Development of a Cardiac Auscultation Virtual Reality App

La auscultación cardiaca es un procedimiento que permite diagnosticar la condición del corazón de un paciente haciendo uso de un estetoscopio. Una examinaciOn apropiada con el estetoscopio puede resultar en un adecuado diagnóstico y tratamiento. Habilidades en auscultación cardiaca están en decaimiento entre practicantes y profesionales de áreas relacionadas al cuidado de la salud debido al extenso tiempo requerido de entrenamiento. Herramientas actuales de entrenamiento incluyen maniquíes de simulación y equipamiento de diagnóstico que está tomando un papel con mayor prominencia en la práctica de auscultación cardiaca que el entrenamiento con el estetoscopio. De acuerdo con la Organización Mundial de la Salud, en 2015 los dos causantes más grandes de muerte fueron ataques al corazón y enfermedades cerebrovasculares. La disponibilidad y bajo costos del estetoscopio lo hace una herramienta rentable en el entrenamiento en auscultación cardiaca. Actualmente, dispositivos de realidad virtual disponibles para el consumidor común están permitiendo el desarrollo de experiencias virtuales asequibles que tienen el potencial para complementar otras formas de entrenamiento. En este trabajo se presenta una aplicación móvil que combina elementos multimedia tales como sonidos de ritmos cardiacos e imágenes indicando áreas donde la exploración cardiaca debería ser llevada a cabo. Modelados 3D con animaciones realistas de pacientes con diferentes características físicas para simulación y texto explicativo para el diagnóstico fueron usados para proveer inmersión y realismo. El sistema está basado en el procedimiento de entrenamiento en auscultación cardiaca, haciendo uso de elementos de juego para enganchar y motivar los usuarios en el proceso de aprendizaje.Cardiac auscultation is a procedure that allows diagnosing a patient’s heart condition making use of the stethoscope. Proper examination skills with the stethoscope may result in proper diagnostics and treatment. Auscultation skills are in decay among health care trainees and even professionals, due to the required extensive training. Current training tools include simulation manikins and diagnostics equipment that is taking a more prominent role in auscultation practice than the training with the stethoscope. According to the World Health Organization, in 2015 the top two causes of death were ischaemic heart disease and stroke. The availability and low cost of the stethoscope makes it a cost-effective tool in cardiac auscultation skills. Currently, virtual reality consumer-grade devices are allowing the development of affordable virtual experiences that have the potential to complement other forms of training. In this work a mobile app combines multimedia elements such as heart rhythm sounds and images indicating areas where cardiac exploration should be performed is presented. 3D models with realistic animations of patients with different physical characteristics for the simulation and explanatory text for the diagnosis were used to provide immersion and realism. The system is based on the cardiac auscultation training procedure, making use of game elements in order to engage and motivate users in the learning process.Pregrad

Proceedings, MSVSCC 2019

Old Dominion University Department of Modeling, Simulation & Visualization Engineering (MSVE) and the Virginia Modeling, Analysis and Simulation Center (VMASC) held the 13th annual Modeling, Simulation & Visualization (MSV) Student Capstone Conference on April 18, 2019. The Conference featured student research and student projects that are central to MSV. Also participating in the conference were faculty members who volunteered their time to impart direct support to their students’ research, facilitated the various conference tracks, served as judges for each of the tracks, and provided overall assistance to the conference. Appreciating the purpose of the conference and working in a cohesive, collaborative effort, resulted in a successful symposium for everyone involved. These proceedings feature the works that were presented at the conference. Capstone Conference Chair: Dr. Yuzhong Shen Capstone Conference Student Chair: Daniel Pere

Deep Learning Based Malware Classification Using Deep Residual Network

The traditional malware detection approaches rely heavily on feature extraction procedure, in this paper we proposed a deep learning-based malware classification model by using a 18-layers deep residual network. Our model uses the raw bytecodes data of malware samples, converting the bytecodes to 3-channel RGB images and then applying the deep learning techniques to classify the malwares. Our experiment results show that the deep residual network model achieved an average accuracy of 86.54% by 5-fold cross validation. Comparing to the traditional methods for malware classification, our deep residual network model greatly simplify the malware detection and classification procedures, it achieved a very good classification accuracy as well. The dataset we used in this paper for training and testing is Malimg dataset, one of the biggest malware datasets released by vision research lab of UCSB

2018 Annual Research Symposium Abstract Book

2018 annual volume of abstracts for science research projects conducted by students at Trinity College

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

Designing and implementing online assessment in the clinical workplace

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Digital assessment in the clinical workplace : Design, implementation, opportunities, challenges

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Scholarship is not just research : Nurturing scholarship in health professions education

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