A model to predict hypovigilance during a monotonous task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create drowsiness or hypovigilance and impair the ability to react to critical events. Identifying vigilance decrement in monotonous conditions has been a major subject of research, but no research to date has attempted to predict this vigilance decrement. This pilot study aims to show that vigilance decrements due to monotonous tasks can be predicted through mathematical modelling. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants’ performance. This task models the driver’s ability to cope with unpredicted events by performing the expected action. A Hidden Markov Model (HMM) is proposed to predict participants’ hypovigilance. Driver’s vigilance evolution is modelled as a hidden state and is correlated to an observable variable: the participant’s reactions time. This experiment shows that the monotony of the task can lead to an important vigilance decline in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

Further evidence for a deficit in switching attention in schizophrenia

In this study, sustained, selective, divided, and switching attention, and reloading of working memory were investigated in schizophrenia by using a newly developed Visual Attention Battery (VAB). Twenty-four outpatients with schizophrenia and 24 control participants were studied using the VAB. Performance on VAB components was correlated with performance of standard tests. Patients with schizophrenia were significantly impaired on VAB tasks that required switching of attention and reloading of working memory but had normal performance on tasks involving sustained attention or attention to multiple stimulus features. Switching attention and reloading of working memory were highly correlated with Trails (B - A) score for patients. The decline in performance on the switching-attention task in patients with schizophrenia met criteria for a differential deficit in switching attention. Future research should examine the neurophysiological basis of the switching deficit and its sensitivity and specificity to schizophrenia.

Introduction of a short writing task to measure and develop academic literacy in first year health undergraduates

This paper describes an initiative in the Faculty of Health at the Queensland University of Technology, Australia, where a short writing task was introduced to first year undergraduates in four courses including Public Health, Nursing, Social Work and Human Services, and Human Movement Studies. Over 1,000 students were involved in the trial. The task was assessed using an adaptation of the MASUS Procedure (Measuring the Academic Skills of University Students) (Webb & Bonanno, 1994). Feedback to the students including MASUS scores then enabled students to be directed to developmental workshops targeting their academic literacy needs. Students who achieved below the benchmark score were required to attend academic writing workshops in order to obtain the same summative 10% that was obtained by those who had achieved above the benchmark score. The trial was very informative, in terms of determining task appropriateness and timing, student feedback, student use of support, and student perceptions of the task and follow-up workshops. What we learned from the trial will be presented with a view to further refinement of this initiative.

Using samples to estimate the sensitivity and specificity of a surveillance process

Determining sensitivity and specificity of a postoperative infection surveillance process is a difficult undertaking. Because postoperative infections are rare, vast numbers of negative results exist, and it is often not reasonable to assess them all. This study gives a methodological framework for estimating sensitivity and specificity by taking only a small sample of the number of patients who test negative and comparing their findings to the reference or “gold standard” rather than comparing the findings of all patients to the gold standard. It provides a formula for deriving confidence intervals for these estimates and a guide to minimum requirements for sampling results.

The performance of a prolonged reading task by students with low vision

Purpose: Students often read for long periods and prolonged reading practice may be important for developing reading skills. For students with low vision, reading at a close working distance imposes high demands on their near visual functions, which might make it difficult to sustain prolonged reading. The aim of this study was to investigate the performance of a prolonged reading task by students with low vision. Method: Forty students with low vision, aged from eight to 20 years and without any intellectual, reading or learning disability, were recruited through the Paediatric Low Vision Clinic, Buranda, Queensland. Following a preliminary vision examination, reading performance measures—critical print size (CPS), maximum oral reading rates (MORR), near text visual acuity— were recorded using the Bailey-Lovie text reading charts before and after a 30-minute prolonged reading task. Results: The mean age of the participants was 13.03 ± 3 years. The distance and near visual acuities ranged between -0.1 to 1.24 logMAR and 0.0 to 1.60 logMAR, respectively. The mean working distance of the participants was 11.2 ± 5.8 cm. Most of the participants (65 per cent) in this study were able to complete the prolonged reading task. Overall, there was no significant change in CPS, MORR and near text visual acuity following the prolonged task (p > 0.05). MORR was significantly correlated to age and near text visual acuity (p < 0.05). Conclusions: In this study, students with low vision were able to maintain their reading performance over a 30-minute prolonged reading task. Overall, there was no significant increase or decrease in reading performance following a prolonged reading task performed at their habitual close working distances but there were wide individual variations within the group.

