On Providing Multi-Level Quality of Service for Operating Rooms of the Future.
Vinicius F RodriguesRodrigo da Rosa RighiCristiano André da CostaBjoern M EskofierAndreas K MaierPublished in: Sensors (Basel, Switzerland) (2019)
The Operating Room (OR) plays an important role in delivering vital medical services to patients in hospitals. Such environments contain several medical devices, equipment, and systems producing valuable information which might be combined for biomedical and surgical workflow analysis. Considering the sensibility of data from sensors in the OR, independently of processing and network loads, the middleware that provides data from these sensors have to respect applications quality of service (QoS) demands. In an OR middleware, there are two main bottlenecks that might suffer QoS problems and, consequently, impact directly in user experience: (i) simultaneous user applications connecting the middleware; and (ii) a high number of sensors generating information from the environment. Currently, many middlewares that support QoS have been proposed by many fields; however, to the best of our knowledge, there is no research on this topic or the OR environment. OR environments are characterized by being crowded by persons and equipment, some of them of specific use in such environments, as mobile x-ray machines. Therefore, this article proposes QualiCare, an adaptable middleware model to provide multi-level QoS, improve user experience, and increase hardware utilization to middlewares in OR environments. Our main contributions are a middleware model and an orchestration engine in charge of changing the middleware behavior to guarantee performance. Results demonstrate that adapting middleware parameters on demand reduces network usage and improves resource consumption maintaining data provisioning.
Keyphrases
- healthcare
- mental health
- electronic health record
- end stage renal disease
- big data
- low cost
- ejection fraction
- chronic kidney disease
- primary care
- newly diagnosed
- high resolution
- computed tomography
- artificial intelligence
- magnetic resonance imaging
- data analysis
- deep learning
- machine learning
- peritoneal dialysis
- health insurance
- electron microscopy
- patient reported