FIT FOR USE ASSESSMENT OF BIOZEN AS A BIOMETRIC SENSOR CONCENTRATOR FOR REMOTE PATIENT MONITORING

In recent years, COVID-19 highlighted the importance of virtual health solutions with regard to improving patient health and conserving valuable hospital resources. Currently, the Defense Health Agency (DHA) does not own a remote patient-monitoring solution and relies on external commercial entities to provide the application and services. This could potentially lead to the DHA not retaining complete data ownership when patient data would reside on or traverse through commercial remote patient-monitoring solutions. This thesis evaluates BioZen, a DHA-owned biomedical sensor concentrator designed to run on a mobile phone, as a remote patient-monitoring tool. From this analysis, several key measures of effectiveness and measures of performance for remote patient-monitoring tools are identified and operationalized to measure the overall value BioZen brings to the DHA. Based on this research, it was found that the current build of BioZen, 2.0.0, is unable to meet any of the measures outlined in the study as a remote patient-monitoring tool. A future build of BioZen, or any remote patient-monitoring tool, could then be assessed using the measures of effectiveness and measures of performance within this study to determine the overall value brought to the DHA.Defense Health Agency, 7700 Arlington Boulevard, Falls Church, VA 22042Captain, United States ArmyLieutenant, United States NavyApproved for public release. Distribution is unlimited

Wearable Devices in Health Monitoring from the Environmental towards Multiple Domains: A Survey

The World Health Organization (WHO) recognizes the environmental, behavioral, physiological, and psychological domains that impact adversely human health, well-being, and quality of life (QoL) in general. The environmental domain has significant interaction with the others. With respect to proactive and personalized medicine and the Internet of medical things (IoMT), wearables are most important for continuous health monitoring. In this work, we analyze wearables in healthcare from a perspective of innovation by categorizing them according to the four domains. Furthermore, we consider the mode of wearability, costs, and prolonged monitoring. We identify features and investigate the wearable devices in the terms of sampling rate, resolution, data usage (propagation), and data transmission. We also investigate applications of wearable devices. Web of Science, Scopus, PubMed, IEEE Xplore, and ACM Library delivered wearables that we require to monitor at least one environmental parameter, e.g., a pollutant. According to the number of domains, from which the wearables record data, we identify groups: G1, environmental parameters only; G2, environmental and behavioral parameters; G3, environmental, behavioral, and physiological parameters; and G4 parameters from all domains. In total, we included 53 devices of which 35, 9, 9, and 0 belong to G1, G2, G3, and G4, respectively. Furthermore, 32, 11, 7, and 5 wearables are applied in general health and well-being monitoring, specific diagnostics, disease management, and non-medical. We further propose customized and quantified output for future wearables from both, the perspectives of users, as well as physicians. Our study shows a shift of wearable devices towards disease management and particular applications. It also indicates the significant role of wearables in proactive healthcare, having capability of creating big data and linking to external healthcare systems for real-time monitoring and care delivery at the point of perception

Enabling Remote Responder Bio-Signal Monitoring in a Cooperative Human–Robot Architecture for Search and Rescue

The roles of emergency responders are challenging and often physically demanding, so it is essential that their duties are performed safely and effectively. In this article, we address real-time bio-signal sensor monitoring for responders in disaster scenarios. In particular, we propose the integration of a set of health monitoring sensors suitable for detecting stress, anxiety and physical fatigue in an Internet of Cooperative Agents architecture for search and rescue (SAR) missions (SAR-IoCA), which allows remote control and communication between human and robotic agents and the mission control center. With this purpose, we performed proof-of-concept experiments with a bio-signal sensor suite worn by firefighters in two high-fidelity SAR exercises. Moreover, we conducted a survey, distributed to end-users through the Fire Brigade consortium of the Provincial Council of Málaga, in order to analyze the firefighters’ opinion about biological signals monitoring while on duty. As a result of this methodology, we propose a wearable sensor suite design with the aim of providing some easy-to-wear integrated-sensor garments, which are suitable for emergency worker activity. The article offers discussion of user acceptance, performance results and learned lessons.This work has been partially funded by the Ministerio de Ciencia, Innovación y Universidades, Gobierno de España, projects RTI2018-093421-B-I00 and PID2021-122944OB-I00. Partial funding for open access charge: Universidad de Málag

Challenges and Limitation Analysis of an IoT-Dependent System for Deployment in Smart Healthcare Using Communication Standards Features

The use of IoT technology is rapidly increasing in healthcare development and smart healthcare system for fitness programs, monitoring, data analysis, etc. To improve the efficiency of monitoring, various studies have been conducted in this field to achieve improved precision. The architecture proposed herein is based on IoT integrated with a cloud system in which power absorption and accuracy are major concerns. We discuss and analyze development in this domain to improve the performance of IoT systems related to health care. Standards of communication for IoT data transmission and reception can help to understand the exact power absorption in different devices to achieve improved performance for healthcare development. We also systematically analyze the use of IoT in healthcare systems using cloud features, as well as the performance and limitations of IoT in this field. Furthermore, we discuss the design of an IoT system for efficient monitoring of various healthcare issues in elderly people and limitations of an existing system in terms of resources, power absorption and security when implemented in different devices as per requirements. Blood pressure and heartbeat monitoring in pregnant women are examples of high-intensity applications of NB-IoT (narrowband IoT), technology that supports widespread communication with a very low data cost and minimum processing complexity and battery lifespan. This article also focuses on analysis of the performance of narrowband IoT in terms of delay and throughput using singleand multinode approaches. We performed analysis using the message queuing telemetry transport protocol (MQTTP), which was found to be efficient compared to the limited application protocol (LAP) in sending information from sensors.Ministerio Español de Ciencia e Innovación under project number PID2020-115570GB-C22 (DemocratAI::UGR)Cátedra de Empresa Tecnología para las Personas (UGR-Fujitsu

