162 resultados para ore facial pain


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Facial expression recognition (FER) has been dramatically developed in recent years, thanks to the advancements in related fields, especially machine learning, image processing and human recognition. Accordingly, the impact and potential usage of automatic FER have been growing in a wide range of applications, including human-computer interaction, robot control and driver state surveillance. However, to date, robust recognition of facial expressions from images and videos is still a challenging task due to the difficulty in accurately extracting the useful emotional features. These features are often represented in different forms, such as static, dynamic, point-based geometric or region-based appearance. Facial movement features, which include feature position and shape changes, are generally caused by the movements of facial elements and muscles during the course of emotional expression. The facial elements, especially key elements, will constantly change their positions when subjects are expressing emotions. As a consequence, the same feature in different images usually has different positions. In some cases, the shape of the feature may also be distorted due to the subtle facial muscle movements. Therefore, for any feature representing a certain emotion, the geometric-based position and appearance-based shape normally changes from one image to another image in image databases, as well as in videos. This kind of movement features represents a rich pool of both static and dynamic characteristics of expressions, which playa critical role for FER. The vast majority of the past work on FER does not take the dynamics of facial expressions into account. Some efforts have been made on capturing and utilizing facial movement features, and almost all of them are static based. These efforts try to adopt either geometric features of the tracked facial points, or appearance difference between holistic facial regions in consequent frames or texture and motion changes in loca- facial regions. Although achieved promising results, these approaches often require accurate location and tracking of facial points, which remains problematic.

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Many research and development projects that are carried out by firms and research institutes are technology-oriented. There is a large gap between research results, for instance in the form of prototypes, and the actual service offerings to customers. This becomes problematic when an organization wants to bring the results from such a project to the market, which will be particularly troublesome when the research results do not readily fit traditional offerings, roles and capabilities in the industry, nor the financial arrangements. In this chapter, we discuss the design of a business model for a mobile health service, starting with a research prototype that was developed for patients with chronic lower back pain, using the STOF model and method. In a number of design sessions, an initial business model was developed that identifies critical design issues that play a role in moving from prototype toward market deployment. The business model serves as a starting-point to identify and commit relevant stakeholders, and to draw up a business plan and case. This chapter is structured as follows. We begin by discussing the need for mobile health business models. Next, the research and development project on mobile health and the prototype for chronic lower back pain patients are introduced, after which the approach used to develop the business model is described, followed by a discussion of the developed mobile health business model for each of the STOF domains. We conclude with a discussion regarding the lessons that were learned with respect to the development of a business model on the basis of a prototype.

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The five quantities of interest in elementary finance problems are present value, future value, amount of periodic payment, number of periods and the rate of compound interest per period. A recursive approach to computing each of these five quantities in a modern version of Excel, for the case of ordinary annuities, is described. The aim is to increase student understanding and build confidence in the answer obtained, and this may be achieved with only linear relationships and in cases where student knowledge of algebra is essentially zero. Annuity problems may be solved without use of logarithms and black-box intrinsic functions; these being used only as check mechanisms. The author has had success with the method at Bond University and surrounding high schools in Queensland, Australia.

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Background Hallux valgus (HV) is highly prevalent and associated with progressive first metatarsophalangeal joint subluxation and osteoarthritis. The link between structural HV deformity and foot pain is unclear. This study investigated possible explanatory factors surrounding foot pain in HV, including radiographic HV angle and signs of joint degeneration. Methods Participants were 60 adults (53 female) with HV aged 20 to 75 years. Participant demographics and a range of radiographic, clinical and functional measures were considered potential correlates of foot pain. Self-reported foot pain (visual analogue scales and a dichotomous definition) was considered the dependent variable. Multivariate modelling was used to determine which characteristics and measures explained pain, with univariate analyses first used to screen potential variables. Results Approximately 20 to 30% of the variance in foot pain associated with HV could be explained by patient characteristics such as poorer general health status, lower educational attainment and increased occupational physical activity levels, in combination with some dynamic physical characteristics such as hallux plantarflexion weakness and reduced force-time integral under the second metatarsal during gait. Neither increasing lateral deviation of the hallux (HV angle) nor presence of first metatarsophalangeal joint osteoarthritis was associated with foot pain. Conclusions This study shows that passive structural factors, including HV angle, do not appear to be significant correlates of foot pain intensity in HV. Our data demonstrate the importance of considering patient characteristics such as general health and physical activity levels when assessing foot pain associated with HV.

