Deep learning-based monitoring technique for real-time intravenous medication bag status.

ABSTRACT: Accidents related to the administration of intravenous (IV) medication, such as drug overdose/underdose, drug/patient mis-identification, and delayed bag exchange, occur consistently in clinical fields. Several previous studies have suggested various contact-sensing and image-processing methodologies; however, most of them can increase the workload of nursing staffs during the long-term, continuous monitoring. In this study, we proposed a smart IV pole that can monitor the infusion status of up to four IV medications (patient/drug identification, and liquid residue) with various sizes and hanging positions to reduce IV-related accidents and improve patient safety with the least additional workload; the system consists of 12 cameras, one code scanner, and four controllers. Two types of deep

SUBMITTER: Hwang YJ 

PROVIDER: S-EPMC10245361 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature