Qu’il s’agisse de suivre des patients à domicile, ou de prévenir l’isolement ou la vulnérabilité de personnes âgées, les systèmes de suivi et d'assistance électroniques qui émergent offrent des opportunités sans précédents. L’enjeu est considérable, et on assiste à un développement technologique important qui permet désormais aux particuliers ou aux établissements hospitaliers ou médico-sociaux d’assurer le diagnostic, la prévention, le contrôle, voire le traitement de patients à distance (mesures de paramètres physiologiques, administration de médicaments, détection de chutes, etc.). Ce suivi à distance est en particulier devenu possible et performant avec l’avènement des objets connectés. On peut ainsi envisager d’exploiter un réseau de capteurs embarqué sur un patient pour mesurer à distance et en temps réel la température, le rythme cardiaque ou la tension artérielle d’un patient. Les données sont transmises (et/ou stockées) au praticien pour réaliser le diagnostic et définir les traitements. Pour autant la conception optimale (choix des technologies de transmission, de stockage, etc.) ainsi que la problématique de la gestion d’énergie constituent des verrous à leur adoption. Le travail proposé dans cette thèse consiste donc à développer un outil d’aide à la conception de réseaux de capteurs médicaux communicants embarqués sur la personne. Il s’agit en particulier de fournir une information sur la faisabilité au plus tôt dans le cycle de conception, et garantir l’obtention d’un circuit « correcte par construction ». L’accent est porté sur la maîtrise (voire la réduction) de la consommation d’énergie Dans ce sens, une simulation fiable et précise permet de contrôler, dès le début du flot de conception, la consommation en énergie du réseau. Elle assure par la suite une meilleure gestion de l’énergie disponible et éventuellement une autonomie plus importante. L’outil, centré sur l’optimisation de la consommation d’énergie, est implémenté dans un environnement Matlab. Basé sur une modélisation de la consommation en énergie d’un nœud de capteur, il se veut générique aussi bien que précis. Il assure une implémentation simple de nouveaux composants à partir de fiches techniques. Ces composants sont construits sous la forme de blocs réutilisables permettant ainsi à l’utilisateur de créer sa propre librairie. En plus de l’estimation de la consommation, cet outil met en œuvre des algorithmes d’optimisation pour guider l’utilisateur vers une conception qui respecte les contraintes énergétiques et médicales de l’application (choix de composants, choix de source d’énergie, configuration du réseau, etc.). Une application est proposée d’abord au niveau d’un nœud de capteur de température corporelle communiquant par Bluetooth Low Energy. Ce même nœud est ensuite placé au sein d’un réseau de capteurs pour la surveillance de cinq paramètres physiologiques différents. Une validation expérimentale des résultats de simulation est également réalisée. / Whether it is to monitor patients at home, or to prevent the isolation and vulnerability of the elderly, the emerging electronic monitoring and assistance systems offer new opportunities. The technological development we have witnessed allows individuals, hospitals, or medical aid organizations to provide the diagnosis, prevention, control or even treatment of patients outside of conventional clinical settings (measurements of physiological parameters, drug administration, fall detection, etc.).Recent developments in connected objects made efficient remote patient monitoring possible. In other words, we are able to use a network of wearable or implantable sensors to remotely obtain real time measurements of a patient’s vital signs (temperature, heart rate, blood pressure, etc.). Data is transmitted (and / or stored) to medical personnel who are able to perform diagnosis and define treatments accordingly. An optimal design (transmission protocols, data storage, etc.) and energy management are the bottlenecks involved in the implementation of such systems. This work proposes to develop a tool to help in the design of medical sensor networks. It aims to provide information regarding feasibility during the early stages of the design thus ensuring that a "well-constructed" circuit is obtained. The emphasis is on the control (or even reduction) of energy consumption. In this regard, an efficient energy consumption simulation at the beginning of the design flow would enable the user to decide on system parameters. This will ensure an optimal management of the available energy and eventually a longer network lifetime. The proposed tool is centered on the optimization of the energy consumption using Matlab environment. It is built over a model of the energy consumption of wireless sensor nodes. It is intended to be generic and accurate. In fact, it enables fast creation of new component description based on the datasheets. These components are reusable thus producing a growing database. In addition to energy consumption estimation, the tool uses optimization routines to guide the user through an energy aware design (picking energy sources, components, network configuration, etc.) that complies with medical requirements. An application to a single Bluetooth Low Energy body temperature sensor is first proposed. The same sensor is then included in a physiological sensor network. A physical implementation is used in order to compare the results obtained through simulation with practical measurements.

