Inter-hemispheric electroencephalography coherence analysis: Assessing brain activity during monotonous driving

The current study investigated the effect of monotonous driving on inter-hemispheric electroencephalography (EEG) coherence. Twenty-four non-professional drivers were recruited to perform a fatigue instigating monotonous driving task while 30 channels of EEG were simultaneously recorded. The EEG recordings were then divided into 5 equal sections over the entire driving period for analysis. Inter-hemispheric coherence was computed from 5 homologous EEG electrode pairs (FP1-FP2, C3-C4, T7-T8, P7-P8, and O1-O2) for delta, theta, alpha and beta frequency bands. Results showed that frontal and occipital inter-hemispheric coherence values were significantly higher than central, parietal, and temporal sites for all four frequency bands (p< 0.0001). In the alpha frequency band, significant difference was found between earlier and later driving sections (p= 0.02). The coherence values in all EEG frequency bands were slightly increased at the end of the driving session, except for FP1-FP2 electrode pair, which showed no significant change in coherence in the beta frequency band at the end of the driving session. © 2010 Elsevier B.V

Transmission Heterogeneity and Control Strategies for Infectious Disease Emergence

The control of emergence and spread of infectious diseases depends critically on the details of the genetic makeup of pathogens and hosts, their immunological, behavioral and ecological traits, and the pattern of temporal and spatial contacts among the age/stage-classes of susceptible and infectious host individuals.We show that failing to acknowledge the existence of heterogeneities in the transmission rate among age/stage-classes can make traditional eradication and control strategies ineffective, and in some cases, policies aimed at controlling pathogen emergence can even increase disease incidence in the host. When control strategies target for reduction in numbers those subsets of the population that effectively limit the production of new susceptible individuals, then control can produce a flush of new susceptibles entering the population. The availability of a new cohort of susceptibles may actually increase disease incidence. We illustrate these general points using Classical Swine Fever as a reference disease.Negative effects of culling are robust to alternative formulations of epidemiological processes and underline the importance of better assessing transmission structure in the design of wildlife disease control strategies

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

Evaluating human factors associated with driver fatigue : implications for development of train driver vigilance system

University of Technology, Sydney. Faculty of Science.NO FULL TEXT AVAILABLE. Access is restricted indefinitely.NO FULL TEXT AVAILABLE. Access is restricted indefinitely. ----- Fatigue has been recognised as a significant factor in industrial accidents, such as transportation industries. Electroencephalography (EEG) has been found to be one of the most reliable indicators of fatigue (Artaud et al., 1994). Several indicators of fatigue can be observed from the increase in alpha and theta activities which are accompanied by a decrease of beta activities in EEG signals (Santamaria & Chiappa, 1987b; Lal & Craig, 2001). This study attempted to identify possible algorithms derived from the changes in the brain activity that could be utilised as a means to detect fatigue in train drivers. This thesis has investigated changes in the brain activity (delta (δ), theta (θ), alpha (α), and beta (β)), and the equation (θ+α)/β activity. Participants from both train driver cohort, as well as non-professional driver cohort, were included in the study, in order to assess the changes in brain activity during a fatigue instigating monotonous driving session. This study has also explored the correlations between brain activity changes and the lifestyle and behavioural factors. Lastly, a case study of ten train drivers was presented with a possible technique proposed for fatigue detection technology. A total of 50 male train drivers (aged 44±9.4 years) were recruited to participate in the 30-minute monotonous train driving experiment. All participants held current Rail Safety Worker Certificate (Driver) from the Department of Transport, Australia. In addition, a total of 52 non-professional drivers (36 males and 16 females, aged 27±9.4 years) were also recruited to participate in a monotonous driving session. All participants held a current driver’s license. Simultaneous physiological recordings were obtained during the monotonous driving sessions. Two channels of EEG (frontal and temporal sites) and one channel of electrooculogram were acquired. The EEG data from the two channels were then subjected to Fast Fourier Transform (FFT) to derive the four EEG frequency components, which were delta (0–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–35 Hz) (Rowan & Tolunsky, 2003). The EEG spectra were then sectioned into 10 equal sections in order to identify the changes in EEG activities over the period of the monotonous driving task. Lifestyle Appraisal Questionnaire (Craig, Hancock, & Craig, 1996), Profile of Mood State (McNair, Lorr, & Doppleman, 1971), and Locus of Control of Behaviour (Craig, Franklin, & Andrews, 1984) questionnaires were administered prior to the study. Fatigue Likert scale, Fatigue questionnaire (Wessely & Powell, 1989), and State and Trait Anxiety Inventory (Spielberger, Gorsuch, Luschene, Vagg, & Jacobs, 1983) questionnaires were administered prior to and after the monotonous driving session. The results showed that at the end of the driving session, the heart rate decreased significantly (p<0.0001), which indicated that the participants were considerably fatigued after the driving task (Malik et al., 1996). At the end of the monotonous driving session, the delta activity showed a significant increase (p=0.04). There was a significant increase of theta activity during the driving session (p=0.002). Alpha activity also decreased significantly at the end of the monotonous driving session (p=0.00003), and a significant decrease in beta activity was also detected (p=0.003). A significant increase of activity computed using equation (θ+α)/β (p=0.01) was also found at the end of the monotonous driving session. The results also showed that higher heart rate was positively associated with an increase in beta activity (r=0.87, p=0.01). A lower self-reported fatigue level was linked with higher beta (r=-0.78, p=0.04) and theta (r=-0.58, p=0.046) activities. The results of the case study indicated that 40%-50% decrease in beta activity was recorded when participants were alert before the monotonous driving session and moderately fatigued at the end of the session. A 60%-70% decrease in beta activity was recorded when participants were extremely fatigued at the end of the driving session. Future research needs to assess the reproducibility of the EEG of fatigue in train drivers and consider the development of robust fatigue countermeasure devices by combining the findings of this research with other technologies to increase the reliability or such systems

