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The Cross-platform Application for Arrhythmia Detection

Background and Motivation: 

Cardiovascular diseases are the most significant reason of death in the world. Continuous monitoring of heart function and automatic detection of arrhythmias in 24/7 manner brings new opportunities to the healthcare. Holter monitor used in Russian medicine is very uncomfortable since it is a heavy device with a lot of electrodes and it requires skilled doctor’s help to set up them correctly. Consequently it can’t be used for long-term monitoring.

The more convenient solution is to use portable digital monitors. In this case all computational tasks can be assigned to the smartphones.
Project Summary: 

Within the projects the application for detection patient’s cardiac abnormalities is developed. If some kind of arrhythmia is detected, the application submits pieces of patient’s electrocardiogram to the doctor and alarms emergency services if it is needed. The application is originally developed and tested for smartphones with Symbian OS.

Project goals and future research directions: 
<ol> <li>Implementation of the arrhythmia detection algorithms and improvement to make them more suitable for limitations of mobile phones.</li> <li>detection of heart arrhythmias will be introduce&nbsp; in clinical</li> <li>should provide the transmission cardio data to hospital database.</li> <li>in the future it is going to port to other mobile platforms (Harmattan, Android, Windows Phone) and desktops (Windows, Linux, Mac).</li> </ol>
List of team members and their organizations: 

Alexander V. Borodin (aborod@cs.petrsu.ru),

Nikolay Lebedev (lebedev@cs.petrsu.ru),

Artem A. Pogorelov (pogorelo@cs.petrsu.ru),

Artem A. Rudenya (rudenya@cs.petrsu.ru),

Yuliya V. Zavyalova (yzavyalo@cs.petrsu.ru),

Department of Computer Science, Petrozavodsk State University (PetrSU) Lenin St. 33, Petrozavodsk, 185910, Russia
Status: 
Active
Project Timeline and Expected Deliverables: 

February – April 2012. Preparing the demo of an application for ECG morphology recognition.

May – October 2012. Implementation of initial algorithms of R peaks detection and related arrhythmias. Publication of the beta version of the application to the Nokia Store.

November 2012 – March 2013. Improvement the quality of ECG peaks detection. Clinical tests with real patients. Adding ventricular arrhythmias detection capabilities.

April – October 2013. Development of server tools and integration with electronic patient cards.

Final deadline: 
Friday, April 24, 2015 (All day)
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