182 research outputs found

    Handheld image acquisition with real-time vision for human-computer interaction on mobile applications

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    Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica), Universidade de Lisboa, Faculdade de Ciências, 2019Várias patologias importantes manifestam-se na retina, sendo que estas podem ter origem na própria retina ou então provirem de doenças sistémicas. A retinopatia diabética, o glaucoma e a degeneração macular relacionada com a idade são algumas dessas patologias oculares, e também as maiores causas de cegueira nos países desenvolvidos. Graças à maior prevalência que se tem verificado, tem havido uma aposta cada vez maior na massificação do rastreio destas doenças, principalmente na população mais suscetível de as contrair. Visto que a retina é responsável pela formação de imagens, ou seja, pelo sentido da visão, os componentes oculares que estão localizados anteriormente têm de ser transparentes, permitindo assim a passagem da luz. Isto faz com que a retina e, por sua vez, o tecido cerebral, possam ser examinados de forma não-invasiva. Existem várias técnicas de imagiologia da retina, incluindo a angiografia fluoresceínica, a tomografia de coerência ótica e a retinografia. O protótipo EyeFundusScope (EFS) da Fraunhofer é um retinógrafo portátil, acoplado a um smartphone, que permite a obtenção de imagens do fundo do olho, sem que seja necessária a dilatação da pupila. Utiliza um algoritmo de aprendizagem automática para detetar lesões existentes na retina, que estão normalmente associadas a um quadro de retinopatia diabética. Para além disso, utiliza um sistema de suporte à decisão, que indica a ausência ou presença da referida retinopatia. A fiabilidade deste tipo de algoritmos e o correto diagnóstico por parte de oftalmologistas e neurologistas estão extremamente dependentes da qualidade das imagens adquiridas. A consistência da captura portátil, com este tipo de retinógrafos, está intimamente relacionada com uma interação apropriada com o utilizador. De forma a melhorar o contributo prestado pelo utilizador, durante o procedimento habitual da retinografia, foi desenvolvida uma nova interface gráfica de utilizador, na aplicação Android do EFS. A abordagem pretendida consiste em tornar o uso do EFS mais acessível, e encorajar técnicos não especializados a utilizarem esta técnica de imagem médica, tanto em ambiente clínico como fora deste. Composto por vários elementos de interação, que foram criados para atender às necessidades do protocolo de aquisição de imagem, a interface gráfica de utilizador deverá auxiliar todos os utilizadores no posicionamento e alinhamento do EFS com a pupila do doente. Para além disto, poderá existir um controlo personalizado do tempo despendido em aquisições do mesmo olho. Inicialmente, foram desenhadas várias versões dos elementos de interação rotacionais, sendo posteriormente as mesmas implementadas na aplicação Android. Estes elementos de interação utilizam os dados recolhidos dos sensores inerciais, já existentes no smartphone, para transmitir uma resposta em tempo real ao utilizador enquanto este move o EFS. Além dos elementos de interação rotacionais, também foram implementados um temporizador e um indicador do olho que está a ser examinado. Após a implementação de três configurações com as várias versões dos elementos de interação, procedeu-se à realização dos testes de usabilidade. No entanto, antes desta etapa se poder concretizar, foram realizados vários acertos e correções com a ajuda de um olho fantoma. Durante o planeamento dos testes de usabilidade foi estabelecido um protocolo para os diferentes cenários de uso e foi criado um tutorial com as principais cautelas que os utilizadores deveriam ter aquando das aquisições. Os resultados dos testes de usabilidade mostram que a nova interface gráfica teve um efeito bastante positivo na experiência dos utilizadores. A maioria adaptou-se rapidamente à nova interface, sendo que para muitos contribuiu para o sucesso da tarefa de aquisição de imagem. No futuro, espera-se que a combinação dos dados fornecidos pelos sensores inerciais, juntamente com a implementação de novos algoritmos de reconhecimento de imagem, sejam a base de uma nova e mais eficaz técnica de interação em prática clínica. Além disso, a nova interface gráfica poderá proporcionar ao EFS uma aplicação que sirva exclusivamente para efeitos de formação profissional.Many important diseases manifest themselves in the retina, both primary retinal conditions and systemic disorders. Diabetic retinopathy, glaucoma and age-related macular degeneration are some of the most frequent ocular disorders and the leading causes of blindness in developed countries. Since these disorders are becoming increasingly prevalent, there has been the need to encourage high coverage screening among the most susceptible population. As its function requires the retina to see the outside world, the involved optical components must be transparent for image formation. This makes the retinal tissue, and thereby brain tissue, accessible for imaging in a non-invasive manner. There are several approaches to visualize the retina including fluorescein angiography, optical coherence tomography and fundus photography. The Fraunhofer’s EyeFundusScope (EFS) prototype is a handheld smartphone-based fundus camera, that doesn’t require pupil dilation. It employs advanced machine learning algorithms to process the image in search of lesions that are often associated with diabetic retinopathy, making it a pre-diagnostic tool. The robustness of this computer vision algorithm, as well as the diagnose performance of ophthalmologists and neurologists, is strongly related with the quality of the images acquired. The consistency of handheld capture deeply depends on proper human interaction. In order to improve the user’s contribution to the retinal acquisition procedure, a new graphical user interface was designed and implemented in the EFS Acquisition App. The intended approach is to make the EFS easier to use by non-ophthalmic trained personnel, either in a non-clinical or in a clinical environment. Comprised of several interaction elements that were created to suit the needs of the acquisition procedure, the graphical user interface should help the user to position and align the EFS illumination beam with the patient’s pupil as well as keeping track of the time between acquisitions on the same eye. Initially, several versions of rotational interaction elements were designed and later implemented on the EFS Acquisition App. These used data from the smartphone’s inertial sensors to give real-time feedback to the user while moving the EFS. Besides the rotational interactional elements, a time-lapse and an eye indicator were also designed and implemented in the EFS. Usability tests took place, after three assemblies being successfully implemented and corrected with the help of a model eye ophthalmoscope trainer. Also, a protocol for the different use-case scenarios was elaborated, and a tutorial was created. Results from the usability tests, show that the new graphical user interface had a very positive outcome. The majority of users adapted very quickly to the new interface, and for many it contributed for a successful acquisition task. In the future, the grouping of inertial sensors data and image recognition may prove to be the foundations for a more efficient interaction technique performed in clinical practices. Furthermore, the new graphical user interface could provide the EFS with an application for educational purposes