The overall aim of this thesis was to develop, deploy and evaluate new IT-based methods for supporting treatment and assessment of treatment of advanced Parkinson’s disease. In this condition a number of different motor and non-motor symptoms occur in episodes of varying frequency, duration and severity. In order to determine outcome of treatment changes, repeated assessments are necessary. Hospitalization for observation is expensive and may not be representative for the situation at home. Paper home diaries have questionable reliability and storage and retrieval of results are problematic. Approaches for monitoring using wearable sensors are unable to address important non-motor symptoms. A test battery system consisting of both self-assessments of symptoms and motor function tests was constructed for a touch screen mobile phone. Tests are performed on several occasions per day during test periods of one week. Data is transmitted over the mobile net to a central server where summaries in different symptom dimensions and an overall test score per patient and test period are calculated. There is a web application that graphically presents the results to treating clinical staff. As part of this work, a novel method for assessment of spiral drawing impairment useful during event-driven sampling was developed. To date, the system has been used by over 100 patients in 10 clinics in Sweden and Italy. Evidence is growing that the test battery is useful, reliable and valid for assessment of symptoms during advanced Parkinson’s disease. Infusion of a levodopa/carbidopa gel into the small intestine has been shown to reduce variation in plasma drug levels and improve clinical response in this patient category. A pharmacokinetic-pharmacodynamic model of this intestinal gel infusion was constructed. Possibly this model can assist the process of individualization of dosage for this treatment through in numero simulations. Results from an exploratory data analysis indicate that severity measures during oral levodopa treatment may be factors to consider when deciding candidates for infusion treatment.

Significant challenges to patient monitoring systems in a hospital environment include the reliable and energy-efficient transmission of data and their real-time display. This thesis proposes innovative and novel mechanisms for the reliable transmission of patient data in Body Area Network (BAN) communication, which simultaneously ensure high throughput, low data latency, and low energy consumption by implementing energy and QoS aware routing protocols. Five main contributions are made in this regard. Firstly, a novel patient monitoring system (ZK-BAN peering framework) is proposed for real-time hospital BAN communication that displays patient data on the display units by considering data privacy, low energy consumption, better control on the devices, and patient mobility. Secondly, a novel energy-aware peering routing protocol (EPR) is introduced in which the choice of next hop is based on the residual energy and geographic information of the neighbor nodes. EPR contains three main components: a Hello protocol, a neighbor table constructor algorithm, and a routing table constructor algorithm. Thirdly, a new modular QoS-aware routing protocol (QPRD) is designed to handle the ordinary and delay-sensitive data for BAN communication in hospitals. QPRD provides an end-to-end path delay mechanism to calculate the path delays of all possible paths from a source to destination and then chooses the best path with the lowest path delay for delay-sensitive packets. Fourthly, a novel modular QoS-aware routing protocol (QPRR) is developed to handle ordinary and reliability-sensitive data for BAN communication in hospitals. The modular architecture of QPRR includes five modules: a reliability module, a packet classifier, a Hello protocol module, a routing services module, and a QoS-aware queuing module. The proposed mechanisms for end-to-end path reliability calculation and data transmission using redundant paths ensure more reliable BAN communication. Finally, a new integrated energy and QoS aware routing protocol (ZEQoS) is designed to deal with ordinary, delay-sensitive, and reliability-sensitive data packets. Extensive simulations in the OMNeT++ based Castalia 3.2 simulator show that EPR, QPRD, QPRR, and ZEQoS perform better than other similar energy and QoS aware routing protocols.

The implementation of electronic medical record (EMR) systems is a complex process that is receiving more focus in developing countries to support understaffed and overcrowded health facilities deal with the HIV/AIDS epidemic. This thesis research uses exploratory-grounded theory to study clinician perceived benefits of EMRs in antiretroviral therapy (ART) clinics at four hospitals in Ethiopia. The study is designed to understand the process, technology, social and organizational challenges associated with EMR implementation in resource-limited areas. The research found the attitude of ART clinicians towards the implementation of EMR systems to be overwhelmingly positive. The data showed that perceived benefits of EMRs are improved continuity of care, timely access to complete medical record, patient care efficiency, reduced medication errors, improved patient confidentiality, improved communication among clinicians, integration of various HIV programs, timely decision support and overall job motivation. Conversely, drawbacks to EMR implementation include productivity loss and negative impact on the interaction and relationship between clinicians and their patients. The study proposes a conceptual framework classifying key components for successful EMR implementation in Ethiopia.

