A Fuzzy Inference System for the Assessment of Indoor Air Quality in an Operating Room to Prevent Surgical Site Infection
Bibliographic Data
| ID | 15489761 |
|---|---|
| Authors | Ylenia Colella (University of Naples Federico II), Antonio Saverio Valente (0000-0002-4544-2166, University of Naples Federico II), Lucia Rossano (University of Naples Federico II), Teresa Angela Trunfio (0000-0003-0929-567X, Federico II University Hospital, corresponding author), Antonella Fiorillo (0000-0002-6289-6602, Federico II University Hospital), Giovanni Improta (0000-0002-9485-1687, University of Naples Federico II) |
| Year | 2022 |
| Volume | 19 |
| Issue | 6 |
| Pages | 3533-3533 |
| Publication date | 2022-03-16 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph19063533 |
| PMID | 35329215 |
| OpenAlex | W4221049689 |
| Language | EN |
| Citations received | 2 |
| References cited | 37 |
Indoor air quality in hospital operating rooms is of great concern for the prevention of surgical site infections (SSI). A wide range of relevant medical and engineering literature has shown that the reduction in air contamination can be achieved by introducing a more efficient set of controls of HVAC systems and exploiting alarms and monitoring systems that allow having a clear report of the internal air status level. In this paper, an operating room air quality monitoring system based on a fuzzy decision support system has been proposed in order to help hospital staff responsible to guarantee a safe environment. The goal of the work is to reduce the airborne contamination in order to optimize the surgical environment, thus preventing the occurrence of SSI and reducing the related mortality rate. The advantage of FIS is that the evaluation of the air quality is based on easy-to-find input data established on the best combination of parameters and level of alert. Compared to other literature works, the proposed approach based on the FIS has been designed to take into account also the movement of clinicians in the operating room in order to monitor unauthorized paths. The test of the proposed strategy has been executed by exploiting data collected by ad-hoc sensors placed inside a real operating block during the experimental activities of the "Bacterial Infections Post Surgery" Project (BIPS). Results show that the system is capable to return risk values with extreme precision
Air conditioning · Air quality index · HVAC · Indoor air quality · Quality (philosophy · Reliability engineering · Computer Science · Engineering · Environmental Science · Intensive Care Unit Cognitive Disorders · Non-Invasive Vital Sign Monitoring · Respiratory Support and Mechanisms · Environmental Engineering
| Unique citing works | 2 |
|---|---|
| Citations per year | 0.5 |
| Citation span | 2022 - 2022 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |