is estimated that close to 10 million people may be undiagnosed and unaware of their condition. With simple and regular blood glucose monitoring, the numbers could decrease over time.

Diabetes Related Healthcare Expense

According to the International Diabetes Federation, the healthcare cost associated to diabetes is estimated at a minimum of $966 billion dollars per year. If more accesible prevention devices were to be implemented, the cost could decrease drastically.

Diabetics by 2030

It is estimated that 643 million people in the world will have diabetes by 2030, that number is expected to rise to 783 million by 2045. We are in urgent need of massive prevention campaigns through improved glucose measurement.