Parents’ self-efficacy, outcome expectations, and self-reported task performance when managing atopic dermatitis in children: Instrument reliability and validity

BACKGROUND: Support and education for parents faced with managing a child with atopic dermatitis is crucial to the success of current treatments. Interventions aiming to improve parent management of this condition are promising. Unfortunately, evaluation is hampered by lack of precise research tools to measure change. OBJECTIVES: To develop a suite of valid and reliable research instruments to appraise parents' self-efficacy for performing atopic dermatitis management tasks; outcome expectations of performing management tasks; and self-reported task performance in a community sample of parents of children with atopic dermatitis. METHODS: The Parents' Eczema Management Scale (PEMS) and the Parents' Outcome Expectations of Eczema Management Scale (POEEMS) were developed from an existing self-efficacy scale, the Parental Self-Efficacy with Eczema Care Index (PASECI). Each scale was presented in a single self-administered questionnaire, to measure self-efficacy, outcome expectations, and self-reported task performance related to managing child atopic dermatitis. Each was tested with a community sample of parents of children with atopic dermatitis, and psychometric evaluation of the scales' reliability and validity was conducted. SETTING AND PARTICIPANTS: A community-based convenience sample of 120 parents of children with atopic dermatitis completed the self-administered questionnaire. Participants were recruited through schools across Australia. RESULTS: Satisfactory internal consistency and test-retest reliability was demonstrated for all three scales. Construct validity was satisfactory, with positive relationships between self-efficacy for managing atopic dermatitis and general perceived self-efficacy; self-efficacy for managing atopic dermatitis and self-reported task performance; and self-efficacy for managing atopic dermatitis and outcome expectations. Factor analyses revealed two-factor structures for PEMS and PASECI alike, with both scales containing factors related to performing routine management tasks, and managing the child's symptoms and behaviour. Factor analysis was also applied to POEEMS resulting in a three-factor structure. Factors relating to independent management of atopic dermatitis by the parent, involving healthcare professionals in management, and involving the child in the management of atopic dermatitis were found. Parents' self-efficacy and outcome expectations had a significant influence on self-reported task performance. CONCLUSIONS: Findings suggest that PEMS and POEEMS are valid and reliable instruments worthy of further psychometric evaluation. Likewise, validity and reliability of PASECI was confirmed.

Real-time performance modelling of a sustained attention to response task

Vigilance declines when exposed to highly predictable and uneventful tasks. Monotonous tasks provide little cognitive and motor stimulation and contribute to human errors. This paper aims to model and detect vigilance decline in real time through participant’s reaction times during a monotonous task. A lab-based experiment adapting the Sustained Attention to Response Task (SART) is conducted to quantify the effect of monotony on overall performance. Then relevant parameters are used to build a model detecting hypovigilance throughout the experiment. The accuracy of different mathematical models are compared to detect in real-time – minute by minute - the lapses in vigilance during the task. We show that monotonous tasks can lead to an average decline in performance of 45%. Furthermore, vigilance modelling enables to detect vigilance decline through reaction times with an accuracy of 72% and a 29% false alarm rate. Bayesian models are identified as a better model to detect lapses in vigilance as compared to Neural Networks and Generalised Linear Mixed Models. This modelling could be used as a framework to detect vigilance decline of any human performing monotonous tasks.

