Medical data processing and analysis for remote health and activities monitoring

Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

An Energy-Autonomous Smart Shirt employing wearable sensors for Users’ Safety and Protection in Hazardous Workplaces

none4siWearable devices represent a versatile technology in the IoT paradigm, enabling noninvasive and accurate data collection directly from the human body. This paper describes the development of a smart shirt to monitor working conditions in particularly dangerous workplaces. The wearable device integrates a wide set of sensors to locally acquire the user’s vital signs (e.g., heart rate, blood oxygenation, and temperature) and environmental parameters (e.g., the concentration of dangerous gas species and oxygen level). Electrochemical gas-monitoring modules were designed and integrated into the garment for acquiring the concentrations of CO, O2, CH2O, and H2S. The acquired data are wirelessly sent to a cloud platform (IBM Cloud), where they are displayed, processed, and stored. A mobile application was deployed to gather data from the wearable devices and forward them toward the cloud application, enabling the system to operate in areas where aWiFi hotspot is not available. Additionally, the smart shirt comprises a multisource harvesting section to scavenge energy from light, body heat, and limb movements. Indeed, the wearable device integrates several harvesters (thin-film solar panels, thermoelectric generators (TEGs), and piezoelectric transducers), a low-power conditioning section, and a 380 mAh LiPo battery to accumulate the recovered charge. Field tests indicated that the harvesting section could provide up to 216 mW mean power, fully covering the power requirements (P = 1.86 mW) of the sensing, processing, and communication sections in all considered conditions (3.54 mW in the worst-case scenario). However, the 380 mAh LiPo battery guarantees about a 16-day lifetime in the complete absence of energy contributions from the harvesting section.Special Issue “Innovative Materials, Smart Sensors and IoT-based Electronic Solutions for Wearable Applications”, https://www.mdpi.com/journal/applsci/special_issues/Materials_Sensors_Electronic_Solutions_Wearable_ApplicationsopenRoberto De Fazio, Abdel-Razzak Al-Hinnawi, Massimo De Vittorio, Paolo ViscontiDE FAZIO, Roberto; Al-Hinnawi, Abdel-Razzak; DE VITTORIO, Massimo; Visconti, Paol

A Discussion on Fall Detection Issues and Its Deployment: When cloud meets battery

IEEE International Conference on Cloud Computing and Big Data Analysis (3rd. 2018., Chengdu, China

Low Cost LoRa based Network for Forest Fire Detection

[EN] Forest fires are one of the main environmental problems in the entire Mediterranean basin. In a context where low power and long-range networks (LPWAN) are increasingly common to the rise of Internet of Things (IoT) architecture, the interest in providing solutions to monitor scenarios and fire prevention based on these technologies is huge. This paper presents a low cost Long Range (LoRa) based network able to evaluate level of fire risk and the presence of a forest fire. The system is composed by a LoRa node and a set of sensors to measure the temperature, relative humidity, wind speed and CO2. The evaluation algorithm is based on the 30- 30-30 rule. Through website the users can see the parameters measured by nodes in real time. The system has been tested in a real environment and the results show that it is possible to cover a circular area of 1.1km or radius.This work has been partially supported by the Ministerio de Ciencia, Innovación y Universidades through the Ayudas para la adquisición de equipamiento científicotécnico, Subprograma estatal de infraestructuras de investigación y equipamiento científico-técnico (plan Estatal I+D+i 2017-2020) (project EQC2018-004988-P) and through the Research Contracts of Youth Employment of the University of Granada, through its operative program of Youth Guarantee of the Regional Government of Andalusia and the European Social Fund.Vega-Rodríguez, R.; Sendra, S.; Lloret, J.; Romero-Díaz, P.; García-Navas, JL. (2019). Low Cost LoRa based Network for Forest Fire Detection. IEEE. 177-184. https://doi.org/10.1109/IOTSMS48152.2019.8939193S17718

City Data Fusion: Sensor Data Fusion in the Internet of Things

Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. We introduce the concept of IoT and present in detail ten different parameters that govern our sensor data fusion evaluation framework. We then evaluate the current state-of-the art in sensor data fusion against our sensor data fusion framework. Our main goal is to examine and survey different sensor data fusion research efforts based on our evaluation framework. The major open research issues related to sensor data fusion are also presented.Comment: Accepted to be published in International Journal of Distributed Systems and Technologies (IJDST), 201

