Big Data Project for Heart Health

June 16, 2017 By IdeaConnection

From predicting epidemics and helping to cure diseases to improving quality of life and identifying drug targets, big data is driving healthcare innovation forward.

To capitalize on this potential, a new open innovation project has been launched to help improve heart health diagnosis.

Through the Heart for Heart smartphone app, members of the public are being encouraged to provide their heart rhythm data.  All they have to do is place a finger over their phone’s camera and flash, which will act in a similar fashion to a pulse oximeter.  This is a non-invasive tool that measures light absorption by the blood.

With regards to the smartphone and the app, more blood in a person’s finger will absorb more light and this indicates a higher heart rate. Nifty algorithms in the app are then able to use this to detect the user’s heartbeat.

World’s Largest Heart Health Initiative

The creators of the app need a lot of data and they are hoping this open innovation effort will become the world’s largest heart health initiative.  The overall aim is to improve understanding of atrial fibrilation (also called AFib), which is an irregular heartbeat (arrhythmia).  This is the second leading cause of strokes in the US and is responsible for 250,000 sudden deaths. Furthermore, around one million patients are undiagnosed.

In addition to providing new knowledge of the heart condition, the patient-generated data will improve diagnosis and treatment and better help doctors to diagnose AFib on the spot.

For more information about the app and how you can help the initiative, click here.

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Reader Comments

We work on personalized skincare products and we use physical and biochemical skin measurements, as well as other information, e.g., age, sex, questionnaire, to determine the optimal skincare formula. We can identify the parameters of importance, performa all range of statistical analysis of big data and finally produce a decision support system which will be used for predictive analysis. In doing so we employ machine learning algorithms. We use R programming language, however, if needed we could use other language or package, like Matlab. I look forward to hearing from you.
Posted by Viktor Popov on June 22, 2017

can you give the data details for the same to go with ??
Posted by Ganesh on June 22, 2017

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