Wearable smart blanket system model for monitoring the vital signs of patients in ambulance
Researcher Bulletin of Medical Sciences,
Vol. 24 No. 1 (2019),
31 August 2020
Introduction: The timely and managed intervention reduces the consequences of disease and sudden death among the patients in emergency conditions. Monitoring the patients in emergency conditions requires rapid and appropriate decisions to save their lives. The present study aimed at modeling the wearable smart blanket system for monitoring the patients in the emergency conditions of ambulance.
Materials and Methods: The present study was based on an applied and descriptive-developmental design. Firstly, the requirements and features of wearable smart blanket system were elicited and secondly a smart blanket system was modeled by using the UML charts and elicited requirements. Finally, the designed architecture was evaluated using ARID scenario-based method.
Results: The functional requirements of wearable smart blanket system with its data elements and physical-structural features of this system as well as non-functional requirements were elicited. Based on the requirements and data elements elicited from the questionnaire, class diagram, activity, use-case diagram, sequence, deployment, and component were drawn. Then, using the UML and the relationships between components, systems, and users from the structural and behavioral perspectives used the ARID scenario-based evaluation method to indicate that the designed architecture could provide the expected scenarios from the proposed system.
Conclusion: Wearable smart blanket system collects the data related to medical signals by the sensors installed on the blanket and such data are processed by the smart system. Therefore, it can be concluded that the design of this system makes it possible to monitor and control patients in risky conditions with better quality and to integrate vital signs. The analyzing biological data makes it easy for doctors to take early diagnosis and interventions
- Wearable technology; Physiological parameters monitoring; Modeling; Smart systems
How to Cite
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