Abstract-In this paper we present a system that uses the human ability to control a video game on a mobile device using electroencephalographic (EEG) Mu rhythms. The signals were obtained using a specially designed electrode cap and equipment, and sent through a Bluetooth connection to a PC that processes it in real time. The signal was then mapped onto two control signals and sent through wireless connection to a mobile gaming device BreakOut − . We have also investigated the human's ability to play the video game by manipulating neuronal motor cortex activity in the presence of a visual feedback environment. The participants played the video game by using their thoughts only with up to 80% accuracy over controlling the target.

Traditionally, Information Fusion systems assume that the information is gathered from known sensors over proprietary communication networks and fuse using fixed rules of information fusion and designated computing and communication resources. Emerging technologies like wireless sensor networks, TEDS enabled legacy sensors, ubiquitous computing devices and all IP next generation networks are challenging the rationale of conventional information fusion systems. The technology has matured to a point where it is reasonable to discover sensors based on the context, establish relevance, query for appropriate data, and fuse it using the most appropriate fusion rule, using ubiquitous computing and communication environment in an opportunistic manner. We define such fusion systems as opportunistic information fusion systems. In this paper we introduce this new paradigm for information fusion and identify plausible approaches and challenges to design, develop and deploy the proposed next generation opportunistic information fusion systems.

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This paper presents the design and performance of a body-machine-interface (BoMI) system, where a user controls a robotic 3D virtual wheelchair with the signals derived from his/her shoulder and elbow movements. BoMI promotes the perspective that system users should no longer be operators of the engineering design but should be an embedded part of the functional design. This BoMI system has real-time controllability of robotic devices based on user-specific dynamic body response signatures in high-density 52-channel sensor shirt. The BoMI system not only gives access to the user’s body signals, but also translates these signals from user’s body to the virtual reality device-control space. We have explored the efficiency of this BoMI system in a semi-cylinderic 3D virtual reality system. Experimental studies are conducted to demonstrate, how this transformation of human body signals of multiple degrees of freedom, controls a robotic wheelchair navigation task in a 3D virtual reality environment. We have also presented how ma- chine learning can enhance the interface to adapt towards the degree of freedoms of human body by correcting the errors performed by the user

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