Energy Conservation Using an Optimized Topology With Distributed Processing of EEG Signals

Investigations in the field of wireless body area network reveals that Electroencephalogram (EEG) is the more concentrated area of research currently. In this regard, this paper works on reducing the power consumed by the electrodes in wireless EEG sensor network. Various existing topological structures such as tree topology, fully connected topology, near end and far end topology are used for electrode arrangements during signal acquisition. But the proposed hexagonally clustered topological structure is found to outperform compared to the other structures for node localization. Also, a comparison is made between the centralized and distributed method of processing on the acquired EEG signals. The proposed work follows distributed processing on the EEG datas where its combination with hexagonal clustering structure for node positioning reports better level of energy conservation compared to other methods as proven in the experimentation.