CAPES; CNPq; Fundação Araucária / Este trabalho teve por objetivo o desenvolvimento de um sistema de monitoramento de sinais de ECG e temperatura, com o propósito de dar mobilidade a pessoas que necessitam de monitoramento contínuo de alguns sinais fisiológicos, tais como pessoas idosas e/ou pessoas com deficiências cardíacas ou até mesmo para atletas que desejam melhorar seu desempenho através do monitoramento de seu condicionamento físico. Foram realizadas pesquisas dos equipamentos similares que existem atualmente no mercado e que estão sendo desenvolvidos para um embasamento técnico do protótipo desenvolvido. O sistema foi desenvolvido utilizando um microcontrolador de baixo custo e consumo para aquisição dos sinais fisiológicos e um módulo Bluetooth para comunicação com um dispositivo móvel que apresenta grande capacidade de processamento e recursos para realizar o armazenamento de dados e a interface com um sistema de monitoramento para avaliação médica remota, garantindo a mobilidade, segurança e melhoria na qualidade de vida de idosos e pacientes. Os principais sinais fisiológicos são os sinais vitais, que são as funções mais básicas do corpo, tais como, temperatura corporal, frequência cardíaca, frequência respiratória e pressão arterial. No protótipo proposto, foi incorporado o monitoramento da temperatura corporal e do eletrocardiograma (ECG) completo com as 12 derivações. A frequência respiratória e pressão arterial não foram contempladas no protótipo devido à complexidade de implementação de muitos sinais fisiológicos em um único equipamento. Para definição do hardware e minimizar o risco de futuros problemas, foram também realizados testes com ferramentas de desenvolvimentos disponibilizados pelos fabricantes dos principais componentes e que também são expostos neste trabalho. Pode-se concluir que os objetivos iniciais foram alcançados pois foi desenvolvido um protótipo para monitoramento remoto de sinais de ECG e temperatura utilizando um aplicativo Android. O protótipo foi testado utilizando-se sinais de um simulador de ECG e um sensor de temperatura, atendendo às principais funcionalidades requeridas para o sistema. / This work aims to develop a system for monitoring ECG and temperature signals with the purpose of giving mobility to people requiring continuous monitoring of some physiological signals, such as the elderly and/or individuals with heart failure or even for athletes who wish to improve their performance by monitoring their fitness. Research of similar equipment that there are currently on the market and that are being developed was made for a technical base of the prototype to be developed. The system was developed using a low cost and low consumption microcontroller for the acquisition of physiological signals and a Bluetooth module for communication with a mobile device having large capacity and processing resources to perform data storage and interface with a monitoring system for remote medical evaluation, ensuring mobility, safety and improved quality of life of elderly and patients. The main physiological signals are vital signals, which are the most basic body functions such as body temperature, heart rate, respiratory rate and blood pressure. In the proposed prototype, monitoring body temperature and complete 12-lead electrocardiogram (ECG) was incorporated. The respiratory rate and blood pressure were not included in the prototype due to the complexity of implementation of many physiological signals in a single equipment. For the hardware definition and to minimize the risk of future problems, tests have also been done with development tools available from manufacturers of the main components and which are also presented in this work. It is possible to conclude that the initials objectives were achieved bacause a prototype was developed for remote monitoring of ECG and temperature signals using an Android application. The prototype was tested using an ECG simulator and a temperature sensor, attending the main required features for the system.

