Thesis

CBF Track: Implementation of mHealth Monitoring System using IoT Enabled Cloud Computing

This project presents a novel application of cloud computing enabled by internet of things (IoT) in monitoring parameters affecting cerebral blood flow (CBF) which is the movement of blood through the network of cerebral arteries and veins supplying the brain. The example design implemented in this proposal can be easily replaced with similar applications to generalize the concept offered in our work. This enables healthcare professionals to have pervasive access to the processed medical data (in this case cerebral blood flow) of patients during their hospitalization process. Our scheme proposes a design in which the cerebral circulation data is captured using sensors connected to Raspberry Pi and then pushed to the cloud, stored in database, later processed, and analyzed. Results then will be retrieved and distributed to medical professionals via Android mobile application. This application is designed to keep track of cerebral circulation and process the data obtained through the sensors. Anomalies such as oxygen imbalance, internal bleeding, swelling due to an increase of water, and disturbance in blood flow that can lead to serious health issues can be detected. We have used Amazon web services (AWS) cloud platform to perform cloud services. Our approach is inspired by Amazon Simple Beer Service (SBS) [10]; a cloud-connected kegerator; that sends sensor data (beer flow and in our case cerebral circulation data flow) to AWS [5]. SBS publishes sensor data collected by an IoT enabled device (Raspberry Pi) to an AWS application program interface (API) gateway over Hypertext Transfer Protocol Secure (HTTPS). So, all the medical data registered with the application is stored securely in the AWS cloud using DynamoDB as the database and the raw data get processed inside cloud and activate real time system alarms based on the abnormal variations in vital parameters to medical professionals via android application. To the best of our knowledge this is the first scheme offered to replace the manual process of monitoring CBF using biomedical electronic devices

Relationships

Items