Browsing by Subject "Augmented reality"

Now showing 1 - 5 of 5
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    Augmented Reality-Assisted Deep Reinforcement Learning-Based Model towards Industrial Training and Maintenance for NanoDrop Spectrophotometer
    (MDPI, 2023-06-29) Alatawi, Hibah; Albalawi, Nouf; Shahata, Ghadah; Aljohani, Khulud; Alhakamy, A’aeshah; Tuceryan, Mihran; Computer and Information Science, School of Science
    The use of augmented reality (AR) technology is growing in the maintenance industry because it can improve efficiency and reduce costs by providing real-time guidance and instruction to workers during repairs and maintenance tasks. AR can also assist with equipment training and visualization, allowing users to explore the equipment’s internal structure and size. The adoption of AR in maintenance is expected to increase as hardware options expand and development costs decrease. To implement AR for job aids in mobile applications, 3D spatial information and equipment details must be addressed, and calibrated using image-based or object-based tracking, which is essential for integrating 3D models with physical components. The present paper suggests a system using AR-assisted deep reinforcement learning (RL)-based model for NanoDrop Spectrophotometer training and maintenance purposes that can be used for rapid repair procedures in the Industry 4.0 (I4.0) setting. The system uses a camera to detect the target asset via feature matching, tracking techniques, and 3D modeling. Once the detection is completed, AR technologies generate clear and easily understandable instructions for the maintenance operator’s device. According to the research findings, the model’s target technique resulted in a mean reward of 1.000 and a standard deviation of 0.000. This means that all the rewards that were obtained in the given task or environment were exactly the same. The fact that the reward standard deviation is 0.000 shows that there is no variability in the outcomes.
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    Can Tele-Neuro-Ophthalmology Be Useful Beyond the Pandemic?
    (Springer Nature, 2023) Lai, Kevin E.; Ko, Melissa W.; Ophthalmology, School of Medicine
    Purpose of the review: Neuro-ophthalmologists rapidly adopted telehealth during the COVID-19 pandemic to minimize disruption to patient care. This article reviews recent research on tele-neuro-ophthalmology adoption, current limitations, and potential use beyond the pandemic. The review considers how digital transformation, including machine learning and augmented reality, may be applied to future iterations of tele-neuro-ophthalmology. Recent findings: Telehealth utilization has been sustained among neuro-ophthalmologists throughout the pandemic. Adoption of tele-neuro-ophthalmology may provide solutions to subspecialty workforce shortage, patient access, physician wellness, and trainee educational needs within the field of neuro-ophthalmology. Digital transformation technologies have the potential to augment tele-neuro-ophthalmology care delivery by providing automated workflow solutions, home-based visual testing and therapies, and trainee education via simulators. Tele-neuro-ophthalmology use has and will continue beyond the COVID-19 pandemic. Digital transformation technologies, when applied to telehealth, will drive and revolutionize the next phase of tele-neuro-ophthalmology adoption and use in the years to come.
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    Distributed Monocular SLAM for Indoor Map Building
    (Hindawi, 2017) Egodagamage, Ruwan; Tuceryan, Mihran; Computer and Information Science, School of Science
    Utilization and generation of indoor maps are critical elements in accurate indoor tracking. Simultaneous Localization and Mapping (SLAM) is one of the main techniques for such map generation. In SLAM an agent generates a map of an unknown environment while estimating its location in it. Ubiquitous cameras lead to monocular visual SLAM, where a camera is the only sensing device for the SLAM process. In modern applications, multiple mobile agents may be involved in the generation of such maps, thus requiring a distributed computational framework. Each agent can generate its own local map, which can then be combined into a map covering a larger area. By doing so, they can cover a given environment faster than a single agent. Furthermore, they can interact with each other in the same environment, making this framework more practical, especially for collaborative applications such as augmented reality. One of the main challenges of distributed SLAM is identifying overlapping maps, especially when relative starting positions of agents are unknown. In this paper, we are proposing a system having multiple monocular agents, with unknown relative starting positions, which generates a semidense global map of the environment.
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    e-DTS 2.0: A Next-Generation of a Distributed Tracking System
    (2012-03-20) Rybarczyk, Ryan Thomas; Raje, Rajeev; Tuceryan, Mihran; Linos, Panos
    A key component in tracking is identifying relevant data and combining the data in an effort to provide an accurate estimate of both the location and the orientation of an object marker as it moves through an environment. This thesis proposes an enhancement to an existing tracking system, the enhanced distributed tracking system (e-DTS), in the form of the e-DTS 2.0 and provides an empirical analysis of these enhancements. The thesis also provides suggestions on future enhancements and improvements. When a Camera identifies an object within its frame of view, it communicates with a JINI-based service in an effort to expose this information to any client who wishes to consume it. This aforementioned communication utilizes the JINI Multicast Lookup Protocol to provide the means for a dynamic discovery of any sensors as they are added or removed from the environment during the tracking process. The client can then retrieve this information from the service and perform a fusion technique in an effort to provide an estimation of the marker's current location with respect to a given coordinate system. The coordinate system handoff and transformation is a key component of the e-DTS 2.0 tracking process as it improves the agility of the system.
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    Virtual reality cognitive intervention for heart failure: CORE study protocol
    (Alzheimer’s Association, 2022-03-15) Jung, Miyeon; Apostolova, Liana G.; Moser, Debra K.; Gradus-Pizlo, Irmina; Gao, Sujuan; Rogers, Jeff L.; Pressler, Susan J.; School of Nursing
    Introduction: Heart failure (HF) is a prevalent, serious chronic illness that affects 6.5 million adults in the United States. Among patients with HF, the prevalence of attention impairment is reported to range from 15% to 27%. Although attention is fundamental to human activities including HF self-care, cognitive interventions for patients with HF that target improvement in attention are scarce. The COgnitive intervention to Restore attention using nature Environment (CORE) study aims to test the preliminary efficacy of the newly developed Nature-VR, a virtual reality-based cognitive intervention that is based on the restorative effects of nature. Nature-VR development was guided by Attention Restoration Theory. The target outcomes are attention, HF self-care, and health-related quality of life (HRQoL). Our exploratory aims examine the associations between attention and several putative/established HF biomarkers (eg, oxygen saturation, brain-derived neurotrophic factor, apolipoprotein E, dopamine receptor, and dopamine transporter genes) as well as the effect of Nature-VR on cognitive performance in other domains (ie, global cognition, memory, visuospatial, executive function, and language), cardiac and neurological events, and mortality. Methods: This single-blinded, two-group randomized-controlled pilot study will enroll 74 participants with HF. The Nature-VR intervention group will view three-dimensional nature pictures using a virtual reality headset for 10 minutes per day, 5 days per week for 4 weeks (a total of 200 minutes). The active comparison group, Urban-VR, will view three-dimensional urban pictures using a virtual reality headset to match the Nature-VR intervention in intervention dose and delivery mode, but not in content. After baseline interviews, four follow-up interviews will be conducted to assess sustained effects of Nature-VR at 4, 8, 26, and 52 weeks. Discussion: The importance and novelty of this study consists of using a first-of-its kind, immersive virtual reality technology to target attention and in investigating the health outcomes of the Nature-VR cognitive intervention among patients with HF.