Smart end-to-end infrastructural solution for monitoring patients with neurological disorders

Monitoring neurological disorders involve management of intensive, continuous, and heterogeneous brain signals. Monitoring EEG has been recognized to be an efficient way to detect abnormalities in neural processes. Traditional techniques for data management are not appropriate for continuous monitoring, any more. A Smart monitoring architecture is required to inherently integrate different technologies, allow seamless integration of different processes including: data gathering, processing, analytics, and visualization. In this paper, we propose an end-to-end architecture based on SOA and other emerging technologies to support continuous monitoring of patients with neurological disorders such as Parkinson's disease. The silent feature of the proposed solution is to incorporate smartness at all levels of monitoring activities from sensing to data storage, processing, and visualization. We evaluated the proposed architecture using an illustrative scenario of monitoring of patients with Parkinson's disease. We described the current implementation efforts and we highlighted how the proposed monitoring solution implemented smartness at a various monitoring processes.