[pt] A Internet das Coisas (IoT) se propõe a interligar o mundo físico e a Internet, o que abre a possibilidade de desenvolvimento de diversas aplicações, principalmente na área da saúde. Essas aplicações requerem um grande número de sensores para coletar informações continuamente, gerando grandes fluxos de dados, muitas vezes excessivos, redundantes ou sem significado para as operações do sistema. Essa geração massiva de dados de sensores desperdiça recursos computacionais para adquirir, transmitir, armazenar e processar informações, levando à perda de eficiência desses sistemas ao longo do tempo. Além disso, os dispositivos IoT são projetados para serem pequenos e portáteis, alimentados por baterias, para maior mobilidade e interferência minimizada no ambiente monitorado. No entanto, esse design também resulta em restrições de consumo de energia, tornando a vida útil da bateria um desafio significativo que precisa ser enfrentado. Além disso, esses sistemas geralmente operam em ambientes imprevisíveis, o que pode gerar alarmes redundantes e insignificantes, tornando-os ineficazes. No entanto, um sistema auto-adaptativo que identifica e prevê riscos iminentes através de um sistema de pontuação de alertas antecipados (EWS) pode lidar com esses problemas. Devido ao seu baixo custo de processamento, a referência EWS pode ser incorporada em dispositivos vestíveis e sensores, permitindo um melhor gerenciamento das taxas de amostragem, transmissões, produção de alarmes e consumo de energia. Seguindo a ideia acima, esta tese apresenta uma solução que combina um sistema EWS com um algoritmo auto-adaptativo em aplicações IoT de monitoramento de pacientes. Desta forma, promovendo uma redução na aquisição e transmissão de dados , diminuindo alarmes não acionáveis e proporcionando economia de energia para esses dispositivos. Além disso, projetamos e desenvolvemos um protótipo de hardware capaz de embarcar nossa proposta, evidenciando a sua viabilidade técnica. Além disso, usando nosso protótipo, coletamos dados reais de consumo de energia dos componentes de hardware que foram usados durante nossas simulações com dados reais de pacientes provenientes de banco de dados públicos. Nossos experimentos demonstraram grandes benefícios com essa abordagem, reduzindo em 87 por cento os dados amostrados, em 99 por cento a carga total das mensagens transmitidas do dispositivo de monitoramento, 78 por cento dos alarmes e uma economia de energia de quase 82 por cento. No entanto, a fidelidade do monitoramento do estado clínico dos pacientes apresentou um erro absoluto total médio de 6,8 por cento (mais ou menos 5,5 por cento), mas minimizado para 3,8 por cento (mais ou menos 2,8 por cento) em uma configuração com menores ganhos na redução de dados. A perda de detecção total dos alarmes dependendo da configuração de frequências e janelas de tempo analisadas ficou entre 0,5 por cento e 9,5 por cento, com exatidão do tipo de alarme entre 89 por cento e 94 por cento. Concluindo, este trabalho apresenta uma abordagem para o uso mais eficiente de recursos computacionais, de comunicação e de energia para implementar aplicativos de monitoramento de pacientes baseados em IoT. / [en] The Internet of Things (IoT) proposes to connect the physical world to the Internet, which opens up the possibility of developing various applications, especially in healthcare. These applications require a huge number of sensors to collect information continuously, generating large data flows, often excessive, redundant, or without meaning for the system s operations. This massive generation of sensor data wastes computational resources to acquire, transmit, store, and process information, leading to the loss of efficiency of these systems over time. In addition, IoT devices are designed to be small and portable, powered by batteries, for increased mobility and minimized interference with the monitored environment. However, this design also results in energy consumption restrictions, making battery lifetime a significant challenge that needs to be addressed. Furthermore, these systems often operate in unpredictable environments, which can generate redundant and negligible alarms, rendering them ineffective. However, a self-adaptive system that identifies and predicts imminent risks using early-warning scores (EWS) can cope with these issues. Due to its low processing cost, EWS guidelines can be embedded in wearable and sensor devices, allowing better management of sampling rates, transmissions, alarm production, and energy consumption. Following the aforementioned idea, this thesis presents a solution combining EWS with a self-adaptive algorithm for IoT patient monitoring applications. Thus, promoting a reduction in data acquisition and transmission, decreasing non-actionable alarms, and providing energy savings for these devices. In addition, we designed and developed a hardware prototype capable of embedding our proposal, which attested to its technical feasibility. Moreover, using our wearable prototype, we collected the energy consumption data of hardware components and used them during our simulations with real patient data from public datasets. Our experiments demonstrated great benefits of our approach, reducing by 87 percent the sampled data, 99 percent the total payload of the transmitted messages from the monitoring device, 78 percent of the alarms, and an energy saving of almost 82 percent. However, the fidelity of monitoring the clinical status of patients showed a mean total absolute error of 6.8 percent (plus-minus 5.5 percent) but minimized to 3.8 percent (plus-minus 2.8 percent) in a configuration with lower data reduction gains. The total loss of alarm detection depends on the configuration of frequencies and time windows, remaining between 0.5 percent and 9.5 percent, with an accuracy of the type of alarm between 89 percent and 94 percent. In conclusion, this work presents an approach for more efficient use of computational, communication, and energy resources to implement IoT-based patient monitoring applications.

