A context-aware, predictive and protective approach for wellness monitoring of cardiac patients

Cardiovascular diseases are major cause of deaths throughout the world. In this work, we develop a context-aware system for wellness monitoring of older adults who leave alone in home and suffers from cardiac disease. The focus here is the integration of social networking services with conventional remote monitoring services by utilizing a scalable cloud platforms. The goal here is to expand patient's social linkage by identifying similarity in his/her cardiac conditions. Here we build a cloud-oriented context-aware model that captures health parameters using modern fit bit device and ECG sensors. The raw data are sent the cloud platforms provided by Amazon Web Service (AWS) where data is converted to high level context. Using social networks this high level context information is send to patient's friends, family and doctors who are interested to know about his/her health condition. The interested parties get notified by Facebook when the context-aware system detects any changes. That is, using this platform a cardiac patient who live alone and need continuous monitoring is always get connected with virtual community by means of his/her health information. This is a new model that utilizes the context data generated by wearable sensors to create interesting social networking services. The system is also designed to promote cardiac patients to interact with their community of interest using various context-aware social services. The results obtained for this innovative model show a new approach of wellness monitoring using social networks.