This work proposes to adapt an existing sensor and embed it on mannequins used in cardiopulmonary resuscitation (CPR) training to accurately measure the amount of air supplied to the lungs during ventilation. The proposed sensor consists of measuring the airflow using propellers. The method directly measures the variable of interest and makes reference to spirometric techniques in the elaboration of its model, improving the realism of the dummies. Besides advantages over the sensors that are commonly used for this purpose, the projected sensor presented an agreement with its theoretical model and with the spirometric model. It is suitable for applications with a resolution of 17 mL, and precision of 50 mL and 26 mL for initial (< 900 mL) and final ranges, respectively.
This work proposes adapting an existing sensor and embedding it on mannequins used in cardiopulmonary resuscitation (CPR) training to accurately measure the amount of air supplied to the lungs during ventilation. Mathematical modeling, calibration, and validation of the sensor along with metrology, statistical inference, and spirometry techniques were used as a base for aquiring scientific knowledge of the system. The system directly measures the variable of interest (air volume) and refers to spirometric techniques in the elaboration of its model. This improves the realism of the dummies during the CPR training, because it estimates, in real-time, not only the volume of air entering in the lungs but also the Forced Vital Capacity (FVC), Forced Expiratory Volume (FEVt) and Medium Forced Expiratory Flow (FEF20–75%). The validation of the sensor achieved results that address the requirements for this application, that is, the error below 3.4% of full scale. During the spirometric tests, the system presented the measurement results of (305 ± 22, 450 ± 23, 603 ± 24, 751 ± 26, 922 ± 27, 1021 ± 30, 1182 ± 33, 1326 ± 36, 1476 ± 37, 1618 ± 45 and 1786 ± 56) × 10−6 m3 for reference values of (300, 450, 600, 750, 900, 1050, 1200, 1350, 1500, 1650 and 1800) × 10−6 m3, respectively. Therefore, considering the spirometry and pressure boundary conditions of the manikin lungs, the system achieves the objective of simulating valid spirometric data for debriefings, that is, there is an agreement between the measurement results when compared to the signal generated by a commercial spirometer (Koko brand). The main advantages that this work presents in relation to the sensors commonly used for this purpose are: (i) the reduced cost, which makes it possible, for the first time, to use a respiratory volume sensor in medical simulators or training dummies; (ii) the direct measurement of air entering the lung using a noninvasive method, which makes it possible to use spirometry parameters to characterize simulated human respiration during the CPR training; and (iii) the measurement of spirometric parameters (FVC, FEVt, and FEF20–75%), in real-time, during the CPR training, to achieve optimal ventilation performance. Therefore, the system developed in this work addresses the minimum requirements for the practice of ventilation in the CPR maneuvers and has great potential in several future applications.
The most common practice related to medical urgency and emergency is Cardiopulmonary Resuscitation (CPR). There were no CPR practices in the training of health professionals until the appearance of realistic mannequins intended for this purpose. Then, the automation of this equipment allowed the continuous improvement of the quality of the maneuvers through real-time feedback. This work implements a Soft-Real-Time in order to present the actions performed on the dummy in a sufficient time interval to perform and correct the maneuver simultaneously. The Arduino platform composes the embedded system and is used together with the Resusci Anne® mannequin. The embedded system is based on the Arduino platform, which encodes the actions performed on the Resusci Anne® mannequin through a Real-Time Scheduling and Multitasking (ARTE). Visual Studio is used to develop the supervisory system, based on CPR teaching methodology, which decodes and present the embedded system information. It was possible to allocate the real-time resources taking into account the requirements of the instrumentation, the embedded system, and the real-time scheduling and multitasking to execute the proposed deadline for the application. In this way, it was possible to make the system achieve real-time requirements and provide feedback to the target audience of this work. The automation of simulators, as presented in this work, brings continuous improvement in the training and training of health professionals, making them able to perform effective maneuvers during CPR. Resumo: A prática mais comum relacionada a urgência e emergência médicas é a Ressuscitação Cardiopulmonar (RCP). Práticas de RCP não foram realizadas na formação de profissionais da área de saúde até o surgimento de manequins realísticos destinados a essa finalidade. Em seguida, a automação desses equipamentos permitiu a melhoria contínua da qualidade das manobras por meio de feedback em tempo real. Neste trabalho, implementa-se um sistema de tempo real de forma que as ações praticadas no manequim são apresentadas em um intervalo de tempo com duração suficiente para realizar e corrigir a manobra simultaneamente. O sistema embarcado foi baseado na plataforma Arduino, que codifica as ações realizadas no manequim Ressusci Anne® por meio de um Escalonador de Tempo Real e Multitarefa (ARTE). O Visual Studio é utilizado para desenvolver um supervisório baseado em metodologia de ensino da RCP, que decodifica e apresenta as informações do sistema embarcado. Foi possível alocar os recursos de tempo real levando-se em consideração as exigências da instrumentação, do sistema embarcado e do escalonador de tempo real e multitarefa para executar o deadline proposto para a aplicação. Desta forma, foi possível fazer com que o sistema atenda aos requisitos de tempo real e forneça feedback ao público-alvo deste trabalho. A automação de simuladores, da forma como apresentado neste trabalho, pode proporcionar melhoria contínua na formação e treinamento dos profissionais da área de saúde, tornando-os mai...
The family of crystals known as Tutton's salts plays a significant role in physics and chemistry; because they are used in phase transition studies and to define models applied to materials. The importance of salts in material engineering is recent, as in applications in adiabatic degaussing refrigerators and solid-state anodes. Studies of the (NH 4 ) 2 Ni(SO 4 ) 2 •6H 2 O and (NH 4 ) 2 Co(SO 4 ) 2 •6H 2 O are widely found in literature but do not occur for the mixture of both. In this research, we studied mixed crystals of the general chemical formula (NH 4 ) 2 Ni x Co (1-x) (SO 4 ) 2 •6H 2 O with x ranging from 0 to 1, utilizing x = 0.7. The objective is to study the modifications caused owing to the ion's weighted composition in the formation of the solid solution and compare it with the pure salts. For this, the growth of these crystals is discussed based on ICP-OES results and optical microscopy concerning the crystal growth theory. The discussion also relates the Raman spectra of the salts with molecular changes according to structured group theory, qualitatively characterizing its crystalline structure. Finally, a Single-crystal X-ray study solves and confirms the structure of pure salts and mixed salt, quantitatively characterizing their crystal structure.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.