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The proliferation of news reports published in online websites and news information sharing among social media users necessitates effective techniques for analysing the image, text and video data related to news topics. This paper presents the first study to classify affective facial images on emerging news topics. The proposed system dynamically monitors and selects the current hot (of great interest) news topics with strong affective interestingness using textual keywords in news articles and social media discussions. Images from the selected hot topics are extracted and classified into three categorized emotions, positive, neutral and negative, based on facial expressions of subjects in the images. Performance evaluations on two facial image datasets collected from real-world resources demonstrate the applicability and effectiveness of the proposed system in affective classification of facial images in news reports. Facial expression shows high consistency with the affective textual content in news reports for positive emotion, while only low correlation has been observed for neutral and negative. The system can be directly used for applications, such as assisting editors in choosing photos with a proper affective semantic for a certain topic during news report preparation.

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Introduction Clinical guidelines for the treatment of chronic low back pain suggest the use of supervised exercise. Motor control (MC) based exercise is widely used within clinical practice but its efficacy is equivalent to general exercise therapy. MC exercise targets the trunk musculature. Considering the mechanical links between the hip, pelvis, and lumbar spine, surprisingly little focus has been on investigating the contribution of the hip musculature to lumbopelvic support. The purpose of this study is to compare the efficacy of two exercise programs for the treatment of non-specific low back pain (NSLBP). Methods Eighty individuals aged 18-65 years of age were randomized into two groups to participate in this trial. The primary outcome measures included self-reported pain intensity (0-100mm VAS) and percent disability (Oswestry Disability Index V2). Bilateral measures of hip strength (N/kg) and two dimensional frontal plane mechanics (º) were the secondary outcomes. Outcomes were measured at baseline and following a six-week home based exercise program including weekly sessions of real-time ultrasound imaging. Results Within group comparisons revealed clinically meaningful reductions in pain for both groups. The MC exercise only (N= 40, xˉ =-20.9mm, 95%CI -25.7, -16.1) and the combined MC and hip exercise (N= 40, xˉ = -24.9mm, 95%CI -30.8, -19.0). There was no statistical difference in the change of pain (xˉ =-4.0mm, t= -1.07, p=0.29, 95%CI -11.5, 3.5) or disability (xˉ =-0.3%, t=-0.19, p=0.85, 95%CI -11.5, 3.5) between groups. Conclusion Both exercise programs had similar and positive effects on NSLBP which support the use of the home based exercise programs with weekly supervised visits. However, the addition of specific hip strengthening exercises to a MC based exercise program did not result in significantly greater reductions in pain or disability. Trial Registration NCTO1567566 Funding: Worker’s Compensation Board Alberta Research Grant.

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We employed a novel cuing paradigm to assess whether dynamically versus statically presented facial expressions differentially engaged predictive visual mechanisms. Participants were presented with a cueing stimulus that was either the static depiction of a low intensity expressed emotion; or a dynamic sequence evolving from a neutral expression to the low intensity expressed emotion. Following this cue and a backwards mask, participants were presented with a probe face that displayed either the same emotion (congruent) or a different emotion (incongruent) with respect to that displayed by the cue although expressed at a high intensity. The probe face had either the same or different identity from the cued face. The participants' task was to indicate whether or not the probe face showed the same emotion as the cue. Dynamic cues and same identity cues both led to a greater tendency towards congruent responding, although these factors did not interact. Facial motion also led to faster responding when the probe face was emotionally congruent to the cue. We interpret these results as indicating that dynamic facial displays preferentially invoke predictive visual mechanisms, and suggest that motoric simulation may provide an important basis for the generation of predictions in the visual system.

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Emotionally arousing events can distort our sense of time. We used mixed block/event-related fMRI design to establish the neural basis for this effect. Nineteen participants were asked to judge whether angry, happy and neutral facial expressions that varied in duration (from 400 to 1,600 ms) were closer in duration to either a short or long duration they learnt previously. Time was overestimated for both angry and happy expressions compared to neutral expressions. For faces presented for 700 ms, facial emotion modulated activity in regions of the timing network Wiener et al. (NeuroImage 49(2):1728–1740, 2010) namely the right supplementary motor area (SMA) and the junction of the right inferior frontal gyrus and anterior insula (IFG/AI). Reaction times were slowest when faces were displayed for 700 ms indicating increased decision making difficulty. Taken together with existing electrophysiological evidence Ng et al. (Neuroscience, doi: 10.3389/fnint.2011.00077, 2011), the effects are consistent with the idea that facial emotion moderates temporal decision making and that the right SMA and right IFG/AI are key neural structures responsible for this effect.