HealthStack: Providing an IoT Middleware for Malleable QoS Service Stacking for Hospital 4.0 Operating Rooms

• Published in: IEEE internet of things journal Vol. 9; no. 19; pp. 18406 - 18430
• Main Authors: Rodrigues, Vinicius F., Righi, Rodrigo R., Costa, Cristiano A., Antunes, Rodolfo S., Bazo, Rodrigo, Reis, Eduardo S., Seewald, Lucas A., Junior, Luis G. S., Eskofier, Bjorn M.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biomedical monitoring; Consumption; Data analysis; Data transmission; Distributed systems; Health care; healthcare; Internet of Things (IoT); Middleware; Monitoring; Quality of service; Real time; Real-time systems; Sensors; Surgery; Ultrawideband; Vibration; Workflow
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2022.3160633

Healthcare 4.0 is a new concept that originates from the evolution of hospitals due to technological advances in medical activities. Nowadays, more and more doctors and healthcare administrators require real-time data analysis obtained from sensors and surgery monitoring. Using real-time information could make the difference between death and life in such settings. Therefore, Quality of Service (QoS) is essential in this context because, without it, the results of the applications become unreliable. Given the background, this article proposes HealthStack, a sensor middleware model for operating room facilities. HealthStack aims at improving delay and jitter from applications and, at the same time, reducing resource consumption. Our scientific contributions are twofold: 1) a middleware for operating rooms with automatic QoS support for real-time data transmission and 2) a QoS strategy based on artificial neurons to select middleware components with critical performance. We developed a prototype that uses depth cameras and ultrawideband (UWB) real-time location systems (RTLSs) to monitor workflow during surgery. The evaluation demonstrates that the strategy improves the average jitter experienced by application by 92.3%. The results also reveal a reduction of network and CPU consumption by up to 61.8% and 8.3%.