Publication

Since the outbreak of COVID-19, the spread of infectious respiratory infectious diseases has caused serious damage not only in medical care but also in politics, society, and economy. In the diagnosis and treatment of respiratory infectious diseases, the introduction of a new concept of medical systems and medical services is required to replace existing diagnostic and treatment methods to prevent exposure and infection by medical staff. As the infection of COVID-19 spreads and continues, the need for the development of various non-face-to face diagnostic and therapeutic robots has emerged in hospitals.
In particular, it was very urgent to develop a robot that performs diagnosis and treatment non-face-to-face for patients visiting otolaryngology for respiratory-related diseases. This study aims at an interdisciplinary convergence study with the theme of a UX design-based artificial intelligence healthcare robot system for non-face-to-face diagnosis and treatment, and a robot system is currently under development. Although it is not in the stage of commercializing the robot system, non-face-to face treatment and treatment will be needed in the diagnosis and treatment process of patients and doctors visiting otolaryngology, which is highly feared to be infected. This non face-to-face diagnosis and treatment process can provide safe, efficient, and accurate diagnosis and treatment for patients, and we would like to present a study of digital twins as a UX-based robotic system for this purpose.