Rebecca Diekmann

Carl von Ossietzky Universität Oldenburg

Papers

Total Citations

H-Index

About

Rebecca Diekmann is a pioneering researcher at the intersection of healthcare robotics and patient simulation, whose work addresses critical challenges in nursing and medical education. Her primary research areas include collaborative robotics for physical relief in healthcare, android robot-patient systems for clinical training, and human-robot interaction in medical settings. Diekmann's most impactful contribution is her 2022 study on "Providing physical relief for nurses by collaborative robotics" (25 citations), which demonstrated how robotic systems can be individually adapted to reduce the musculoskeletal burden from manual patient handling—a pressing issue affecting healthcare workers worldwide. She has also pioneered the use of android robot-patients for medical training, developing innovative simulation scenarios for teaching the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and communication training for relatives of non-verbal patients. Her 2023 pilot study on android robot-patients for delirium assessment training, though early-stage, represents a novel approach to addressing the complexity of medical education. Diekmann's work on observation-driven android robots with individualized communication skills further showcases her commitment to creating adaptive, patient-centered training tools. Her research holds significant promise for improving both healthcare worker safety and patient care quality through technological innovation.