Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology

Abstract

EEG-based Brain-computer interfaces (BCI) are facing basic challenges in real-world applications. The technical difficulties in developing truly wearable BCI systems that are capable of making reliable real-time prediction of users' cognitive states in dynamic real-life situations may seem almost insurmountable at times. Fortunately, recent advances in miniature sensors, wireless communication and distributed computing technologies offered promising ways to bridge these chasms. In this paper, we report an attempt to develop a pervasive on-line EEG-BCI system using state-of-art technologies including multi-tier Fog and Cloud Computing, semantic Linked Data search, and adaptive prediction/classification models. To verify our approach, we implement a pilot system by employing wireless dry-electrode EEG headsets and MEMS motion sensors as the front-end devices, Android mobile phones as the personal user interfaces, compact personal computers as the near-end Fog Servers and the computer clusters hosted by the Taiwan National Center for High-performance Computing (NCHC) as the far-end Cloud Servers. We succeeded in conducting synchronous multi-modal global data streaming in March and then running a multi-player on-line EEG-BCI game in September, 2013. We are currently working with the ARL Translational Neuroscience Branch to use our system in real-life personal stress monitoring and the UCSD Movement Disorder Center to conduct in-home Parkinson's disease patient monitoring experiments. We shall proceed to develop the necessary BCI ontology and introduce automatic semantic annotation and progressive model refinement capability to our system.

Fog computing security: a review of current applications and security solutions

“…The benefits of the proposed system are demonstrated through playing a multi-player online game called EEG Tractor Beam. Another similar system is developed in [80], where a multi-tiered Fog and Cloud system, linked data, and classification models have been used for EEG-based Brain-computer interfaces (BCI). The Fog servers are used for real-time data processing, caching, computation off-loading, managing heterogeneity and forwarding data from mobile devices and sensors to the Cloud system.…”

A Novel Approach for Accessing Semantic Data by Translating RESTful/JSON Commands into SPARQL Messages

“…There have been studies about Linked Data, such as database applications for interacting with and sharing multiple layers of distributed systems that are used to track human brain waves [5]. This research achieved a significant accomplishment in real-time forecasting of human awareness states in real life situations by combining intelligent sensors.…”

Energy efficient and latency aware TDM-PON for local customer internetworking

“…To ensure safe road traffic control system, local control loop subsystem should make decision and execute different operations within a few milliseconds [1]. In [13], authors came up with wearable brain-computer interface (BCI) system which is developed to make realtime prediction of human cognitive state. In their BCI system, latency is one of the key factors.…”