    Game Based Learning for Safety and Security Education

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    Safety and security education are important part of technology related education, because of recent number of increase in safety and security related incidents. Game based learning is an emerging and rapidly advancing forms of computer-assisted instruction. Game based learning for safety and security education enables students to learn concepts and skills without the risk of physical injury and security breach. In this paper, a pedestal grinder safety game and physical security game have been developed using industrial standard modeling and game development software. The average score of the knowledge test of grinder safety game was 82%, which is higher than traditional lecture only instruction method. In addition, the survey of physical security game shows 84% average satisfaction ratio from high school students who played the game during the summer camp. The results of these studies indicated that game based learning method can enhance students' learning without potential harm to the students

    Introductory Chapter: Why Usability Matters

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    Justifying Breaking the Glass: How Accountability Can Deter Unauthorized Access

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    This research-in-progress study examines how accountability—the expectation that one will be required to answer for one’s actions, and justification—the requirement to give reasons for performing an action—can reduce instances of break-the-glass violations—can encourage compliance with data access policies. We examine whether justification can embolden users to break the glass in warranted situations, and deter users in inappropriate situations. We propose a series of lab experiments to test our hypotheses. We expect that our results will have implications for research on information security policy (ISP) compliance and practice

    A review of privacy and usability issues in mobile health systems: Role of external factors

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    The increased penetration of mobile devices has created opportunities in the health sector and led to emerging of mobile health systems. As much as the mobile health systems have registered tremendous progress, they have been faced with privacy and usability issues. Due to the sensitivity of health information, there is an ethical need to equip mobile health systems with adequate privacy measures. However, these systems should also be useable by the intended users. Even though many researchers are working on solutions, the issues still persist. External factors such as cultural differences have also contributed to the issues, yet they have been under researched. In this article, we conduct a systematic literature review of 22 articles, categorize and present privacy and usability issues and possible solutions. We then discuss the relevance and implications of external factors to the findings on privacy and usability. We end with recommendations to address these external factors.Peer Reviewe

    Understanding the Experience of Interprofessional Team Members after Participating in Comprehensive Obstetric Hemorrhage Training

