Big data and WBAN: prediction and analysis of the patient health condition in a remote area
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Abstract
The present research aims at the development of a disease prediction system using a Wireless Body Area Network (WBAN) and big data. WBAN is referred as a dynamic sensor network that is based on the deployment of sensor nodes (SNs) in or around the human body. This makes it feasible to make biotic measurements such as an electroencephalogram (EEG), electrocardiogram (ECG) and electromyography (EMG) among others on human subjects. Big data is based on cloud computing and the concept refers to wide scale distributed data processing applications that generally operate with a huge amount of data. The developed prediction model works in two phases. First, biotic measurements were made on human subjects through the use of body sensors. Second, the obtained data from human subjects was compared with big data to make disease predictions.
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