This thesis explores a methodology to quantify trust in wearable medical devices (WMD) by addressing two main challenges: identifying key factors influencing trust and developing a formal framework for precise trust quantification under uncertainty. The work empirically validates trust factors and uses a Bayesian network to quantify trust. The thesis further employs a data-driven approach to estimate Bayesian parameters, facilitating query-based inference and validating the trust model with real and synthetic datasets, culminating in a customizable parameterized trust evaluation prototype for WMD. / Advances in sensor and digital communication technologies have revolutionized the capabilities of wearable medical device (WMD) to monitor patients’ health remotely, raising growing concerns about trust in these devices. There is a need to quantify trust in WMD for their continued acceptance and adoption by different users. Quantifying trust in WMD poses two significant challenges due to their subjective and stochastic nature. The first challenge is identifying the factors that influence trust in WMD, and the second is developing a formal framework for precise quantification of trust while taking into account the uncertainty and variability of trust factors. This thesis proposes a methodology to quantify trust in WMD, addressing these challenges. In this thesis, first, we devise a method to empirically validate dominant factors that influence the trustworthiness of WMD from the perspective of device users. We identified the users’ awareness of trust factors reported in the literature and additional user concerns influencing their trust. These factors are stepping stones for defining the specifications and quantification of trust in WMD. Second, we develop a probabilistic graph using Bayesian network to quantify trust in WMD. Using the Bayesian network, the stochastic nature of trust is viewed in terms of probabilities as subjective degrees of belief by a set of random variables in the domain. We define each random variable in the network by the trust factors that are identified from the literature and validated by our empirical study. We construct the trust structure as an acyclic-directed graph to represent the relationship between the variables compactly and transparently. We set the inter-node relationships, using the goal refinement technique, by refining a high-level goal of trustworthiness to lower-level goals that can be objectively implemented as measurable factors. Third, to learn and estimate the parameters of the Bayesian network, we need access to the probabilities of all nodes, as assuming a uniform Gaussian distribution or using values based on expert opinions may not fully represent the complexities of the factors influencing trust. We propose a data-driven approach to generate priors and estimate Bayesian parameters, in which we use data collected from WMD for all the measurable factors (nodes) to generate priors. We use non-functional requirement engineering techniques to quantify the impacts between the node relationships in the Bayesian network. We design propagation rules to aggregate the quantified relationships within the nodes of the network. This approach facilitates the computation of conditional probability distributions and enables query-based inference on any node, including the high-level trust node, based on the given evidence. The results of this thesis are evaluated through several experimental validations. The factors influencing trust in WMD are empirically validated by an extensive survey of 187 potential users. The learnability, and generalizability of the proposed trust network are validated with a real dataset collected from three users of WMD in two conditions, performing predefined activities and performing regular daily activities. To extend the variability of conditions, we generated an extensive and representative synthetic dataset and validated the trust network accordingly. Finally, to test the practicality of our approach, we implemented a user-configurable, parameterized prototype that allows users of WMD to construct a customizable trust network and effectively compare the trustworthiness of different devices. The prototype enables the healthcare industry to adapt and adopt this method to evaluate the trustworthiness of WMD for their own specific use cases. / Thesis / Doctor of Philosophy (PhD) / In this thesis, two challenges in quantifying trust in wearable medical devices, are addressed. The first challenge is the identification of factors influencing trust which are inherently subjective and vary widely among users. To address this challenge, we conducted an extensive survey to identify and validate the trust factors. These factors are stepping stones for defining the specifications and quantifying trust in wearable medical devices. The second challenge is to develop a precise method for quantification of trust while taking into account the uncertainty and variability of trust factors. We constructed a Bayesian network, that captures the complexities of trust as probabilities of the trust factors (identified from the survey) and developed a data-driven approach to estimate the parameters of the Bayesian network to compute the measure of trust. The findings of this thesis are empirically and experimentally validated across multiple use cases, incorporating real and synthetic data, various testing conditions, and diverse Bayesian network configurations. Additionally, we developed a customizable, parameterized prototype that empowers users and healthcare providers to effectively assess and compare the trustworthiness of different wearable medical devices.

