The main issue we address in our solution is to use data in order to help improve human health. The formula is simple ; parameterizing the data we calculate the risk of developing a heart related disease as a number in the range 0-26. This helps people and hospitals in early diagnostication and creates a possibility for tracking their health progress.
We named our application Pulsar, inspired by pulsating stars and connecting it to pulse. The applications and the opportunities can be many, from hospitals which can use the application via a moderator doing the survey en masse , to research centers around the world which can use data we provide ( of course taking into consideration GDPR and MDM) to help improve the treatment of these diseases. We plan to extend our solution to other illnesses and propose it to hospitals as a form of health analysis for them.
Several health conditions, your lifestyle, your age and family history can increase your risk for heart disease. These are called risk factors. About half of all Americans(47%) have at least one of the three key risk factors for heart disease: high blood pressure, high cholesterol, and smoking 1
According to this other resource provided by NASA 2, the number one factor of deaths from 2009 amongst USA population was by heart diseases. Following the measures stated here to help prevent health diseases 3 and here 4 our solution tends to be a zero-cost solution in this field.
Our application goals:
Registers the above graphics in a tabular data.
Has an integrated survey to get the data by questioning people taking the test.
Shows the risk result via a widget/mail by calculating the risk according to the algorithm.
Offers a moderator section to propose it to researchers who want to test a number of individuals at the same time.
Helps keep track of health status.
It is an easy and extensible way for hospitals to use in evaluating health of their patients.
Our application steps:
First page: (the factors we take into consideration)
Survey (5 questions/factors we take into consideration)
2. Smoker/Non smoker
4. Systolic blood pressure
After gathering the data of the survey we use our algorithm to find the risk of developing a heart-related disease.
The algorithm we use is described in this graph 5
The risk evaluation is shown at the end in form of a widget (by clicking get result button)
As shown in the widget there are three levels of risk:
Minimal: evaluated from 0-4 (green color)
Medium: evaluated from 4-14 (yellow color)
High: evaluated from 14-26 (red color)
Our code and contact:
Github repository: https://github.com/loridacito/healthcalculator/
Web application page: http://22.214.171.124:7000/index
Test users: email@example.com/testuser1
SpaceApps is a NASA incubator innovation program.