Predicting effects of monotony on driver’s vigilance

Monotony has been identified as a contributing factor to road crashes. Drivers’ ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks, such as driving on Australian rural roads, many of which are monotonous by nature. Highway design in particular attempts to reduce the driver’s task to a merely lane-keeping one. Such a task provides little stimulation and is monotonous, thus affecting the driver’s attention which is no longer directed towards the road. Inattention contributes to crashes, especially for professional drivers. Monotony has been studied mainly from the endogenous perspective (for instance through sleep deprivation) without taking into account the influence of the task itself (repetitiveness) or the surrounding environment. The aim and novelty of this thesis is to develop a methodology (mathematical framework) able to predict driver lapses of vigilance under monotonous environments in real time, using endogenous and exogenous data collected from the driver, the vehicle and the environment. Existing approaches have tended to neglect the specificity of task monotony, leaving the question of the existence of a “monotonous state” unanswered. Furthermore the issue of detecting vigilance decrement before it occurs (predictions) has not been investigated in the literature, let alone in real time. A multidisciplinary approach is necessary to explain how vigilance evolves in monotonous conditions. Such an approach needs to draw on psychology, physiology, road safety, computer science and mathematics. The systemic approach proposed in this study is unique with its predictive dimension and allows us to define, in real time, the impacts of monotony on the driver’s ability to drive. Such methodology is based on mathematical models integrating data available in vehicles to the vigilance state of the driver during a monotonous driving task in various environments. The model integrates different data measuring driver’s endogenous and exogenous factors (related to the driver, the vehicle and the surrounding environment). Electroencephalography (EEG) is used to measure driver vigilance since it has been shown to be the most reliable and real time methodology to assess vigilance level. There are a variety of mathematical models suitable to provide a framework for predictions however, to find the most accurate model, a collection of mathematical models were trained in this thesis and the most reliable was found. The methodology developed in this research is first applied to a theoretically sound measure of sustained attention called Sustained Attention Response to Task (SART) as adapted by Michael (2010), Michael and Meuter (2006, 2007). This experiment induced impairments due to monotony during a vigilance task. Analyses performed in this thesis confirm and extend findings from Michael (2010) that monotony leads to an important vigilance impairment independent of fatigue. This thesis is also the first to show that monotony changes the dynamics of vigilance evolution and tends to create a “monotonous state” characterised by reduced vigilance. Personality traits such as being a low sensation seeker can mitigate this vigilance decrement. It is also evident that lapses in vigilance can be predicted accurately with Bayesian modelling and Neural Networks. This framework was then applied to the driving task by designing a simulated monotonous driving task. The design of such task requires multidisciplinary knowledge and involved psychologist Rebecca Michael. Monotony was varied through both the road design and the road environment variables. This experiment demonstrated that road monotony can lead to driving impairment. Particularly monotonous road scenery was shown to have the most impact compared to monotonous road design. Next, this study identified a variety of surrogate measures that are correlated with vigilance levels obtained from the EEG. Such vigilance states can be predicted with these surrogate measures. This means that vigilance decrement can be detected in a car without the use of an EEG device. Amongst the different mathematical models tested in this thesis, only Neural Networks predicted the vigilance levels accurately. The results of both these experiments provide valuable information about the methodology to predict vigilance decrement. Such an issue is quite complex and requires modelling that can adapt to highly inter-individual differences. Only Neural Networks proved accurate in both studies, suggesting that these models are the most likely to be accurate when used on real roads or for further research on vigilance modelling. This research provides a better understanding of the driving task under monotonous conditions. Results demonstrate that mathematical modelling can be used to determine the driver’s vigilance state when driving using surrogate measures identified during this study. This research has opened up avenues for future research and could result in the development of an in-vehicle device predicting driver vigilance decrement. Such a device could contribute to a reduction in crashes and therefore improve road safety.

Forecasting negative effects of monotony and sensation seeking on performance during a vigilance task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create hypovigilance and impair performance towards critical events. Identifying such impairment in monotonous conditions has been a major subject of research, but no research to date has attempted to predict it in real-time. This pilot study aims to show that performance decrements due to monotonous tasks can be predicted through mathematical modelling taking into account sensation seeking levels. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants‟ performance. The framework for prediction developed on this task could be extended to a monotonous driving task. A Hidden Markov Model (HMM) is proposed to predict participants‟ lapses in alertness. Driver‟s vigilance evolution is modelled as a hidden state and is correlated to a surrogate measure: the participant‟s reactions time. This experiment shows that the monotony of the task can lead to an important decline in performance in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

Effect of group formation on performance, task management and social loafing

Engineering graduates of today are required to adapt to a rapidly changing work environment. In particular, they are expected to demonstrate enhanced capabilities in both mono-disciplinary and multi-disciplinary teamwork environments. Engineering education needs, as a result, to further focus on developing group work capabilities amongst engineering graduates. Over the last two years, the authors trialed various group work strategies across two engineering disciplines. In particular, the effect of group formation on students' performance, task management, and social loafing was analyzed. A recently developed online teamwork management tool, Teamworker, was used to collect students' experience of the group work. Analysis showed that students who were allowed to freely allocate to any group were less likely to report loafing from other team members, than students who were pre-allocated to a group. It also showed that performance was more affected by the presence or absence of a leader in pre-allocated rather than free-allocated groups.

