Roderick Murray-Smith

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In recent years, new research has brought the field of electroencephalogram (EEG)-based brain-computer interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus(More)
The area of multimodal interaction has expanded rapidly. However, the implementation of multimodal systems still remains a difficult task. Addressing this problem, we describe the OpenInterface (OI) framework, a component-based tool for rapidly developing multimodal input interfaces. The OI underlying conceptual component model includes both generic and(More)
We consider the problem of multi-step ahead prediction in time series analysis using the non-parametric Gaussian process model. -step ahead forecasting of a discrete-time non-linear dynamic system can be performed by doing repeated one-step ahead predictions. For a state-space model of the form , the prediction of at time is based on the point estimates of(More)
We present a novel typewriter application ‘Hex-o-Spell’ that is specifically tailored to the characteristics of direct brain-to-computer interaction. The high bandwidth at which a user may perceive information from the display is used in an appealing visualization based on hexagons. On the other hand the control of the application is possible at low(More)
Gaussian processes provide an approach to nonparametric modelling which allows a straightforward combination of function and derivative observations in an empirical model. This is of particular importance in identification of nonlinear dynamic systems from experimental data. 1) It allows us to combine derivative information, and associated uncertainty with(More)
In this article we describe a novel approach to pedestrian navigation using bearing-based haptic feedback. People are guided in the general direction of their destination via vibration, but additional exploratory navigation is stimulated by varying feedback based on the potential for taking alternative routes. We describe two mobile prototypes that were(More)
Shoogle is a novel, intuitive interface for sensing data withina mobile device, such as presence and properties of textmessages or remaining resources. It is based around activeexploration: devices are shaken, revealing the contents rattlingaround "inside". Vibrotactile display and realistic impactsonification create a compelling system. Inertial sensingis(More)
We present a flexible Machine Learning approach for learning user-specific touch input models to increase touch accuracy on mobile devices. The model is based on flexible, non-parametric Gaussian Process regression and is learned using recorded touch inputs. We demonstrate that significant touch accuracy improvements can be obtained when either raw sensor(More)
We combine the functionality of a mobile Global Positioning System (GPS) with that of an MP3 player, implemented on a PocketPC, to produce a handheld system capable of guiding a user to their desired target location via continuously adapted music feedback. We illustrate how the approach to presentation of the audio display can benefit from insights from(More)