Ultrasonic waves: Bioeffects on yeast cells

Applications of ultrasound were starting from 1912 with the primary objective the detection of icebergs on prevention of maritime accidents. Algae, fish deaths and destruction were observed in the vicinity of sonar that equipped ships and submarines during the First World War.The evolutions of research and studies with ultrasound have big advances following the discovery of piezoelectric transducers in science and technology. As an example we can mention its application in microsurgery, fatigue detection in aerospace mechanics, catalysis sonochemical, biotechnology and others.The work presented here aims to demonstrate the application of ultrasonic in pulsed mode beams in biotechnology with the aim of improving the fermentation of a culture broth containing biological agents. In these experiments we used as ultrasound equipment and oscilator Sonics VCX-600 (20KHz), probe type wave guide. The experiments were conducted in a glass reactor of 200 mL of biomaterial containing cane juice and Saccharomyces cerevisiae in suspension. The parameters analyzed were related to the content Alcohlic (FID gas chromatography), and cell viability (Neubauer chamber), TRS (refractometry). Analysis of results showed that the total production exceeded in irradiated samples compared to normal fermentation (without ultrasound), suggesting additional advantage of ultrasound activation. Lastin Trials 1400 min, showed ethanol production systems 12% more than non-enabled systems. In this context alternatives for ethanol production, bio fuel and many other byproducts of the alcohol industries and chemicals could benefit from the use of ultrasound beams in this range of frequencies.

Online Alpha Wave detector: an Embedded hardware-software implementation

The recent trend on embedded system development opens a new prospect for applications that in the past were not possible. The eye tracking for sleep and fatigue detection has become an important and useful application in industrial and automotive scenarios since fatigue is one of the most prevalent causes of earth-moving equipment accidents. Typical applications such as cameras, accelerometers and dermal analyzers are present on the market but have some inconvenient. This thesis project has used EEG signal, particularly, alpha waves, to overcome them by using an embedded software-hardware implementation to detect these signals in real time

Differential effects of monotony versus fatigue on driving performance and the effectiveness of various detection methods : implications for road safety in the ACT

Background Situational driving factors, including fatigue, distraction, inattention and monotony, are recognised killers in Australia, contributing to an estimated 40% of fatal crashes and 34% of all crashes . More often than not the main contributing factor is identified as fatigue, yet poor driving performance has been found to emerge early in monotonous conditions, independent of fatigue symptoms and time on task. This early emergence suggests an important role for monotony. However, much road safety research suggests that monotony is solely a task characteristic that directly causes fatigue and associated symptoms and there remains an absence of consistent evidence explaining the relationship. Objectives We report an experimental study designed to disentangle the characteristics and effects of monotony from those associated with fatigue. Specifically, we examined whether poor driving performance associated with hypovigilance emerges as a consequence of monotony, independent of fatigue. We also examined whether monotony is a multidimensional construct, determined by environmental characteristics and/or task demands that independently moderate sustained attention and associated driving performance. Method Using a driving simulator, participants completed four, 40 minute driving scenarios. The scenarios varied in the degree of monotony as determined by the degree of variation in road design (e.g., straight roads vs. curves) and/or road side scenery. Fatigue, as well as a number of other factors known to moderate vigilance and driving performance, was controlled for. To track changes across time, driving performance was assessed in five minute time periods using a range of behavioural, subjective and physiological measures, including steering wheel movements, lane positioning, electroencephalograms, skin conductance, and oculomotor activity. Results Results indicate that driving performance is worse in monotonous driving conditions characterised by low variability in road design. Critically, performance decrements associated with monotony emerge very early, suggesting monotony effects operate independent of fatigue. Conclusion Monotony is a multi-dimensional construct where, in a driving context, roads containing low variability in design are monotonous and those high in variability are non-monotonous. Importantly, low variability in road side scenery does not appear to exacerbate monotony or associated poor performance. However, high variability in road side scenery can act as a distraction and impair sustained attention and poor performance when driving on monotonous roads. Furthermore, high sensation seekers seem to be more susceptible to distraction when driving on monotonous roads. Implications of our results for the relationship between monotony and fatigue, and the possible construct-specific detection methods in a road safety context, will be discussed.

