A Kernel Partial Least Square Based Feature Selection Method

Maximum relevance and minimum redundancy (mRMR) has been well recognised as one of the best feature selection methods. This paper proposes a Kernel Partial Least Square (KPLS) based mRMR method, aiming for easy computation and improving classification accuracy for high-dimensional data. Experiments with this approach have been conducted on seven real-life datasets of varied dimensionality and number of instances, with performance measured on four different classifiers: Naive Bayes, Linear Discriminant Analysis, Random Forest and Support Vector Machine. Experimental results have exhibited the advantage of the proposed method over several competing feature selection techniques

Adaptive feature extraction in EEG-based motor imagery BCI: tracking mental fatigue

Objective: Electroencephelogram (EEG) signals are non-stationary. This could be due to the internal fluctuation of brain states such as fatigue, frustration, etc. This necessitates the development of adaptive Brain-Computer Interfaces (BCI) whose performance does not deteriorate significantly with the adversary change in the cognitive state. In this paper, we put forward an unsupervised adaptive scheme to adapt the feature extractor of motor imagery (MI) BCIs by tracking the fatigue level of the user. Approach: Eleven subjects participated in the study during which they accomplished MI tasks while self-reporting their perceived levels of mental fatigue. Out of the 11 subjects, only 6 completed the whole experiment, while the others quit in the middle because of experiencing high fatigue. The adaptive feature extractor is attained through the adaptation of the common spatial patterns (CSP), one of the most popular feature extraction algorithms in EEG-based BCIs. The proposed method was analyzed in two ways: oine and in near real-time. The separability of the MI EEG features extracted by the proposed adaptive CSP (ADCSP) has been compared with that by the conventional CSP (C-CSP) and another CSP based adaptive method (ACSP) in terms of: Davies Bouldin Index (DBI), Fisher Score (FS) and Dunn's Index (DI). Results: Experimental results show significant improvement in the separability of MI EEG features extracted by ADCSP as compared to that by C-CSP and ACSP. Signficance: Collectively, the results of the experiments in this study suggest that adapting CSP based on mental fatigue can improve the class separability of MI EEG features

cBDI-based Collaborative Control for a Robotic Wheelchair

In this paper we present a collaborative control architecture for a robotic wheelchair with the aim of providing "assistance as required". The architecture is based on cBDI - an extension to the Belief-Desire-Intention model to support human-machine collaboration. We present results of an evaluation of the architecture in a simulated environment and conclude that collaborative control could ensure "feeling in control" even under assistance

Continuous Transitions in Mereotopology

Continuity from a qualitative perspective is different from both the philosophical and mathematical view of continuity. We explore different intuitive notions of spatio-temporal continuity. We present a general formal framework for continuity and continuous transitions in mereotopology for spatio-temporal histories and thus sketch the correctness of the conceptual neighbourhood for the qualitative spatial representation language RCC-8

Spatio-Temporal Continuity in Geographic Space

The paper is an investigation into different notions of spatial, temporal, and spatio-temporal continuity. A formal framework is proposed in which a number of different notions of continuity is situated

Abducing Qualitative Spatio-Temporal Histories from Partial Observations

We present a logic-based framework in which a qualitative spatio-temporal world model is constructed from local surveys i.e. partial spatio-temporal knowledge. Complete space-time histories are obtained through an abductive process driven by continuity constraints and a library of possibly domain specific behaviour patterns. The abduction technique is circumscription, which implements the heuristic that changes should only occur when forced to. We then discuss various additional heuristics to drive the selection of preferred explanations