IoT and fog computing-based monitoring system for cardiovascular patients with automatic ECG classification using deep neural networks

[EN] Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a dataset of 8.528 short single-lead ECG records using two merge MobileNet networks that classify data with an accuracy of 90% for atrial fibrillation.This work was partly supported by the Spanish Government (RTI2018-095390-B-C31), Universitat Politecnica de Valencia Research Grant PAID-10-19. S.G-O has been funded by grant PDBCEx COLDOC 679, scholarship programme from COLCIENCIAS (Administrative Department of Science, Technology and Innovation of Colombia).Rincón-Arango, JA.; Guerra-Ojeda, S.; Carrascosa Casamayor, C.; Julian, V. (2020). IoT and fog computing-based monitoring system for cardiovascular patients with automatic ECG classification using deep neural networks. Sensors. 20(24):1-19. https://doi.org/10.3390/s20247353119202

GNSS-free outdoor localization techniques for resource-constrained IoT architectures : a literature review

Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/

Situational awareness through IoT sensors : A smart healthcare system as a use case

Emerging technologies of the Internet of Things are getting increasingly significant and to some extent essential as well to the society we are living in. These technologies have shown ability over the time to be implemented in a number of different fields, for instance, Smart Home, Smart Building, Smart City, Smart Retail, Smart Supply Chain, Smart Farming, Smart Grid, Industrial Internet and many more. Incorporation of Internet of Things technologies in the healthcare sector has potential to benefit not only medical related enterprises but at the same time it can improve the overall health and well-being of individuals as well. The deployment of IoT integrated systems has to deal with fairly heterogeneous environments that consist of a large number of sensors and actuators which all can be quite different from one another in many aspects. For example, they can use different operating systems and can have different hardware architecture. Such sensors are sometimes used for situational awareness of the surrounding and for making the individuals interact better with their environment. Such variety of applications and tasks poses a problem for system designers and developers on the choice of the most suitable technology to be employed to accomplish a specific task. This thesis explores the potential of Internet of Things technologies in the medical sector. We used analytical hierarchical process to have a kind of situational awareness through IoT technologies. As an use case, a healthcare system was considered for elderly people with neurological problems who need special care – people suffering with dementia for example. At the same time we have taken into account for the proposed system that it would enable regular people track and monitor their usual activities with a focus on improving the quality of life and enhancing their overall wellbeing. It is of prime importance for the system designers and developers that they have an idea about the potential IoT technologies and applications that can help this cause. We have considered eleven different IoT technologies to select from for the proposed paradigm. The decision of selecting the most appropriate technology obviously depends upon different criteria. Every IoT technology has its pros and cons. According to the needs of the proposed healthcare system, we have constructed a multi-criteria hierarchical model to assess the potential of those eleven IoT technologies for the healthcare system and chosen the best one based on set criteria and sub criteria. A 4-tier Analytical Hierarchical model is used to compare those technologies in terms of their quality of service or effectiveness, their acceptability and from the cost perspective. These criteria are then further divided into sub-criteria and the technologies are compared with respect to these ten sub-criteria to have a more thorough and comprehensive analysis. For these comparisons, quantitative data were collected from the internet including IEEE articles, and some of the comparisons are purely subjective. The results indicate that wide-area low-power solutions show more potential for the proposed healthcare system than other IoT technologies which we used for comparison, and SigFox tops the table. Also WiFi solutions have shown significant potential. But again, every technology has its shortcomings as well. Further studies are needed to see if we can somehow make a hybrid healthcare system that utilizes multiple IoT technologies and incorporate the plus points of all of them into the system; such future system can prove to be revolutionary in the medical care

Applications of Engineering 4.0 to Improve the Safety of Metalworking Operators: The Ansaldo Energia Case

The paper describes how, on behalf of Ansaldo Energia Spa, a multidisciplinary team developed a methodology based on Industry 4.0 technologies, an approach that allows rescue teams to quickly intervene in the event of a mandown in isolated areas of the plant, where the unfortunate person would risk being found with significant delay and onsequent problems for his physical well-being. Under the supervision of the team, a highly specialized supplier created a suitable hardware and software device to achieve this outcome. Such a device can immediately warn rescue crews in real time as soon as an incident occurs, as well as geo-locate the man on the ground with exceptional precision. Once developed, the approach was standardized in a set of sequential and generic procedures in order to make it adaptable to any sort of firm, construction site, or workshop where a man-down event may happen. The methodology is set up as a real toolkit to protect operators from severe damage that can result from long waits for rescue teams, whenever operators experience negative events for their safety being them exogenous (fainting illnesses, heart attacks, epileptic attacks, strokes, etc.) or endogenous (accidents in the workplace)