Analysis of Robotic Health Care Assisted Surgical Device Doctors, Hospitals and Engineers

Abstract

The combination of eye tracking and brain-computer interfaces (BCI), especially using electroencephalography (EEG), has been highly promising in neurological studies, disease diagnosis, and human-computer interaction. This review discusses the combined uses of eye tracking and EEG, their application in emotion recognition, cognitive analysis, and medical diagnostics. This research also investigates technological innovations in healthcare robotics, AI-based diagnostics, and surgical automation. The design and experimental verification of 3D-printed ergonomic surgical mask straps are discussed, highlighting the possibilities of personalized medical solutions. In addition, AI-based keratoconus detection from corneal topography imaging is examined, highlighting its significance in mitigating medical risk and expenses. A new predict-then-optimize framework is also introduced to improve hospital admission scheduling, optimizing patient care effectiveness. The study also explores robotic use in surgery, including flexible surgical tools, robotic gloves for tetraplegic individuals, and AI-based motion constraint control in surgery. Lastly, the progress in medical service robots, hospital logistics, and orthopedic surgical robotics is discussed, highlighting the increasing contribution of automation to contemporary healthcare. The results indicate that the combination of AI, robotics, and intelligent medical devices has the potential to greatly enhance diagnostic accuracy, patient care, and hospital resource utilization, leading to future innovation in precision medicine.

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