A new rapid detection threshold method for use with older adults: reducing fatigue whilst maintaining accuracy

Taste and smell detection threshold measurements are frequently time consuming especially when the method involves reversing the concentrations presented to replicate and improve accuracy of results. These multiple replications are likely to cause sensory and cognitive fatigue which may be more pronounced in elderly populations. A new rapid detection threshold methodology was developed that quickly located the likely position of each individuals sensory detection threshold then refined this by providing multiple concentrations around this point to determine their threshold. This study evaluates the reliability and validity of this method. Findings indicate that this new rapid detection threshold methodology was appropriate to identify differences in sensory detection thresholds between different populations and has positive benefits in providing a shorter assessment of detection thresholds. The results indicated that this method is appropriate at determining individual as well as group detection thresholds.

A novel detection method for determining a surgeon's fatigue and hand tremor

The thesis presents new methodology and algorithms that can be used to analyse and measure the hand tremor and fatigue of surgeons while performing surgery. This will assist them in deriving useful information about their fatigue levels, and make them aware of the changes in their tool point accuracies. This thesis proposes that muscular changes of surgeons, which occur through a day of operating, can be monitored using Electromyography (EMG) signals. The multi-channel EMG signals are measured at different muscles in the upper arm of surgeons. The dependence of EMG signals has been examined to test the hypothesis that EMG signals are coupled with and dependent on each other. The results demonstrated that EMG signals collected from different channels while mimicking an operating posture are independent. Consequently, single channel fatigue analysis has been performed. In measuring hand tremor, a new method for determining the maximum tremor amplitude using Principal Component Analysis (PCA) and a new technique to detrend acceleration signals using Empirical Mode Decomposition algorithm were introduced. This tremor determination method is more representative for surgeons and it is suggested as an alternative fatigue measure. This was combined with the complexity analysis method, and applied to surgically captured data to determine if operating has an effect on a surgeon’s fatigue and tremor levels. It was found that surgical tremor and fatigue are developed throughout a day of operating and that this could be determined based solely on their initial values. Finally, several Nonlinear AutoRegressive with eXogenous inputs (NARX) neural networks were evaluated. The results suggest that it is possible to monitor surgeon tremor variations during surgery from their EMG fatigue measurements.

Robust suspicious behaviour detection for smart surveillance systems

Video surveillance technology, based on Closed Circuit Television (CCTV) cameras, is one of the fastest growing markets in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. To overcome this limitation, it is necessary to have “intelligent” processes which are able to highlight the salient data and filter out normal conditions that do not pose a threat to security. In order to create such intelligent systems, an understanding of human behaviour, specifically, suspicious behaviour is required. One of the challenges in achieving this is that human behaviour can only be understood correctly in the context in which it appears. Although context has been exploited in the general computer vision domain, it has not been widely used in the automatic suspicious behaviour detection domain. So, it is essential that context has to be formulated, stored and used by the system in order to understand human behaviour. Finally, since surveillance systems could be modeled as largescale data stream systems, it is difficult to have a complete knowledge base. In this case, the systems need to not only continuously update their knowledge but also be able to retrieve the extracted information which is related to the given context. To address these issues, a context-based approach for detecting suspicious behaviour is proposed. In this approach, contextual information is exploited in order to make a better detection. The proposed approach utilises a data stream clustering algorithm in order to discover the behaviour classes and their frequency of occurrences from the incoming behaviour instances. Contextual information is then used in addition to the above information to detect suspicious behaviour. The proposed approach is able to detect observed, unobserved and contextual suspicious behaviour. Two case studies using video feeds taken from CAVIAR dataset and Z-block building, Queensland University of Technology are presented in order to test the proposed approach. From these experiments, it is shown that by using information about context, the proposed system is able to make a more accurate detection, especially those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information give critical feedback to the system designers to refine the system. Finally, the proposed modified Clustream algorithm enables the system to both continuously update the system’s knowledge and to effectively retrieve the information learned in a given context. The outcomes from this research are: (a) A context-based framework for automatic detecting suspicious behaviour which can be used by an intelligent video surveillance in making decisions; (b) A modified Clustream data stream clustering algorithm which continuously updates the system knowledge and is able to retrieve contextually related information effectively; and (c) An update-describe approach which extends the capability of the existing human local motion features called interest points based features to the data stream environment.

