Wednesday, 19 December 2012
Our paper entitled "Towards Cooperative Brain-Computer Interfaces for Space Navigation," has been
accepted for presentation at ACM's Intelligent User Interfaces (IUI) 2013 conference. The review process was extremely selective with only about 20% of submissions being accepted for presentation. The paper is co-authored by Riccardo Poli Caterina Cinel Ana Matran-Fernandez, Francisco Sepulveda and Adrian Stoica.
Here is the abstract of the paper:
We explored the possibility of controlling a spacecraft simulator using an analogue Brain-Computer Interface (BCI) for 2-D pointer control. This is a difficult task, for which no previous attempt has been reported in the literature. Our system relies on an active display which produces event-related potentials (ERPs) in the user’s brain. These are analysed in real-time to produce control vectors for the user interface. In tests, users of the simulator were told to pass as close as possible to the Sun. Performance was very promising, on average users managing to satisfy the simulation success criterion in 67.5% of the runs. Furthermore, to study the potential of a collaborative approach to spacecraft navigation, we developed BCIs where the system is controlled via the integration of the ERPs of two users. Performance analysis indicates that collaborative BCIs produce trajectories that are statistically significantly superior to those obtained by single users.
Monday, 17 December 2012
Our paper entitled "Improving Decision-making based on Visual Perception via a Collaborative Brain-Computer Interface" has been accepted for oral presentation at the 2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA). The paper is co-authored by Riccardo Poli , Caterina Cinel , Francisco Sepulveda and Adrian Stoica.
Here is the abstract of the paper:
In the presence of complex stimuli, in the absence of sufficient time to complete the visual parsing of a scene, or when attention is divided, an observer can only take in a subset of the features of a scene, potentially leading to poor decisions. In this paper we look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better decision making. Our approach involves the combination of brain-computer interface (BCI)
technology with human behavioural responses. To test our ideas in controlled conditions, we asked observers to perform a simple visual matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same
or different. Visual stimuli were presented for insufficient time for the observers to be certain of the decision. The degree of difficulty of the task also depended on the number of matching features between the two patterns. The higher the number, the more difficult the task. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines these behavioural and neural measures. For group decisions, we tested the use of a majority rule and three further decision rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with individual performance. Also, within groups of each size, decision rules based on such features outperform the majority rule.
Friday, 14 December 2012
We have published a number of papers under the support from this grant in the last few months. Here is a list:
. J Cannan and H. Hu, A Multi-Sensor Armband based on Muscle and Motion Measurements, Proc. of IEEE Int. Conf. on Robotics and Biomimetics, Guangzhou, China, 11-14 December 2012, pages 1098-1103.
. S. Wang, L. Chen, H. Hu and and K. McDonald-Maier, Doorway Passing of an Intelligent Wheelchair by Dynamically Generating B´ezier Curve Trajectory, Proc. of IEEE Int. Conf. on Robotics and Biomimetics, Guangzhou, China, 11-14 December 2012, pages 1206-1211.
. E.J. Rechy-Ramirez, H. Hu and K. McDonald-Maier, Head movements based control of an intelligent wheelchair in an indoor environment, Proc. of IEEE Int. Conf. on Robotics and Biomimetics, Guangzhou, China, 11-14 December 2012, pages 1464-1469.
. L. Chen, H. Hu and K. McDonald-Maier, EKF based Mobile Robot Localisation, Proc. of the 3rd International Conf. on Emerging Security Technologies (EST-2012), Lisbon, Portugal, 5-7 Sept. 2012, pages 149-154.
. S. Wang, H. Hu and Klaus McDonald-Marie, Optimization and Sequence Search based Localization in Wireless Sensor Networks, Proc. of the 3rd International Conf. on Emerging Security Technologies (EST-2012), Lisbon, Portugal, 5-7 September 2012, pages 155-160.
. Y. Kovalchuk, H. Hu, D. Gu, K. McDonald-Maier, D. Newman, S. Kelly, G. Howells, Investigation of Properties of ICmetrics Features, Proc. of the 3rd International Conf. on Emerging Security Technologies (EST-2012), Lisbon, Portugal, 5-7 September 2012, pages 115-120.
. Y. Kovalchuk, H. Hu, D. Gu, K. McDonald-Maier, G. Howells, ICmetrics for Low Resource Embedded Systems, Proc. of the 3rd International Conf. on Emerging Security Technologies (EST-2012), Lisbon, Portugal, 5-7 September 2012, pages 121-126.
. B. Lu, D. Gu, H. Hu and K. McDonald-Marier, Sparse Gaussian Process for Spatial Function Estimation with Mobile Sensor Networks, Proc. of the 3rd International Conf. on Emerging Security Technologies (EST-2012), Lisbon, Portugal, 5-7 September 2012, pages 145-150.
. L. Chen, S. Wang and H. Hu, B´ezier Curve based Path Planning for an Intelligent Wheelchair to pass a Doorway, Proceedings of the UKACC Int. Conference on Control, Cardiff, 3-5 September 2012.