General

The reliability of sensing fatigue from neurophysiology

2011-05-13T01:40:13Z

The reliability of sensing fatigue from neurophysiology Lal Saroj; Bekiaris Evangelos UTS To date no-study has tested the reproducibility of electroencephalography (EEG) changes that occur during driver fatigue. For the EEG changes to be useful in the development of a fatigue sensing and countermeasure device the EEG response during each onset period of fatigue in individuals needs to be reproducible. The aim of the present study was to investigate the reproducibility of the EEG changes during fatigue in professional drivers in order to identify the feasibility of the EEG measure for a fatigue sensor. Twenty professional drivers were assessed during two separate sessions of a driver simulator task.

Mutual Information Based Data Association

2012-05-08T04:58:56Z

Mutual Information Based Data Association Alempijevic Alen; Kodagoda Sarath; Dissanayake Gamini Marusic, S;Palaniswami,J;Law, Y.W Relating information originating from disparate sensors without any attempt to model the environment or the behaviour of any particular object within it is a challenging task. Inspired by human perception, the focus of this paper will be on observing objects moving in space using sensors that operate based on different physical principles and the fact that motion has in principle, greater power to specify properties of an object than purely spatial information captured as a single observation in time. The contribution of this paper include the development of a novel strategy for detecting a set of signals that are statistically dependent and correspond to each other related by a common cause. Mutual Information is proposed as a measure of statistical dependence. The algorithm is evaluated through simulations and three application domains, which includes, (1.) Grouping problem in images, (2.) Data association problem in moving observers with dynamic targets, and (3.) Multi-modal sensor fusion.

Towards a countermeasure device to detect fatigue in drivers

2013-01-18T04:40:20Z

Towards a countermeasure device to detect fatigue in drivers Lal Saroj; Craig Ashley n/a Fatigue affects the drivers' ability to continue driving safely. Therefore, on-line monitoring of physiological signals while driving provides the possibility of detecting fatigue in real time. The EEG signal has been found to be the most predictive and reliable indicator. However, little evidence exists on implementing EEG into a fatigue countermeasure device. The aims were to utilise EEG changes during fatigue for development of fatigue countermeasure software and to test the ability of such software in detecting fatigue. EEG was obtained in twenty truck drivers during a driver simulator task till subjects fatigued. Changes found in delta, theta, alpha and beta activity were used to develop algorithms for the software. The software was designed to detect an alert state and early, medium and extreme levels of fatigue. The software was tested in off-line mode in a group often truck drivers. The software was capable of detecting fatigue accurately in all ten subjects. The percentage of time the subjects were detected to be in a fatigue state was significantly different to the alert phase (p

A Course Recommender System Using Multiple Criteria Decision Making Method

2012-05-29T05:14:14Z

A Course Recommender System Using Multiple Criteria Decision Making Method Le Roux Francois; Ranjeet Elkunchwar; Ghai Vinit; Gao Ya; Lu Jie Tianrui Li, Yang Xu, Da Ruan