SELFLIFE: AN ANDROID BASED HEALTHCARE SYSTEM

Abstract

Mobile applications for activity monitoring have potential of efficient improvement in the field of healthcare. The monitoring of all fitness activity should be easy for user. Generally monitoring required special sensor devices that are affixed at different locations, so these are not suitable for daily usage. Movement monitoring based on accelerometer enables to use of smart phones for monitoring daily activity. So carrying a smart phone in a pocket will provide all information of the performed activity by user (Gerald et al. 2009). In this project, we have developed the method, and using that method to we are detecting daily activities like walking, resting, running, sleeping or standing. It is difficult to affix multiple sensors at different locations of body. To reduce the problems for users, we present in this project, a flexible framework in terms of an mobile application and a web based tool that measures the data and provide analysis in graphical form. We have worked on distinguishing and monitoring some basic human activities such as walking, running etc. Since we plan to implement the system mostly for those who are fitness aware or those who want to research in this area, simplicity of the application is very important. We also focused for researchers who are working in the field of some diseases like neurodegenerative disease (Parkinson’s disease). So here, we have successfully implemented an algorithm that would not require the acceleration sensor to be fixed in a specific position (the smart phone itself in our application). The application developed in this project is hosted at http://genomeinformatics.dtu.ac.in/selflife.