Assessing a potential electroencephalography based algorithm during a monotonous train driving task in train drivers

Electroencephalography can be utilized to detect driver fatigue. One algorithm that shows promising results in detecting fatigue is the equation ((θ+α)/β). The current study observes the result of equation (θ+α)/β) on 10 train drivers who were completing a 30-minute monotonous train driving experiment. © 2011 IEEE

Comparing combinations of EEG activity in train drivers during monotonous driving

This study investigated the changes in electroencephalography (EEG) activity in train drivers during a monotonous train-driving session. Four combinations of EEG activities were also compared to investigate the difference in performance of these equations. The four equations tested were equation 1 (θ/β), equation 2 (θ/(α + β)), equation 3 ((θ + α)/β), and equation 4 ((θ + α)/(α + β)). A total of fifty male train drivers were recruited to perform a 30-min monotonous train-driving task while 2-channels of EEG (frontal and temporal) were recorded. At the frontal site, significant differences were found for theta (p = 0.045) and alpha (0.0001) activities, and at the temporal site, significant differences were found for delta (p = 0.007) and theta (0.01) activities. For the average of frontal and temporal site activities, significant differences were found for delta (p = 0.004), theta (p = 0.001), and beta (p = 0.048). Significant difference were found for temporal site for equation 1 (θ/β) (p = 0.04), and equation 4 ((θ + α)/(α + β)) (p = 0.02), and for the average of frontal and temporal site activities, significant differences were found for all four equations (equation 1 (p = 0.001), equation 2 (p = 0.006), equation 3 (p = 0.04), and equation 4 (p = 0.002)). These findings can be utilised as a potential fatigue indicator. © 2010 Elsevier Ltd. All rights reserved

Using EEG spectral components to assess algorithms for detecting fatigue

Fatigue is a constant occupational hazard for drivers and it greatly reduces efficiency and performance when one persists in continuing the current activity. Studies have investigated various physiological associations with fatigue to try to identify fatigue indicators. The current study assessed the four electroencephalography (EEG) activities, delta (δ), theta (θ), alpha (α) and beta (β), during a monotonous driving session in 52 subjects (36 males and 16 females). Performance of four algorithms, which were: algorithm (i) (θ + α)/β, algorithm (ii) α/β, algorithm (iii) (θ + α)/(α + β), and algorithm (iv) θ/β, were also assessed as possible indicators for fatigue detection. Results showed stable delta and theta activities over time, a slight decrease of alpha activity, and a significant decrease of beta activity (p < 0.05). All four algorithms showed an increase in the ratio of slow wave to fast wave EEG activities over time. Algorithm (i) (θ + α)/β showed a larger increase. The results have implications for detecting fatigue. Impact on industry: The results of this research have the implication for detecting fatigue and can be used for future development of fatigue countermeasure devices. © 2008 Elsevier Ltd. All rights reserved

Using spectral analysis to extract frequency components from electroencephalography: Application for fatigue countermeasure in train drivers

Train accidents can have a massive impact towards the surrounding area as well as the general community. Most train accidents can be attributed to fatigue, and hence, development of fatigue countermeasure devices that can warn drivers of fatigue status and prevent accidents can greatly benefit train drivers, passengers, society and general community. Electroencephalography (EEG) has been proven to be one of the most reliable indicators of fatigue. This study investigated the change of brain activity during fatigue-instigating monotonous driving session, by extracting the four frequency components (delta, theta, alpha, and beta) using FFT spectral analysis at different brain sites (frontal, central, temporal, parietal, and occipital). Results identified some statistically significant differences between early and later stages of driving in delta, theta and beta activities at different brain sites. The results of the current study may be used for future development of fatigue countermeasure by targeting specific frequency component and brain sites. © 2007 IEEE

Single channel wireless EEG: Proposed application in train drivers

Electroencephalography (EEG) can be used as an indicator of fatigue. Several studies have shown that slow wave brain activities, delta (0-4 Hz) and theta (4- 8 Hz), increase as an individual becomes fatigued, while the fast brain activities, alpha (8-13 Hz) and beta (13-35 Hz), decrease. However, an EEG is a complex piece of equipment that is generally used in laboratory based studies. In order to develop a fatigue countermeasure device for train drivers using EEG, there is a need for a simple and wireless EEG monitor. This paper explains the development of a single channel wireless EEG device. © 2008 IEEE

Optical flow image analysis of facial expressions of human emotion - Forensic applications

© 2008 ICST. The objective of this study was to induce emotions in individuals to determine if specific facial movements could be detected and analysed by the optical flow technique. This analysis is in the form of motion vector plots. The procedure ascertains if specific emotions can be defined as a set of facial movements which are common to most people when they experience a particular emotion. 'Emotion vector maps' would then be established for specific emotions. These vector sets could then be applied to automated facial image analysis for security/forensic purposes. Individuals were videotaped while watching emotion-inducing short films. After the viewing of each short film, volunteers completed a brief self-reporting questionnaire to establish the emotions they experienced. The image sequences were then analysed according to emotion, by using optical flow analysis. Results were statistically analysed. Trends and analyses are presented in relation to security and video surveillance. Issues and the development of pattern recognition systems applied to human facial images for security purposes are briefly discussed