The purpose of this quantitative, descriptive study was to identify shortcomings in the implementation of the Batho Pele Principles in a public hospital. Findings were obtained from a range of patients who had been admitted to specific units for three or more days, and more evidence was gathered from articles in mass media. Data was collected through a structured questionnaire from one hundred respondents (n=100) and analysed by means of descriptive statistics. The research findings revealed that none of the Batho Pele Principles were implemented effectively and that patients in general were not satisfied with treatment in public hospitals. Shortcomings are attributed to insufficient management skills and knowledge on different levels of the health care system, as well as a lack of awareness among patients of their rights and responsibilities in health care. / Health Studies / M.A. (Public Health)

The purpose of this quantitative, descriptive study was to identify shortcomings in the implementation of the Batho Pele Principles in a public hospital. Findings were obtained from a range of patients who had been admitted to specific units for three or more days, and more evidence was gathered from articles in mass media. Data was collected through a structured questionnaire from one hundred respondents (n=100) and analysed by means of descriptive statistics. The research findings revealed that none of the Batho Pele Principles were implemented effectively and that patients in general were not satisfied with treatment in public hospitals. Shortcomings are attributed to insufficient management skills and knowledge on different levels of the health care system, as well as a lack of awareness among patients of their rights and responsibilities in health care. / Health Studies / M.A. (Public Health)

Este trabalho apresenta a proposta de um protocolo de comunicação de dados integrando tecnologias de internet das coisas, computação móvel e armazenamento em nuvem, aplicado ao telemonitoramento sob demanda de sinais fisiológicos. O objetivo do trabalho foi adquirir, transmitir, armazenar, receber e permitir a visualização sob demanda, mantendo a integridade da representação do sinal biomédico para a análise médica, sem alterar a mobilidade do paciente em monitoramento. O trabalho utiliza um canal de ECG, para adquirir o sinal de eletrocardiografia do paciente, que é conectado via Bluetooth com um dispositivo de computação móvel. O dispositivo de computação móvel, com acesso a internet sem fio, envia o sinal fisiológico através do protocolo proposto para uma base segura de armazenamento de informações em nuvem, podendo ser acessada sob demanda por um especialista para realizar a avaliação médica. O telemonitoramento sob demanda permite ao especialista: visualizar e analisar dados recentes, como se fosse um monitoramento remoto em tempo real do paciente; e visualizar e analisar dados anteriores que estão armazenados na nuvem, semelhante à análise de um exame realizado previamente. O protocolo proposto possui características de segurança da informação, mantendo a integridade da representação no tempo do sinal fisiológico, ainda que dados sejam corrompidos. O trabalho envolveu o uso de tecnologias recentes aplicadas às necessidades de registros de sinais fisiológicos. Estas tecnologias estão em evolução, os padrões não estão consolidados, ocorrendo alterações à medida que novas necessidades vão sendo apresentadas, assim como novas soluções venham a ser desenvolvidas. Como dispositivo de computação móvel foi utilizado neste trabalho um tablet, podendo ser utilizado um smartphone. O protocolo para este trabalho foi utilizado com o sinal de um canal de eletrocardiografia, podendo ser modificado para atender outras necessidades, incluindo outros sinais fisiológicos. Neste trabalho foi utilizado como sinal fisiológico o sinal de um simulador de ECG. / This work shows a proposal for a data communication protocol integrating internet of things technologies, mobile computing and cloud storage, applied to on-demand remote monitoring physiological signals. The aim of this work was to acquire, transmit, store, receive and allow the on-demand visualization, keeping the integrity of the biomedical signals representation for medical analysis, without changing the mobility of the patient being monitored. The work uses an ECG channel to acquire the patient’s electrocardiography signal, which is linked via Bluetooth to a mobile computing device. The mobile computing device, with wireless internet access, sends the physiological signal through the proposed protocol to a safe base of cloud information storage, which can be accessed on demand by a specialist to do the medical evaluation. On-demand remote monitoring allows the specialist to visualize and analyze recent data, as if it were real time remote monitoring of the patient, and visualize and analyze previous data that are stored in the cloud, similar to an analysis of a previously made exam. The proposed protocol has information security features, keeping the integrity of the time representation of the physiological signal, even if the data are corrupted. The work involved the use of new technologies applied to the necessity of physiological signals record. These technologies are evolving. The patterns are not consolidated, and changes are made as new necessities are presented and new solutions developed. For this work, it was used a tablet as a computing mobile device. However, a smartphone could also be used. The protocol was used with an electrocardiography channel signal, which can be modified to attend other necessities, including other physiological signals. As a physiological signal, for this work, it was used an ECG simulator signal.