Nizhny Novgorod Scientists Patent an App to Measure Brain Age
The tool can assess how fast the brain is aging in about 15 minutes and flag early signs of cognitive decline. Its creators say the model’s accuracy is comparable to MRI- and EEG-based approaches.
Population aging is accelerating worldwide. By 2050, more than two billion people will be over the age of 60, up from 841 million in 2013. By 2047, older adults are expected to outnumber children globally.
More than 46 million people worldwide are living with cognitive impairment, placing a growing burden on healthcare systems, social services, and informal care networks. This is why modern medicine increasingly focuses on early diagnosis. Interventions are most effective when they begin early, before decline accelerates.
A Russian Approach to Measuring Cognitive Aging
The brain aging assessment app was developed by a team from the AI Research Center and the Research Institute of Aging Biology at Lobachevsky State University of Nizhny Novgorod (NNGU) as part of the project Mnogomernye markery zdorovogo stareniya i aktivnogo dolgoletiya (Multidimensional Markers of Healthy Aging and Active Longevity – Digital Health Passport).
The team secured a patent for the invention “Method for Determining Human Cognitive Age Using Artificial Intelligence,” establishing rights to the methodology. The findings were published in NPJ Aging, a leading international journal focused on aging and age-related diseases.
The paper describes a new approach to predicting cognitive age using psychophysiological testing. Participants complete a series of short tests designed to measure different cognitive functions, including reaction time, cognitive conflict, short-term memory, verbal ability, and both color and spatial perception.
An Algorithm That Measures Memory
At the core of the system is a machine learning model called Cognitive-Age-V, trained on data from more than 1,800 individuals aged 20 to 85. Based on the test results, the model calculates metrics such as average completion time, accuracy rates, mean absolute delta in color campimetry tests, the number of correctly identified words in the Munsterberg matrix, and other indicators.
These features are preprocessed and used to train a regression-based machine learning algorithm that predicts cognitive age. The system integrates results from five short tests assessing memory, attention, logical reasoning, reaction speed, and color perception.
Toward “Cognitive Clocks” in Preventive Medicine
The first version of the system, referred to as Kognitivnye chasy (Cognitive Clocks), was released in test mode on the university’s open platform in 2024. It has since evolved into a fully functional system supported by a growing evidence base and registered intellectual property. Users can complete the assessment in 15–20 minutes and receive a detailed breakdown of their cognitive profile, bringing personalized prevention of neurodegenerative disorders closer to routine practice.
The system is already being introduced into preventive and healthy longevity programs at the state corporation Rosatom and the Federal Medical-Biological Agency of Russia (FMBA), as well as in preventive medicine clinics.
From Lab Research to a Digital Health Product
The Kalykulyator kognitivnogo biologicheskogo vozrasta (Cognitive Biological Age Calculator) illustrates how a university research project can evolve into a practical digital health product. NNGU has been developing a portfolio of solutions in this area and collaborates with the Atlas clinic network. This increases the likelihood of commercialization and supports the transition from laboratory models to deployment in healthcare institutions and preventive medicine services, aligning with broader trends in Russian medtech and AI-driven healthcare.
At this stage, the focus is not on large-scale state rollout but on patenting and applied development at the university level. Still, early screening of cognitive aging using digital tests and AI sits at the intersection of several fast-growing fields, including AI in medicine, preventive care, healthy longevity, and digital biomarkers.
