Risk of falls, injurious falls, and other injuries resulting from visual impairment among older adults with age-related macular degeneration

Purpose: Age-related macular degeneration (AMD) is the leading cause of irreversible visual impairment among older adults. This study explored the relationship between AMD, falls risk and other injuries and identified visual risk factors for these adverse events. Methods: Participants included 76 community-dwelling individuals with a range of severity of AMD (mean age, 77.0±6.9 years). Baseline assessment included binocular visual acuity, contrast sensitivity and merged visual fields. Participants completed monthly falls and injury diaries for one year following the baseline assessment. Results: Overall, 74% of participants reported having either a fall, injurious fall or other injury. Fifty-four percent of participants reported a fall and 30% reported more than one fall; of the 102 falls reported, 63% resulted in an injury. Most occurred outdoors (52%), between late morning and late afternoon (61%) and when navigating on level ground (62%). The most common non-fall injuries were lacerations (36%) and collisions with an object (35%). Reduced contrast sensitivity and visual acuity were associated with increased fall rate, after controlling for age, gender, cognitive function, cataract severity and self-reported physical function. Reduced contrast sensitivity was the only significant predictor of falls and other injuries. Conclusion: Among older adults with AMD, increased visual impairment was significantly associated with an increased incidence of falls and other injuries. Reduced contrast sensitivity was significantly associated with increased rates of falls, injurious falls and injuries, while reduced visual acuity was only associated with increased falls risk. These findings have important implications for the assessment of visually impaired older adults.

Evaluation of texture and geometry for dimensional facial expression recognition

Facial expression recognition (FER) algorithms mainly focus on classification into a small discrete set of emotions or representation of emotions using facial action units (AUs). Dimensional representation of emotions as continuous values in an arousal-valence space is relatively less investigated. It is not fully known whether fusion of geometric and texture features will result in better dimensional representation of spontaneous emotions. Moreover, the performance of many previously proposed approaches to dimensional representation has not been evaluated thoroughly on publicly available databases. To address these limitations, this paper presents an evaluation framework for dimensional representation of spontaneous facial expressions using texture and geometric features. SIFT, Gabor and LBP features are extracted around facial fiducial points and fused with FAP distance features. The CFS algorithm is adopted for discriminative texture feature selection. Experimental results evaluated on the publicly accessible NVIE database demonstrate that fusion of texture and geometry does not lead to a much better performance than using texture alone, but does result in a significant performance improvement over geometry alone. LBP features perform the best when fused with geometric features. Distributions of arousal and valence for different emotions obtained via the feature extraction process are compared with those obtained from subjective ground truth values assigned by viewers. Predicted valence is found to have a more similar distribution to ground truth than arousal in terms of covariance or Bhattacharya distance, but it shows a greater distance between the means.

Sparse temporal representations for facial expression recognition

In automatic facial expression recognition, an increasing number of techniques had been proposed for in the literature that exploits the temporal nature of facial expressions. As all facial expressions are known to evolve over time, it is crucially important for a classifier to be capable of modelling their dynamics. We establish that the method of sparse representation (SR) classifiers proves to be a suitable candidate for this purpose, and subsequently propose a framework for expression dynamics to be efficiently incorporated into its current formulation. We additionally show that for the SR method to be applied effectively, then a certain threshold on image dimensionality must be enforced (unlike in facial recognition problems). Thirdly, we determined that recognition rates may be significantly influenced by the size of the projection matrix \Phi. To demonstrate these, a battery of experiments had been conducted on the CK+ dataset for the recognition of the seven prototypic expressions - anger, contempt, disgust, fear, happiness, sadness and surprise - and comparisons have been made between the proposed temporal-SR against the static-SR framework and state-of-the-art support vector machine.

Preventing injuries on a state-wide basis : researchers and parliamentary committees are partners in turning injury prevention and safety research into practice and policy

Context: Parliamentary committees established in Westminster parliaments, such as Queensland, provide a cross-party structure that enables them to recommend policy and legislative changes that may otherwise be difficult for one party to recommend. The overall parliamentary committee process tends to be more cooperative and less adversarial than the main chamber of parliament and, as a result, this process permits parliamentary committees to make recommendations more on the available research evidence and less on political or party considerations. Objectives: This paper considers the contributions that parliamentary committees in Queensland have made in the past in the areas of road safety, drug use as well as organ and tissue donation. The paper also discusses the importance of researchers actively engaging with parliamentary committees to ensure the best evidence based policy outcomes. Key messages: In the past, parliamentary committees have successfully facilitated important safety changes with many committee recommendations based on research results. In order to maximise the benefits of the parliamentary committee process it is essential that researchers inform committees about their work and become key stakeholders in the inquiry process. Researchers can keep committees informed by making submissions to their inquiries, responding to requests for information and appearing as witnesses at public hearings. Researchers should emphasise the key findings and implications of their research as well as considering the jurisdictional implications and political consequences. It is important that researchers understand the differences between lobbying and providing informed recommendations when interacting with committees. Discussion and conclusions: Parliamentary committees in Queensland have successfully assisted in the introduction of evidence based policy and legislation. In order to present best practice recommendations, committees rely on the evidence presented to them including the results of researchers. Actively engaging with parliamentary committees will help researchers to turn their results into practice with a corresponding decrease in injuries and fatalities. Developing an understanding of parliamentary committees, and the typical inquiry process used by these committees, will help researchers to present their research results in a manner that will encourage the adoption of their ideas by parliamentary committees, the presentation of these results as recommendations within the report and the subsequent enactment of the committee’s recommendations by the government.

