Distributed Multimodal Brain Monitoring Using Body-Area Sensor Arrays

Abstract

The wearable sensing technologies of continuous brain monitoring have become a central facilitator of healthcare, assistive systems, and humancomputer interaction. But the majority of solutions available to date use centralised data acquisition and processing designs, which have been plagued by scalability, cost issues, go directly through the communication line and cannot be trusted in long-term deployments. It is necessary to overcome these shortcomings; to this end, the present paper introduces a distributed Internet of Things (IoT)-based body area sensor network (BASN) architecture in multimodal brain monitoring. The presented system incorporates the electroencephalography (EEG), inertial, and auxiliary physiological sensors in a wireless body-area network to supply it with the possibility of real-time operation, energy efficiency, and scalability. Its architecture takes the form of hierarchical and distributed architecture that includes the low powered body worn sensor nodes, edge-enabled body coordinator, and cloud / fog based services. Preprocessing and feature extraction are done locally at sensor and coordinator levels to minimise communication overhead as well as enhance responsiveness. The energy-conscious communication plan is used to optimise the data transfer in order to ensure the consistent synchronisation of multiple sensor streams of various modalities. The system is tested by way of simulation in different networking conditions and sensor densities. Performance data prove that the distributed architecture proposed allows to reduce end-to-end latency by a factor, end node energy used by a factor, and the percentage of packet delivery by a factor than the same architecture would provide in a traditional centralised scheme based on monitoring. These results prove the usefulness of distributed sensing and edge-assistance data management in body area networks. The suggested framework offers a scalable and implementable platform of next-generation IoT-bases brain monitoring systems and other wearable cyber-physical health solutions.