A suspicious behaviour detection using a context space model for smart surveillance systems

Video surveillance systems using Closed Circuit Television (CCTV) cameras, is one of the fastest growing areas in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. This work attempts to address these problems by proposing an automatic suspicious behaviour detection which utilises contextual information. The utilisation of contextual information is done via three main components: a context space model, a data stream clustering algorithm, and an inference algorithm. The utilisation of contextual information is still limited in the domain of suspicious behaviour detection. Furthermore, it is nearly impossible to correctly understand human behaviour without considering the context where it is observed. This work presents experiments using video feeds taken from CAVIAR dataset and a camera mounted on one of the buildings Z-Block) at the Queensland University of Technology, Australia. From these experiments, it is shown that by exploiting contextual information, the proposed system is able to make more accurate detections, especially of those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information gives critical feedback to the system designers to refine the system.

A longitudinal study of health-related quality of life, fatigue and physical activity in chronic kidney disease patients

This study assessed the health-related quality of life (HRQoL), fatigue and physical activity levels of 28 persons with chronic kidney disease (CKD) on initial administration of an erythropoietin stimulating agent, and at 3 months, 6 months and 12 months. The sample comprised of 15 females and 13 males whose ages ranged from 31 to 84 years. Physical activity was measured using the Human Activity Profile (HAP): Self-care, Personal/Household work, Entertainment/Social, Independent exercise. Quality of life was measured using the SF-36 which gives scores on physical health (physical functioning, role-physical, bodily pain and general health) and mental health (vitality, social functioning, role-emotional and emotional well-being). Fatigue was measured by the Fatigue Severity Scale (FSS). Across all time points the renal sample engaged in considerably less HAP personal/household work activities and entertainment/social activities compared to healthy adults. The normative sample engaged in three times more independent/exercise activities compared to renal patients. One-way Repeated measures ANOVAs indicated a significant change over time for SF-36 scales of role physical, vitality, emotional well-being and overall mental health. There was a significant difference in fatigue levels over time [F(3,11) = 3.78, p<.05]. Fatigue was highest at baseline and lowest at 6 months. The more breathlessness the CKD patient reported, the fewer activities undertaken and the greater the reported level of fatigue. There were no significant age differences over time for fatigue or physical activity. Age differences were only found for SF-36 mental health at 3 months (t=-2.41, df=14, p<.05). Those younger than 65 years had lower emotional well-being compared to those aged over 65. Males had poorer physical health compared to females at 12 months. There were no significant gender differences on mental health at any time point. In the management of chronic kidney disease, early detection of a person’s inability to engage in routine activities due to fatigue is necessary. Early detection would enable timely interventions to optimise HRQoL and independent exercise.

Quality of life, fatigue and activity in Australians with chronic kidney disease : a longitudinal study

Aims and objectives This study sought to determine the relationship between health related quality of life (HRQoL), fatigue and activity levels of people with anaemia secondary to chronic kidney disease (CKD) over a 12 month period following the introduction of an erythropoietin stimulating agent (ESA). Background CKD occurs in five stages and it is a complex chronic illness which severely impacts on an individual’s HRQoL, and ability to perform everyday activities. Fatigue is also a common symptom experienced by people with CKD. Design and methods Using a longitudinal repeated measures design, 28 people with CKD completed the SF-36, human activity profile and fatigue severity scale at the commencement of an ESA and then at 3, 6 and 12 months. Results Over a 12 month period, people reported a significant change in HRQoL in relation to role physical, vitality, mental health/emotional well-being and overall mental health. However activity levels did not significantly improve during that time. Both the amount of breathlessness and level of fatigue were highest at baseline and declined over time. Both fatigue and breathlessness were correlated with less reported general health over time. Conclusion Renal nurses, in dialysis units and CKD outpatient clinics, have repeated and frequent contact with people with CKD over long periods of time, and are in an ideal position to routinely assess fatigue and activity levels and to institute timely interventions. Early detection would enable timely nursing interventions to optimise HRQoL and independent activity. Relevance to Clinical Practice Drawing on rehabilitation nursing interventions could assist renal nurses to minimize the burden of fatigue and its impact on simple everyday activities and a person’s quality of life. These interventions are important for people who are living at home and could assist in lowering the burden on home support services.