Hamstring strain injuries : factors that lead to injury and re-injury

Hamstring strain injuries (HSIs) are common in a number of sports and incidence rates have not declined in recent times. Additionally, the high rate of recurrent injuries suggests that our current understanding of HSI and re-injury risk is incomplete. Whilst the multifactoral nature of HSIs is agreed upon by many, often individual risk factors and/or causes of injury are examined in isolation. This review aims to bring together the causes, risk factors and interventions associated with HSIs to better understand why HSIs are so prevalent. Running is often identified as the primary activity type for HSIs and given the high eccentric forces and moderate muscle strain placed on the hamstrings during running these factors are considered to be part of the aetiology of HSIs. However, the exact causes of HSIs remain unknown and whilst eccentric contraction and muscle strain purportedly play a role, accumulated muscle damage and/or a single injurious event may also contribute. Potentially, all of these factors interact to varying degrees depending on the injurious activity type (i.e. running, kicking). Furthermore, anatomical factors, such as the biarticular organization, the dual innervations of biceps femoris (BF), fibre type distribution, muscle architecture and the degree of anterior pelvic tilt, have all been implicated. Each of these variables impact upon HSI risk via a number of different mechanisms that include increasing hamstring muscle strain and altering the susceptibility of the hamstrings to muscle damage. Reported risk factors for HSIs include age, previous injury, ethnicity, strength imbalances, flexibility and fatigue. Of these, little is known, definitively, about why previous injury increases the risk of future HSIs. Nevertheless, interventions put in place to reduce the incidence of HSIs by addressing modifiable risk factors have focused primarily on increasing eccentric strength, correcting strength imbalances and improving flexibility. The response to these intervention programmes has been mixed with varied levels of success reported. A conceptual framework is presented suggesting that neuromuscular inhibition following HSIs may impede the rehabilitation process and subsequently lead to maladaptation of hamstring muscle structure and function, including preferentially eccentric weakness, atrophy of the previously injured muscles and alterations in the angle of peak knee flexor torque. This remains an area for future research and practitioners need to remain aware of the multifactoral nature of HSIs if injury rates are to decline.

Safeguarding rural Australia: addressing masculinity and violence in rural settings : unintentional violent harm including injuries in an Australian rural context : analysis of secondary data analysis

This report is an update of an earlier one produced in January 2010 (see Carrington et al. 2010) which remains as an ePrint through the project’s home page. This report focuses on our examination of extant data which have been sourced with respect to unintentional serious and violent harm, including injuries, to males living in regional and remote Australia . and which were available in public data bases at production. Such harm typically might be caused by, for example, transport accidents, occupational exposures and hazards, burns and so on. Thus unintentional violent harm can cause physical trauma the consequences of which can lead to chronic conditions including psychological harm or substance abuse.

Personal Injuries Proceedings Act 2002, s 32 - Duty to Disclose - consequences of non-disclosure - discretion to excuse non-compliance

In Newson v Aust Scan Pty Ltd t/a Ikea Springwood [2010] QSC 223 the Supreme Court examined the discretion under s 32(2) of the Personal Injuries Proceedings Act 2002 (Qld), to permit a document which has not been disclosed as required by the pre-court procedures under the PIPA to be used in a subsequent court proceeding. This appears to be the first time that the nature and parameters of the discretion have been judicially considered.

On the relationships between self-reported bicycling injuries and perceived risk among cyclists in Queensland, Australia

The focus of governments on increasing active travel has motivated renewed interest in cycling safety. Bicyclists are up to 20 times more likely to be involved in serious injury crashes than drivers so understanding the relationship among factors in bicyclist crash risk is critically important for identifying effective policy tools, for informing bicycle infrastructure investments, and for identifying high risk bicycling contexts. This study aims to better understand the complex relationships between bicyclist self reported injuries resulting from crashes (e.g. hitting a car) and non-crashes (e.g. spraining an ankle) and perceived risk of cycling as a function of cyclist exposure, rider conspicuity, riding environment, rider risk aversion, and rider ability. Self reported data from 2,500 Queensland cyclists are used to estimate a series of seemingly unrelated regressions to examine the relationships among factors. The major findings suggest that perceived risk does not appear to influence injury rates, nor do injury rates influence perceived risks of cycling. Riders who perceive cycling as risky tend not to be commuters, do not engage in group riding, tend to always wear mandatory helmets and front lights, and lower their perception of risk by increasing days per week of riding and by increasing riding proportion on bicycle paths. Riders who always wear helmets have lower crash injury risk. Increasing the number of days per week riding tends to decrease both crash injury and non crash injury risk (e.g. a sprain). Further work is needed to replicate some of the findings in this study.

No evidence for subliminal affective priming with emotional facial expression primes

The present study investigated whether facial expressions of emotion presented outside consciousness awareness will elicit evaluative responses as assessed in affective priming. Participants were asked to evaluate pleasant and unpleasant target words that were preceded by masked or unmasked schematic (Experiment 1) or photographic faces (Experiments 1 and 2) with happy or angry expressions. They were either required to perform the target evaluation only or to perform the target evaluation and to name the emotion expressed by the face prime. Prime-target interval was 300 ms in Experiment 1 and 80 ms in Experiment 2. Naming performance confirmed the effectiveness of the masking procedure. Affective priming was evident after unmasked primes in tasks that required naming of the facial expressions for schematic and photographic faces and after unmasked primes in tasks that did not require naming for photographic faces. No affective priming was found after masked primes. The present study failed to provide evidence for affective priming with masked face primes, however, it indicates that voluntary attention to the primes enhances affective priming.

Discovering the best feature extraction and selection algorithms for spontaneous facial expression recognition

Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

Improved facial expression recognition via uni-hyperplane classification

Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.