Concepts for the use of assistive robots and artificial intelligence in a nuclear medicine facility
Tomasz Winiarski, Daniel Giełdowski, Konrad Giełdowski, Monika Tulik, Małgorzata Kobylecka, Jolanta Kunikowska
- Year
- 2025
- Citations
- 1
- Access
- Open access
Abstract
Abstract Purpose Nuclear medicine is an evolving multidisciplinary branch of medicine that presents challenges for patients and staff, because of radiation exposure. This problem is not easy to address, yet the solution could be the inclusion of the newest technological advances, such as assistive robots. These resilient machines employ artificial intelligence and sets of sensors to interact with the world, which enables them to perform dangerous jobs and tedious tasks without fatigue. This article briefly presents the state of assistive robots in medicine and proposes possibilities for their utilisation within a nuclear medicine facility using Rico, a robotic mobile platform. Methods We included references to autonomous and semi-autonomous assistive robots in a hospital environment, with particular emphasis on nuclear medicine departments searched in PubMed database. The articles referencing the TIAGo robotic platform were also included, as it serves as a base for Rico. Results We present a short review of assistive robots utilisation within medicinal environments and an overview of previous employments of TIAGo. Furthermore, we propose possibilities for the usage of it within the nuclear medicine department. The potential use cases are discussed in detail to pinpoint the most critical tasks and identify their associated challenges. We validate one of these tasks (object transportation) using Rico. Conclusions The utilisation of assistive robots in nuclear medicine requires further research, as there are many yet unexplored possibilities. An increase in the usage of robotic platforms would allow to reduce employees’ radiation exposure and help alleviate problems with staff shortage, thus presenting the need for additional experiments.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991