Harnessing Big Data for Wireless Body Area Network Applications

Abstract

Precision medicine initiative recently launched by the Government, focuses on prescribing right drug for right patient at a right dosage. Information of genome variation and lifestyle monitoring of a patient using wireless sensor devices is leveraged for this initiative. Wireless Body Area Network (WBAN) applications used for monitoring pervasive health care generates a very high volume of heterogeneous unstructured data (text, video, and images). We propose cloud based WBAN architecture for efficient processing, storage, indexing and archiving of the highly dense clinical data. We use components from Apache Hadoop's ecosystem for parallel and distributed computing. Our evaluation of system uses two public datasets: physical activity monitoring dataset and genome dataset: for examining the prognostic effect of the immune system on breast cancer in lymph node-negative breast cancer patients. Results obtained are very encouraging and indicate that harnessing big data is a vital step for efficiently processing and analyzing clinical data, which can be adopted in precision medicine initiative.