We are developing an actionable wrinkle tracker to dynamically analyze facial wrinkles and test the effects of various treatments and interventions in the most scientific and professional way.
Our project addresses a primal human need
People usually accept ageing as a process that they can’t control on a biological level. However, they want to look young and beautiful, but currently there is no way to track ageing objectively.
People talk about fighting aging all the time, but there is no credible set of aging biomarkers that can be used to track the effects of various treatments.
We would like to contribute to development of these biomarkers. Some of the members of our team are dedicated to development of these biomarkers on all levels: molecular, cellular, tissue-level and organismal level using massive biological databases.
Your face is one of the best indicators other humans use to guess your age. In fact, machines can even guess your age more accurately when looking at your picture than when looking at the biochemical composition of your blood.
RYNKL is a wrinkle analysis app. It is an artificial intelligence which cares about your looks and helps you adjust your lifestyle to look younger.
RYNKL app will allow you to take pictures of your face in a standardized way, analyze the “wrinkleness” of your face and see how it changes in response to the various lifestyle interventions like losing or gaining weight, drug and supplement regimens, skin creams and cosmetics products.
This app will eliminate the need to search for pictures from previous years to see how your face has changed over time and will track only the most important areas of your face that affect our perception of age.
We are using both parametric algorithms and deep learning methods to analyze the “wrinkly” areas of your face and evaluate the number and intensity of your wrinkles before and after trying certain treatments or lifestyle adjustments.
We would like your support to fund the last mile of the IOS App, including development, hosting, computational resources, and research required to improve the accuracy of the parametric wrinkle tracking algorithm.
We are Youth Laboratories, the team of IT, biogerontology and deep learning experts, who are dedicated to developing effective interventions to keeping people young, healthy and beautiful and we would like to start from your wrinkles.
Alexey Shevtsov, CEO
Recent project: Deep Knowledge Ventures
Listen to Alexey:
Alex Zhavoronkov, Biogerontology expert
- Insilico Medicine, one of the most active and promising companies in aging research
- AgingPortfolio.ORG - http://www.ncbi.nlm.nih.gov/pubmed/21799912
- AgingChart.ORG - http://www.ncbi.nlm.nih.gov/pubmed/26602690
- Geroprotectors.ORG - http://www.ncbi.nlm.nih.gov/pubmed/2634291
- Biogerontology Research Foundation
Listen to Alex:
Konstantin Kiselev, CTO
- VimpelCom - world’s TOP-10 telecom operator (lead machine learning and big data developer)
Theoretical physics and mathematics graduate of MSU
Listen to Konstantin:
Olga Kairova, MBA, Business development
- Deloitte - one of the BIG4 - world's leading audit & consulting services companies
- HealthExtention - a community working to extend healthy life
- MEDESK - cloud healthcare platform
- Internet Initiatives Development Fund - one of the biggest startup accelerators in Europe
Listen to Olga:
Anastasia Georgievskaya, Robot tutor
Graduate of bioengineering department of MSU
Listen to Anastasia:
Jane Schastnaya, Research scientist
Hair and beauty products, Insilico Medicine, www.agingkills.com
Listen to Jane:
We use several stages to recognize and estimate the level of wrinkles on a face.
The first one is a determination of general facial zones (forehead, eyes, cheeks, mouth) by a few machine learning algorithms.
The second one is recognizing the areas where wrinkles are most likely located in each facial zone by the combination of image processing transformations and filtering.
Next the machine learning algorithm is applied to calculate wrinkle map.
The final step is the calculation of wrinkle score - the complex measure of size and quantity of wrinkles. The score function also has BMI (body mass index) in the input parameters.
We are now researching deep learning methods to increase the precision of wrinkle recognition.
The final product is the wrinkle tracking app that will help reverse wrinkles in most scientific and professional way and will help to:
- track wrinkles over time
- see the effect of various treatments before and after
- reverse the main signs of facial aging
- look young and beautiful with the power of mobile phone
The further app versions will include treatment suggestions and friending function.
Project story before Kickstarter
Our story started in August 2015, when Alexey was looking for the team to realize his ideas, influenced by Alex and other brilliant biogerontologists. Alexey met Konstantin at the deep learning hackathon Deephack.me. They then started to form the team and met Olga, with Anastasia later joining the team.
As of now we have launched Beauty.AI - the first international beauty contest judged by artificial intelligence, in which contestants enter using a mobile app and data science teams from all over the world can submit algorithms to evaluate the many criteria linked to the perception of human beauty, "youthfulness" for their own age, and many other parameters.
This platform is also a scientific experiment, helping to find the best health analytic solutions. This is made for two main reasons:
1. to train & test machine learning models,
2. to involve more people and to attract attention to computer vision and deep learning technologies in the skin health analysis.
The second part of the project is launching a series of apps that allow people to track the effects of various products (including cosmetics) on their face and quickly understand their dynamics using the impartial opinion of deep learning algorithms.
Our aim is to provide best in class mobile apps to monitor skin health so that our users can choose the most suitable skin treatments.
We have started with wrinkles and developed an algorithm for wrinkle analysis - the core of the RYNKL app. We are now developing the RYNKL app for Android and starting development for IOS.
We need your support on this last mile with RYNKL. We also invite you to join us in this challenging journey and help our effort to spread this cutting-edge technological solutions around the world.
Please support our team. We are genuinely committed to aging research and we will be contributing to some of the most promising research groups worldwide to bring you even more solutions against wrinkles and aging.
Risks and challenges
App development. Once the campaign is successful, the funds will go to pay for app development. Our estimation is completion of the app by January, 25. However, as in all development work, there may be unforeseen delays, but if this happens we will surely overcome it.
Algorithm development. Our technology is extremely new and we are testing our wrinkle recognition algorithm. While there can be some delays with it, but we will definitely overcome them within reasonable amount of time.
As all new products going to market, we face some uncertainty. We will meet a lot of market challenges, from user retention to exponential growth. Still, these all are normal challenges, and you, as our early adopter, will have fun of being with us on this thrilling journey. So welcome to being in the thick of things.
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