An Effective Deep Learning Model to Discriminate Coronavirus Disease From Typical Pneumonia

Current technological advances are paving the way for technologies based on deep learning to be utilized in the majority of life fields. The effectiveness of these technologies has led them to be utilized in the medical field to classify and detect different diseases. Recently, the pandemic of coronavirus disease (COVID-19) has imposed considerable press on the health infrastructures all over the world. The reliable and early diagnosis of COVID-19-infected patients is crucial to limit and prevent its outbreak. COVID-19 diagnosis is feasible by utilizing reverse transcript-polymerase chain reaction testing;however, diagnosis utilizing chest x-ray radiography is deemed safe, reliable, and precise in various cases. © 2022 IGI Global. All rights reserved.

Towards a Social VR-based Exergame for Elderly Users: An Exploratory Study of Acceptance, Experiences and Design Principles

For many elderly individuals, the aging experience is associated with a lack of social interaction and physical exercise that may negatively affect their health. To address these issues, researchers have designed experiences based on immersive virtual reality (VR) and 2D screen-based exergames. However, very few have studied the use of social VR for elderly, in which users can interact remotely through avatars in a single, shared, immersive virtual environment, using a head-mounted display. Additionally, there is limited research on the experience of elderly in performing interactive activities, especially game-based activities, in social VR. We conducted an exploratory study with 10 elderly people who never experienced VR before, to evaluate an avatar-mediated interaction-based social VR game prototype. Based on a mixed-methods approach, our study presents new insights into the usability, acceptance, and gameplay experience of elderly in a social VR game. Moreover, our study reflects upon design principles that should be considered when developing social VR games for elderly to ensure an engaging and safe user experience. Our results suggest that such games have a potential among the user group. Direct hand manipulation, based on hand tracking for interaction with 3D objects, presented an engaging and intuitive interaction paradigm, and the social game activity in VR was found to be enjoyable. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

AI and Robotics in the Fight Against COVID-19 Pandemic

The outbreak of the novel coronavirus and its disease COVID-19 present an unprecedented challenge for humanity. Artificial Intelligence (AI) and robotics may help fighting COVID-19. Potential applications of AI in this accelerating pandemic include, but are not limited to, early detection and diagnosis, massive agent modeling and simulation, data analytics, assistive robots, disinfection robots, public awareness and patrolling, contactless delivery services, virtual healthcare assistants, drug repurposing and vaccination discovery. This chapter sheds light on the roles AI and robotics can play in fighting this disastrous pandemic, and possible future ones, and highlights several potential applications to transform this challenge into opportunities. This chapter also discusses the ethical implications of AI and robotics during the pandemic and in the post-pandemic world. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Disease diagnosis system using IoT empowered with fuzzy inference system

Disease diagnosis is a challenging task due to a large number of associated factors. Uncertainty in the diagnosis process arises from inaccuracy in patient attributes, missing data, and limitation in the medical expert’s ability to define cause and effect relationships when there are multiple interrelated variables. This paper aims to demonstrate an integrated view of deploying smart disease diagnosis using the Internet of Things (IoT) empowered by the fuzzy inference system (FIS) to diagnose various diseases. The Fuzzy System is one of the best systems to diagnose medical conditions because every disease diagnosis involves many uncertainties, and fuzzy logic is the best way to handle uncertainties. Our proposed system differentiates new cases provided symptoms of the disease. Generally, it becomes a time-sensitive task to discriminate symptomatic diseases. The proposed system can track symptoms firmly to diagnose diseases through IoT and FIS smartly and efficiently. Different coefficients have been employed to predict and compute the identified disease’s severity for each sign of disease. This study aims to differentiate and diagnose COVID-19, Typhoid, Malaria, and Pneumonia. This study used the FIS method to figure out the disease over the use of given data related to correlating with input symptoms. MATLAB tool is utilised for the implementation of FIS. Fuzzy procedure on the aforementioned given data presents that affectionate disease can derive from the symptoms. The results of our proposed method proved that FIS could be utilised for the diagnosis of other diseases. This study may assist doctors, patients, medical practitioners, and other healthcare professionals in early diagnosis and better treat diseases. © 2022 Tech Science Press. All rights reserved.

Robotics and intelligent systems against a pandemic

The outbreak of the novel coronavirus and its disease COVID-19 presents an unprecedented challenge for humanity. Intelligent systems and robotics particularly are helping the fight against COVID-19 several ways. Potential technology-driven solutions in this accelerating pandemic include, but are not limited to, early detection and diagnosis, assistive robots, indoor and outdoor disinfection robots, public awareness and patrolling, contactless last-mile delivery services, micro-and nano-robotics and laboratory automation. This article sheds light on the roles robotics and automation can play in fighting this disastrous pandemic and highlights a number of potential applications to transform this challenge into opportunities. The article also highlights the ethical implications of robotics and intelligent systems during the emergency side and in the post-pandemic world. © 2021, Budapest Tech Polytechnical Institution. All rights reserved.

Multi-Agent System Based Mobile Help Desk and Monitoring of Safety Measures to Combat COVID-19 and Future Pandemics

The outbreak of COVID-19 pandemic presents an unprecedented challenge for humanity. The historical data about the past pandemics indicates towards a high possibility of future pandemics. Moreover, current pandemic is expected to stay for longer time. In this situation, social robots hold a huge potential to assist in fighting against current and future pandemics by minimizing human-to-human interactions e.g., by providing digital help desk, and monitoring the compliance of people with required safety measures at public places. A huge number of robots are required to monitor large spaces like shopping malls, airports etc. Therefore, we present Multi-Agent System (MAS) to provide robot based mobile help desk and monitoring safety measure of wearing face mask, for large spaces in an efficient and cost-effective manner. Our proposed MAS is based on collaborative work of two agents: 1) CCTV Camera, and 2) Robot. Experimental results show efficiency and effectiveness of proposed MAS in navigation and control of robot based on visual information interpreted by CCTV camera to provide mobile help desk, and detecting face masks through robot by using state-of-the-art real-time computer vision algorithms in large spaces. © 2021 IEEE.