Abstract Introduction According to the World Health Organization, about 9.2% of the 28 million newborns worldwide are stillborn. Besides, about 358,000 women died due to complications related to pregnancy in 2015. Part of these deaths could have been avoided with improving prenatal care agility to recognize problems during pregnancy. Based on that, many efforts have been made to provide technologies that can contribute to offer better access to information and assist in decision-making. In this context, this work presents an architecture to automate the classification and referral process of pregnant women between the basic health units and the referral hospital through a Telehealth platform. Methods The Telehealth architecture was developed in three components: The data acquisition component, responsible for collecting and inserting data; the data processing component, which is the core of the architecture implemented using expert systems to classify gestational risk; and the post-processing component, in charge of the delivery and analysis of cases. Results Acceptance test, system accuracy test based on rules and performance test were realized. For the tests, 1,380 referral forms of real situations were used. Conclusion On the results obtained with the analysis of real data, ILITIA, the developed architecture has met the requirements to assist medical specialists on gestational risk classification, which decreases the inconvenience of pregnant women displacement and the resulting costs.

INTRODUCTION: Patient monitoring will tend to decline in the coming years due to a shortage of physical and human resources in hospitals. Therefore, several studies define alternatives to improve patient monitoring using wireless networks. In these studies, a wireless network is used to transfer data generated by medical sensors without interacting with the traffic in the data network of the hospital. However, this approach should be avoided because there are demands for integration between user applications and patient monitoring. Therefore, this paper defines a patient monitoring system, called Wi-Bio, directed to the establishment of IEEE 802.11 networks that allows traffic generated by user applications. METHODS: The formal validation of Wi-Bio was made through the design of Petri nets, and performance analysis was performed through simulations of the Network Simulator 2 tool. The adoption of this approach is justified by the fact that Petri nets allow verification of logical correctness of the designed systems, while simulations allow behavioral analysis of Wi-Bio in overload scenarios where many patients are monitored. RESULTS: The results confirmed the validity of the designed Petri nets and showed that Wi-Bio is able to accomplish the temporal goals imposed by medical sensors, thereby promoting efficient integration of traffic present in the data network and the patient monitoring network. CONCLUSION: As described, Wi-Bio fulfilled its objectives and motivates future studies aimed at complementing the obtained results.

Uma identificação correta de transientes em sinais de ECG (Eletrocardiograma) pode auxiliar métodos de processamento de sinal de ECG, pois esse tipo de evento degrada o sinal e pode induzir a erros. Diante disso, o presente trabalho propõe uma arquitetura para a detecção desses fenômenos, seguindo a tendência atual da computação distribuída, na qual um sensor realiza a detecção dos transientes no momento da aquisição do sinal, e, em seguida, encaminha essa informação através de uma rede de comunicação de dados, desenvolvida especialmente para a automação hospitalar, até um dispositivo computacional que irá processar os dados ou então apresentá-los a um profissional capacitado para fazer a análise de forma manual. Para realizar a detecção de transientes, foi proposto um método matemático baseado na transformada Hilbert do sinal de ECG, aliado ao PM-AH (Protocolo Multiciclos para Automação Hospitalar), com adição de quadros neste, para que seja possível o envio da informação sobre a ocorrência de transientes junto aos dados do sinal de eletrocardiograma. Dentre os transientes possíveis, foi escolhido o ruído, por ser o fenômeno que mais interfere no processamento de sinais de ECG, onde testes foram realizados com a base de dados MIT-BIH Arrhythmia Database, enquanto uma análise matemática foi feita nos novos quadros do protocolo PM-AH, com o intuito de demonstrar a consistência do protocolo com esta adição.

A correct identification of transients in the ECG (electrocardiogram) can assist processing methods for ECG signals, since this type of event degrades the signal and can be misleading. Therefore, this paper proposes an architecture for detection of these phenomena, following the current trend of distributed computing, in which a sensor will detect transients at the time of signal acquisition, and then forward this information through a data communication network, designed specifically for hospital automation, to a computing device that will process the data or present it to a trained professional for manual analysis. To perform the detection of transients, a mathematical method based on the Hilbert transform of the ECG signal is proposed here, allied with the MP-HA (Multicycle Protocol for Hospital Automation), with the addition of frames, so that information on the occurrence of transients can be transmitted along with signal data of the electrocardiogram. Among the possible transients, noise was chosen because it is the phenomenon that interferes the most with the processing of ECG signals. Tests were performed using the MIT-BIH Arrhythmia Database, while a mathematical analysis was used in the new frames of the MP-HA protocol in order to demonstrate the consistency of the protocol with this addition.

O aumento nas demandas por gerenciamento, controle e monitoramento das informações na área da automação hospitalar tem promovido um maior volume de pesquisas que são indutoras do processo de inovação tecnológica na área da saúde. Neste contexto, um aspecto considerado importante na automatização do monitoramento de pacientes consiste na eficiência em detectar e informar em tempo hábil as anomalias encontradas nos sinais vitais dos pacientes. O procedimento de notificar as ocorrências dessas anomalias à equipe médica pode ser implementado por meio da geração e envio de alertas (sonoros ou visuais). Verificando a relevância desse tipo de demanda no ambiente hospitalar, o presente artigo descreve uma arquitetura que tem como fundamento a geração e o envio de alertas, cujos dados são advindos de pacientes internados em Unidades de Terapia Intensiva (UTI). A premissa foi, portanto, otimizar o processo de comunicação das anomalias detectadas de modo que a equipe médica responsável seja notificada de tais eventos de maneira mais eficiente. A arquitetura de comunicação, definida para o ambiente hospitalar, baseou-se em estudos realizados na UTI do Hospital Universitário Onofre Lopes (HUOL). Tais estudos possibilitaram uma análise de requisitos que permitiu definir um gerador de alertas personalizados, e o envio desses para dispositivos móveis das equipes médicas. O processo de envio dos alertas foi baseado em um algoritmo de escalonamento de tempo real, fazendo uso de um middleware e de computação móvel e distribuída, sendo esses os aspectos inovadores dessa arquitetura.

The increase in demand for the management, control and monitoring of information in hospitals has promoted a greater volume of research that induces the process of technological innovation in healthcare. In this context, an important aspect to consider in the automation of patient monitoring is the efficiency to detect and report anomalies in patients' vital signs in a timely manner. The procedure for notifying the medical staff of these anomalies can be implemented by generating and sending alerts (either audible or visual). Noting the relevance of this demand in the hospital environment, this paper describes an architecture based on the generation and transmission of alerts, whose data are coming from patients hospitalized in intensive care units (ICU). The premise was therefore to optimize the procedure for reporting deficiencies so that the medical staff in charge is notified of such events more efficiently. The communication architecture in hospitals, used in this paper, was based on studies conducted at the ICU of the University Hospital Onofre Lopes (HUOL). These studies allowed an analysis of requirements that lead to the definition of a generator of custom alerts, and the sending of these alerts to mobile devices kept by medical staff. The process of sending those alerts was based on a real time scheduling algorithm making use of a middleware and both mobile and distributed computing, which are the innovative aspects of this architecture.