I AM HEALTHY ANALYTICS (IAHA)

Automatic health analysis system

Marina Stepanenko

project founder

I'm 36, I'm from Moldova, my main activity is graphic design and volunteering to help animals

So let me introduce my project

I AM HEALTHY ANALYTICS (IAHA)

Automatic health analysis system

From a technological point of view, this is a system for automated analysis of ECG recorded using Apple watch, capable of detecting T-wave microvolt alternans and other cardiac events. The low quality of ECG recording is compensated by the large volume of data coming from the wearable device.
The user part consists of subscription app for smartphones and Apple watch, which sends the owner his status in the form of messages like “Your heart looks quite healthy today!” or "Perhaps you should take care of your health and visit a doctor"

Having identified a suspicious cardiac event

the system saves the ECG section and a commentary on its automatic interpretation for subsequent analysis by the attending physician, who makes the final decision on further examination.

The application can also automatically send similar ECG sections to the smartphone to the attending physician and the user’s relatives. Or even call an ambulance using the geolocation of the owner of the apple watch if system suspects an ischemic stroke, loss of consciousness and other emergency conditions displayed on the ECG

Who might be interested

in the application

WHICH DOES NOT AIM TO MAKE A DIAGNOSIS OR CLARIFY IT

People with diagnosed cardiovascular diseases or at risk for cardiovascular diseases
People caring for elderly relatives
Athletes monitoring their health
People concerned about their health in general
People suffering from poor health
Young women with chest pain
People suffering from paroxysmal arrhythmias

Opportunities for app monetization

In addition to the monthly subscription

the project is great for advertising both commercial medical centers and third-party applications dedicated to healthy eating and exercise

Project development prospects

Since the system is capable of self-improvement thanks to machine learning, analyzing incoming ECG data, with each new user the accuracy of analyzing ECG events in general and determining microvoltage T-wave alternans in particular will only increase.

Moreover, in the future, big data analytics of users’ ECGs, taking into account their health status and lifestyle (with the users’ consent, of course), will make it possible, with the help of neural networks, to find completely new markers of health and longevity, providing medical organizations with material and direction for relevant scientific research

Stage of project implementation to date

Using databases and elements of software products from the open resource PhysioNet, the leading technical specialist of the project created a web version of the system that automatically analyzes the downloaded ECG of a registered user and successfully identifies microvolt T-wave alternans using the MMA method

The PhysioNet platform is managed by members of the MIT Laboratory for Computational Physiology. The other core laboratory of the PhysioNet Resource is the Margret and H.A. Rey Institute for Nonlinear Dynamics at Beth Israel Deaconess Medical Center

Fragments of MMA analysis of MTWA of loaded ECGs

Project development prospects

More information about the project can be found in my detailed presentation in Loom format (left).

The presentation is also available
in pdf-format.

Here you can see an example
of how the algorithm works on test ECGs

At the moment the project is financed

exclusively from my personal funds which are obviously not enough to complete it

Tasks that cannot be implemented without third-party funding:

  • Development of an application for smartphones and Apple watch
  • Providing significant computing power for storing and processing large amounts of data
  • Expanding the team of technical specialists

Our Team

Marina Stepanenko

Project founder

Andrey Beletsky

leading technical specialist

Thank you

for your attention

IAHA,  64, Str. Sfânta Vineri, Chisinau, Moldova

[email protected]
+373 (69) 800 437