Early congenital heart defect diagnosis in neonates using novel WBAN based three-tier network architecture

Abstract

Medical diagnosis is an emerging area in Wireless Body Area Networks (WBAN). Many research works have been held on WBAN in the perspective of energy efficiency, security, and routing etc. But none of this work conducts medical diagnosis using WBAN. To do this, we proposed a novel WBAN based Three-Ttier architecture for early detection of Congenital Heart Diseases (CHD) in neonates. We adapt IEEE 802.15.6 Media Access Control Address (MAC) to identify the priority level of data. Based on priority level, data is scheduled in time division multiple access (TDMA) manner. Data transmission is secured by using advanced encryption standard (AES) in first tier. Optimal channel selection process is performed using bird swarm optimization (BSO) algorithm in second tier. Here fitness evaluation considers reference signal received quality (RSRQ), signal to noise ratio (SNR), and channel capacity. In third tier, sensed data is classified at diagnosis server to detect CHD in neonates. Neuro-fuzzy algorithm is incorporated in diagnosis server for classification. In diagnosis server, CHD is diagnosed by screening pulse oximetry along with heart beat rate and respiratory rate. Extensive simulation in OMNeT++ shows promising results in delay, average delay, power consumption, and probability of available channels.