RESUMO
The current crisis surrounding the COVID-19 pandemic demonstrates the amount of responsibility and the workload on our healthcare system and, above all, on the medical staff around the world. In this work, we propose a promising approach to overcome this problem using robot-assisted telediagnostics, which allows medical experts to examine patients from distance. The designed telediagnostic system consists of two robotic arms. Each robot is located at the doctor and patient sites. Such a system enables the doctor to have a direct conversation via telepresence and to examine patients through robot-assisted inspection (guided tactile and audiovisual contact). The proposed bilateral teleoperation system is redundant in terms of teleoperation control algorithms and visual feedback. Specifically, we implemented two main control modes: joint-based and displacement-based teleoperation. The joint-based mode was implemented due to its high transparency and ease of mapping between Leader and Follower whereas the displacement-based is highly flexible in terms of relative pose mapping and null-space control. Tracking tests between Leader and Follower were conducted on our system using both wired and wireless connections. Moreover, our system was tested by seven medical doctors in two experiments. User studies demonstrated the system's usability and it was successfully validated by the medical experts.
RESUMO
OBJECTIVES: This paper provides an overview of existing applications and concepts of robotic systems and artificial intelligence in dentistry. This review aims to provide the community with novel inputs and argues for an increased utilization of these recent technological developments, referred to as Dentronics, in order to advance dentistry. METHODS: First, background on developments in robotics, artificial intelligence (AI) and machine learning (ML) are reviewed that may enable novel assistive applications in dentistry (Sec A). Second, a systematic technology review that evaluates existing state-of-the-art applications in AI, ML and robotics in the context of dentistry is presented (Sec B). RESULTS: A systematic literature research in pubmed yielded in a total of 558 results. 41 studies related to ML, 53 studies related to AI and 49 original research papers on robotics application in dentistry were included. ML and AI have been applied in dental research to analyze large amounts of data to eventually support dental decision making, diagnosis, prognosis and treatment planning with the help of data-driven analysis algorithms based on machine learning. So far, only few robotic applications have made it to reality, mostly restricted to pilot use cases. SIGNIFICANCE: The authors believe that dentistry can greatly benefit from the current rise of digital human-centered automation and be transformed towards a new robotic, ML and AI-enabled era. In the future, Dentronics will enhance reliability, reproducibility, accuracy and efficiency in dentistry through the democratized use of modern dental technologies, such as medical robot systems and specialized artificial intelligence. Dentronics will increase our understanding of disease pathogenesis, improve risk-assessment-strategies, diagnosis, disease prediction and finally lead to better treatment outcomes.