Smart Health Care wiki
A mobile based Smart health Care system with Smart Analytics
SmartHealthCare focusses on complete heath analysis
the app is divided into three section ECG_tool , Caloriemeter and Food_Tracker .
##ECG Section
the ECG system first takes a survey of patient regarding the patient
like takes alcohol or if some one in family has cardiatic disease etc
after selection the Bluetooth Activity pens up and shows nearby bluet* ooth devices you chose your
- device
and the Live plot if ecg shown (THe ECG plot is not shown here but trust me it works :p)
Food_tracked
This class has not yet been completed as I was still in a dillema about it's effect on UX
it was ntroduced with a vision to give user a pop message daily at night two check some check boxes regarding
a very rough approximatte of food he has taken through out the day so tha t we can get an approximate idea about the
Calorie intake and tah can be compared with the Calories burned via Caloriemeter section and can be compared
to get approximate idea about user's lifestyle and get more idea about his chances of some cardiatic diseases.
And also notifying the user about his habbit and showing a vizualisation of his calories intake vs calories burned.
also predic chances of being fat etc.
##Caloriemeter
measures the Kinetic Energy in calories burned by the user and live ploting
Normal Mode. and a live plot is shown via staticticsview.class of his instantaneoueous Acceraltion data
if the orientation of phone becomes horizontal while in ActivityTracker.class it's assumed that perso is jogging/running
and has fallen and if he didn't waked up in 8-10s a toast message is shown (it can be furhter increased to launch
the Ecg Activity as well as giving some push message to person's relative's that he has fallen)
##Future Vision Food_tracked This class has not yet been completed as I was still in a dillema about it's effect on UX it was ntroduced with a vision to give user a pop message daily at night two check some check boxes regarding a very rough approximatte of food he has taken through out the day so tha t we can get an approximate idea about the Calorie intake and tah can be compared with the Calories burned via Caloriemeter section and can be compared to get approximate idea about user's lifestyle and get more idea about his chances of some cardiatic diseases. And also notifying the user about his habbit and showing a vizualisation of his calories intake vs calories burned. also predic chances of being fat etc. In future also belive to add machine learning analysis too presenly a fuzzy Matrix is integrated to predict the Heart Attack risk but is not implemented in future I plan to add Machine learning analytics