Fuzzy Logic-Based Health Monitoring System for COVID’19 Patients
| Autor: | Lalit Garg, Ali Kashif Bashir, Kathiravan Srinivasan, K. Ramesh, K. Maharajan, M. Jayalakshmi, K. Jayakumar |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Reasoning system business.industry Computer science Fuzzy set Inference Context (language use) 02 engineering and technology Semantic reasoner Fuzzy logic Computer Science Applications Biomaterials Identification (information) 020901 industrial engineering & automation Risk analysis (engineering) Mechanics of Materials Modeling and Simulation Health care 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Electrical and Electronic Engineering business |
| Zdroj: | Computers, Materials & Continua. 67:2431-2447 |
| ISSN: | 1546-2226 |
| DOI: | 10.32604/cmc.2021.015352 |
| Popis: | In several countries, the ageing population contour focuses on high healthcare costs and overloaded health care environments. Pervasive health care monitoring system can be a potential alternative, especially in the COVID-19 pandemic situation to help mitigate such problems by encouraging healthcare to transition from hospital-centred services to self-care, mobile care and home care. In this aspect, we propose a pervasive system to monitor the COVID’19 patient’s conditions within the hospital and outside by monitoring their medical and psychological situation. It facilitates better healthcare assistance, especially for COVID’19 patients and quarantined people. It identifies the patient’s medical and psychological condition based on the current context and activities using a fuzzy context-aware reasoning engine based model. Fuzzy reasoning engine makes decisions using linguistic rules based on inference mechanisms that support the patient condition identification. Linguistics rules are framed based on the fuzzy set attributes belong to different context types. The fuzzy semantic rules are used to identify the relationship among the attributes, and the reasoning engine is used to ensure precise real-time context interpretation and current evaluation of the situation. Outcomes are measured using a fuzzy logic-based context reasoning system under simulation. The results indicate the usefulness of monitoring the COVID’19 patients based on the current context. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|