Modal flexibility method for structural damage detection in suspension bridges

Suspension bridges meet the steadily growing demand for lighter and longer bridges in today’s infrastructure systems. These bridges are designed to have long life spans, but with age, their main cables and hangers could suffer from corrosion and fatigue. There is a need for a simple and reliable procedure to detect and locate such damage, so that appropriate retrofitting can be carried out to prevent bridge failure. Damage in a structure causes changes in its properties (mass, damping and stiffness) which in turn will cause changes in its vibration characteristics (natural frequencies, modal damping and mode shapes). Methods based on modal flexibility, which depends on both the natural frequencies and mode shapes, have the potential for damage detection. They have been applied successfully to beam and plate elements, trusses and simple structures in reinforced concrete and steel. However very limited applications for damage detection in suspension bridges have been identified to date. This paper examines the potential of modal flexibility methods for damage detection and localization of a suspension bridge under different damage scenarios in the main cables and hangers using numerical simulation techniques. Validated finite element model (FEM) of a suspension bridge is used to acquire mass normalized mode shape vectors and natural frequencies at intact and damaged states. Damage scenarios will be simulated in the validated FE models by varying stiffness of the damaged structural members. The capability of damage index based on modal flexibility to detect and locate damage is evaluated. Results confirm that modal flexibility based methods have the ability to successfully identify damage in suspension bridge main cables and hangers.

Damage detection in cable structures using vibration characteristics

Cable structures find many applications such as in power transmission, in anchors and especially in bridges. They serve as major load bearing elements in suspension bridges, which are capable of spanning long distances. All bridges, including suspension bridges, are designed to have long service lives. However, during this long life, they become vulnerable to damage due to changes in loadings, deterioration with age and random action such as impacts. The main cables are more vulnerable to corrosion and fatigue, compared to the other bridge components, and consequently reduces the serviceability and ultimate capacity of the bridge. Detecting and locating such damage at the earliest stage is challenging in the current structural health monitoring (SHM) systems of long span suspension bridges. Damage or deterioration of a structure alters its stiffness, mass and damping properties which in turn modify its vibration characteristics. This phenomenon can therefore be used to detect damage in a structure. The modal flexibility, which depends on the vibration characteristics of a structure, has been identified as a successful damage indicator in beam and plate elements, trusses and simple structures in reinforced concrete and steel. Successful application of the modal flexibility phenomenon to detect and locate the damage in suspension bridge main cables has received limited attention in recent research work. This paper, therefore examines the potential of the modal flexibility based Damage Index (DI) for detecting and locating damage in the main cable of a suspension bridge under four different damage scenarios. Towards this end, a numerical model of a suspension bridge cable was developed to extract the modal parameters at both damaged and undamaged states. Damage scenarios considered in this study with varied location and severity were simulated by changing stiffness at particular locations of the cable model. Results confirm that the DI has the potential to successfully detect and locate damage in suspension bridge main cables. This simple method can therefore enable bridge engineers and managers to detect and locate damage in suspension bridges at an early stage, minimize expensive retrofitting and prevent bridge collapse.

Matrix Crack Detection in Composite Plate with Spatially Random Material Properties using Fractal Dimension

Fractal dimension based damage detection method is investigated for a composite plate with random material properties. Composite material shows spatially varying random material properties because of complex manufacturing processes. Matrix cracks are considered as damage in the composite plate. Such cracks are often seen as the initial damage mechanism in composites under fatigue loading and also occur due to low velocity impact. Static deflection of the cantilevered composite plate with uniform loading is calculated using the finite element method. Damage detection is carried out based on sliding window fractal dimension operator using the static deflection. Two dimensional homogeneous Gaussian random field is generated using Karhunen-Loeve (KL) expansion to represent the spatial variation of composite material property. The robustness of fractal dimension based damage detection method is demonstrated considering the composite material properties as a two dimensional random field.