Abstract

This paper 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 by our work. This enables healthcare professionals have ubiquitous access to the processed medical data (in this case cerebral blood flow) of patients during their treatment process. Using cloud computing, accessing data from multiple locations has become easier. Big Data analytic frameworks enabled by IoT and cloud computing methods present new opportunities to extract new knowledge and create novel applications in health care domain. This paper shows one of the novel methods to improve the quality of health care data processing inside the cloud. 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, 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). To the best of our knowledge this is the first scheme offered to replace the manual process of monitoring CBF using biomedical electronic devices.

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