Accofrisk was founded in 2008 by Dr.Oleg Tikhonenko. The startup began its development with a clear idea to simplify the lives of people with diabetes, and now the work of our team and the company's movement forward is based on research into innovative methods of measuring human health indicators and the development of devices based on these methods.
The company's flagship product is a smartwatch for non-invasive monitoring of major body systems, and the company plans to develop aline of devices and solutions in the areas of health monitoring,diabetes prevention, healthy aging and mass measurement.
The core of our products is ARIA artificial intelligence based on aneural network trained on health monitoring data from over 2 million people.
The company operates in the global market through representative offices and a network of partners. To this point, about 600,000 devices have been sold in China.
Electronic Research Conference. International Scientific Solutions 2022.
February 9, 2022. Ney York.
Interuniversity Scientific Congress "Higher School: Scientific Research".
January 9, 2023. Moscow.
16
YEARS OF WORK
10
PATENTS
5
PARTNERS
3
COUNTRIES OF WORK
"Our team is committed to creating a Digital Health Tracker for the user, where data and AI will tell you about abnormalities before symptoms of disease appear, and the diagnosis will be made at the first visit to the doctor without additional tests."
ACCOFRISK FOUNDER, Dr.OLEG TIKHONENKO.
A form factor for those who do not wear watches (30% of people) but want to monitor their health.
A budget model with simplified functionality to replace traditional fitness bracelets.
Multi-person data measurement terminal for discrete periodic measurements.
Accofrisk Health platform launch with clinic functionality, open API and patient portal.
We invite companies interested in sellingAccofrisk smart watches and other devices of the company or inmanufacturing devices under their own brand under the White Labelmodel.
For manufacturers of electronics and gadgets we offerintegration of our technologies into developed devices under theOriginal equipment manufacturer model.
We are ready to discuss the exchange of health parametermeasurement data with those interested in the development ofinformation systems based on artificial intelligence.
21 top AI (Artificial Intelligence) Companies and Startups in Abu Dhabi in 2024.
We became speakers at the conference. The event was attended by all those interested in artificial intelligence, healthcare, preventive and predictive medicine, and emerging technologies. The event brought together leading experts and developers implementing machine learning technologies that will shape the future of AI diagnostics and innovation. The event was attended by individuals and representatives from the United States, Latin America, the Caribbean, Europe, the Middle East and Asia.
Accofrisk's AI measurement performance was tested at the Chongqing Red Cross Hospital (Jiangbei County People's Hospital) under the supervision of Prof. Liang. The results confirm that the measurements meet the requirements set forth in the “Chinese Guideline on Clinical Application of Blood Glucose Monitoring” (2021 edition).
This paper proposes a method for non-invasive blood sugar determination by arterial pulse. A technique has been developed to collect volumetric pulse wave signal and thermal metabolic signal at the radial artery of the subject's wrist. This method will allow everyone to monitor blood glucose levels according to a personalized effective range of blood glucose levels based on a scientific approach.
This paper proposes a method for non-invasive blood sugar determination by arterial pulse. A technique has been developed to collect volumetric pulse wave signal and thermal metabolic signal at the radial artery of the subject's wrist. This method will allow everyone to monitor blood glucose levels according to a personalized effective range of blood glucose levels based on a scientific approach.
The article is devoted to the objectification of pulse diagnostics, methods of extraction and analysis of pulse parameters and pulse signal processing, to explain morphological changes in various pulse wave forms, based on optical methods and the use of wearable devices working with photoplethysmography to solve these problems.
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