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    Purpose: The obstetric hemorrhage rate has risen steadily in the U.S. accounting for 11.4% of maternal deaths between 2011 and 2013, and remains a leading cause of maternal morbidity. Improving the quality and safety of care could prevent much of the morbidity and potential mortality associated with obstetric hemorrhages. An interprofessional obstetric team developed, tested, and implemented obstetric hemorrhage and massive transfusion protocols. Multi-modal team training occurred before service-wide implementation of the protocols, including didactic, skills stations, on-line educational modules, and in situ simulation team training. Early quantitative results were promising. Methods: To augment understanding of the quantitative results and to understand the experience of interprofessional team members after participating in obstetric hemorrhage training; an exploratory, medically-focused, ethnographic qualitative study was conducted in a five-year old obstetric service within a large, metropolitan, tertiary, free-standing pediatric hospital. Participants were purposively sampled from interprofessional obstetric team members who cared for obstetric hemorrhage patients and participated in hemorrhage training. Data was generated during field observations, and individual and focus group interviews. Results: Twenty (n = 89 participants) semi-structured interviews were conducted. An inductive, descriptive thematic analysis of the data revealed two central themes: Knowing, and Teaming. Knowing was influenced by training and experience with obstetric hemorrhages, and was further influenced by interactions among members of the interprofessional obstetric team within the complex, non-linear environment. Teaming was reported as a compelling benefit of engaging the interprofessional obstetric team in simulation team training. Simulation training helped the team know how to use the protocols, and improved team functioning during obstetric hemorrhages. Conclusions: Similar to Benner’s model, training and experience influenced the knowing that obstetric team members applied during an obstetric hemorrhage event. Simulation team training promoted teaming, which helped the interprofessional obstetric team to effectively and efficiently manage an obstetric hemorrhage

    Challenges of implementing computer-aided diagnostic models for neuroimages in a clinical setting

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    Advances in artificial intelligence have cultivated a strong interest in developing and validating the clinical utilities of computer-aided diagnostic models. Machine learning for diagnostic neuroimaging has often been applied to detect psychological and neurological disorders, typically on small-scale datasets or data collected in a research setting. With the collection and collation of an ever-growing number of public datasets that researchers can freely access, much work has been done in adapting machine learning models to classify these neuroimages by diseases such as Alzheimer’s, ADHD, autism, bipolar disorder, and so on. These studies often come with the promise of being implemented clinically, but despite intense interest in this topic in the laboratory, limited progress has been made in clinical implementation. In this review, we analyze challenges specific to the clinical implementation of diagnostic AI models for neuroimaging data, looking at the differences between laboratory and clinical settings, the inherent limitations of diagnostic AI, and the different incentives and skill sets between research institutions, technology companies, and hospitals. These complexities need to be recognized in the translation of diagnostic AI for neuroimaging from the laboratory to the clinic.</p

    Evaluation of Game-Based Learning in Cybersecurity Education for High School Students

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    Game based learning is a new game play mechanism that the players explore various aspects of game play in a learning context designed by the instructor or the game designer. Nevertheless, general acceptance of game based learning as a new learning paradigm was deferred by a lack of well-controlled, large sample efficacy studies. To address the increasing need of cybersecurity workforce, this paper introduces a game based learning method for high school cybersecurity education. Purdue University Northwest launched GenCyber high school summer camps to about 200 high school students in Chicago metropolitan area. The survey conducted after the summer camp indicated that the game based learning for cybersecurity education was very effective in cybersecurity awareness training. Further analysis of survey data revealed that there is a gender difference in raising students' interests in cybersecurity and computer science education using game based learning method

    Data Loss Prevention Management and Control: Inside Activity Incident Monitoring, Identification, and Tracking in Healthcare Enterprise Environments

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    As healthcare data are pushed online, consumers have raised big concerns on the breach of their personal information. Law and regulations have placed businesses and public organizations under obligations to take actions to prevent data breach. Among various threats, insider threats have been identified to be a major threat on data loss. Thus, effective mechanisms to control insider threats on data loss are urgently needed. The objective of this research is to address data loss prevention challenges in healthcare enterprise environment. First, a novel approach is provided to model internal threat, specifically inside activities. With inside activities modeling, data loss paths and threat vectors are formally described and identified. Then, threat vectors and potential data loss paths have been investigated in a healthcare enterprise environment. Threat vectors have been enumerated and data loss statistics data for some threat vectors have been collected. After that, issues on data loss prevention and inside activity incident identification, tracking, and reconstruction are discussed. Finally, evidences of inside activities are modeled as evidence trees to provide guidance for inside activity identification and reconstruction
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