Predictors of future falls in Parkinson disease

Background: Falls are a major health and injury problem for people with Parkinson disease (PD). Despite the severe consequences of falls, a major unresolved issue is the identification of factors that predict the risk of falls in individual patients with PD. The primary aim of this study was to prospectively determine an optimal combination of functional and disease-specific tests to predict falls in individuals with PD. ----- ----- Methods: A total of 101 people with early-stage PD undertook a battery of neurologic and functional tests in their optimally medicated state. The tests included Tinetti, Berg, Timed Up and Go, Functional Reach, and the Physiological Profile Assessment of Falls Risk; the latter assessment includes physiologic tests of visual function, proprioception, strength, cutaneous sensitivity, reaction time, and postural sway. Falls were recorded prospectively over 6 months. ----- ----- Results: Forty-eight percent of participants reported a fall and 24% more than 1 fall. In the multivariate model, a combination of the Unified Parkinson's Disease Rating Scale (UPDRS) total score, total freezing of gait score, occurrence of symptomatic postural orthostasis, Tinetti total score, and extent of postural sway in the anterior-posterior direction produced the best sensitivity (78%) and specificity (84%) for predicting falls. From the UPDRS items, only the rapid alternating task category was an independent predictor of falls. Reduced peripheral sensation and knee extension strength in fallers contributed to increased postural instability. ----- ----- Conclusions: Falls are a significant problem in optimally medicated early-stage PD. A combination of both disease-specific and balance- and mobility-related measures can accurately predict falls in individuals with PD.

Effects of different practice task constraints on fluctuations of player heart rate in small-sided football games

This paper analyzes effects of different practice task constraints on heart rate (HR) variability during 4v4 smallsided football games. Participants were sixteen football players divided into two age groups (U13, Mean age: 12.4±0.5 yrs; U15: 14.6±0.5). The task consisted of a 4v4 sub-phase without goalkeepers, on a 25x15 m field, of 15 minutes duration with an active recovery period of 6 minutes between each condition. We recorded players’ heart rates using heart rate monitors (Polar Team System, Polar Electro, Kempele, Finland) as scoring mode was manipulated (line goal: scoring by dribbling past an extended line; double goal: scoring in either of two lateral goals; and central goal: scoring only in one goal). Subsequently, %HR reserve was calculated with the Karvonen formula. We performed a time-series analysis of HR for each individual in each condition. Mean data for intra-participant variability showed that autocorrelation function was associated with more short-range dependence processes in the “line goal” condition, compared to other conditions, demonstrating that the “line goal” constraint induced more randomness in HR response. Relative to inter-individual variability, line goal constraints demonstrated lower %CV and %RMSD (U13: 9% and 19%; U15: 10% and 19%) compared with double goal (U13: 12% and 21%; U15: 12% and 21%) and central goal (U13: 14% and 24%; U15: 13% and 24%) task constraints, respectively. Results suggested that line goal constraints imposed more randomness on cardiovascular stimulation of each individual and lower inter-individual variability than double goal and central goal constraints.

Examination of gaze behaviors under in situ and video simulation task constraints reveals differences in information pickup for perception and action

Gaze and movement behaviors of association football goalkeepers were compared under two video simulation conditions (i.e., verbal and joystick movement responses) and three in situ conditions (i.e., verbal, simplified body movement, and interceptive response). The results showed that the goalkeepers spent more time fixating on information from the penalty kick taker’s movements than ball location for all perceptual judgment conditions involving limited movement (i.e., verbal responses, joystick movement, and simplified body movement). In contrast, an equivalent amount of time was spent fixating on the penalty taker’s relative motions and the ball location for the in situ interception condition, which required the goalkeepers to attempt to make penalty saves. The data suggest that gaze and movement behaviors function differently, depending on the experimental task constraints selected for empirical investigations. These findings highlight the need for research on perceptual— motor behaviors to be conducted in representative experimental conditions to allow appropriate generalization of conclusions to performance environments.

Extending the task of diarization to speaker attribution

In this paper we extend the concept of speaker annotation within a single-recording, or speaker diarization, to a collection wide approach we call speaker attribution. Accordingly, speaker attribution is the task of clustering expectantly homogenous intersession clusters obtained using diarization according to common cross-recording identities. The result of attribution is a collection of spoken audio across multiple recordings attributed to speaker identities. In this paper, an attribution system is proposed using mean-only MAP adaptation of a combined-gender UBM to model clusters from a perfect diarization system, as well as a JFA-based system with session variability compensation. The normalized cross-likelihood ratio is calculated for each pair of clusters to construct an attribution matrix and the complete linkage algorithm is employed to conduct clustering of the inter-session clusters. A matched cluster purity and coverage of 87.1% was obtained on the NIST 2008 SRE corpus.