A Methodology for Trustworthy IoT in Healthcare-Related Environments

The transition to the so-called retirement years, comes with the freedom to pursue old passions and hobbies that were not possible to do in the past busy life. Unfortunately, that freedom does not come alone, as the previous young years are gone, and the body starts to feel the time that passed. The necessity to adapt elder way of living, grows as they become more prone to health problems. Often, the solution for the attention required by the elders is nursing homes, or similar, that take away their so cherished independence. IoT has the great potential to help elder citizens stay healthier at home, since it has the possibility to connect and create non-intrusive systems capable of interpreting data and act accordingly. With that capability, comes the responsibility to ensure that the collected data is reliable and trustworthy, as human wellbeing may rely on it. Addressing this uncertainty is the motivation for the presented work. The proposed methodology to reduce this uncertainty and increase confidence relies on a data fusion and a redundancy approach, using a sensor set. Since the scope of wellbeing environment is wide, this thesis focuses its proof of concept on the detection of falls inside home environments, through an android app using an accelerometer sensor and a micro- phone. The experimental results demonstrates that the implemented system has more than 80% of reliable performance and can provide trustworthy results. Currently the app is being tested also in the frame of the European Union projects Smart4Health and Smart Bear.A transição para os chamados anos de reforma, vem com a liberdade de perseguir velhas pai- xões e passatempos que na passada vida ocupada não eram possíveis de realizar. Infelizmente, essa liberdade não vem sozinha, uma vez que os anos jovens anteriores terminaram, e o corpo começa a sentir o tempo que passou. A necessidade de adaptar o modo de vida dos menos jovens, cresce à medida que estes se tornam mais propensos a problemas de saúde. Muitas vezes, a solução para a atenção que os mais idosos necessitam são os lares de idosos, ou similares, que lhes tiram a tão querida independência. IoT tem o grande potencial de ajudar os cidadãos idosos a permanecerem mais saudá- veis em casa, uma vez que tem a possibilidade de se ligar e criar sistemas não intrusivos capa- zes de interpretar dados e agir em conformidade. Com essa capacidade, vem a responsabili- dade de assegurar que os dados recolhidos são fiáveis e de confiança, uma vez que o bem- estar humano possa depender dos mesmos. Abordar esta incerteza é a motivação para o tra- balho apresentado. A metodologia proposta para reduzir esta incerteza e aumentar a confiança no sistema baseia-se numa fusão de dados e numa abordagem de redundância, utilizando um conjunto de sensores. Uma vez que o assunto de bem-estar e saúde é vasto, esta tese concentra a sua prova de conceito na deteção de quedas dentro de ambientes domésticos, através de uma aplicação android, utilizando um sensor de acelerómetro e um microfone. Os resultados expe- rimentais demonstram que o sistema implementado tem um desempenho superior a 80% e pode fornecer dados fiáveis. Atualmente a aplicação está a ser testada também no âmbito dos projetos da União Europeia Smart4Health e Smart Bear

Fall Detection Analysis Using a Real Fall Dataset

International Conference on Soft Computing Models in Industrial and Environmental Applications (13th. 2018. San Sebastián

A direct-sequence spread-spectrum communication system for integrated sensor microsystems

Some of the most important challenges in health-care technologies have been identified to be development of noninvasive systems and miniaturization. In developing the core technologies, progress is required in pushing the limits of miniaturization, minimizing the costs and power consumption of microsystems components, developing mobile/wireless communication infrastructures and computing technologies that are reliable. The implementation of such miniaturized systems has become feasible by the advent of system-on-chip technology, which enables us to integrate most of the components of a system on to a single chip. One of the most important tasks in such a system is to convey information reliably on a multiple-access-based environment. When considering the design of telecommunication system for such a network, the receiver is the key performance critical block. The paper describes the application environment, the choice of the communication protocol, the implementation of the transmitter and receiver circuitry, and research work carried out on studying the impact of input data characteristics and internal data path complexity on area and power performance of the receiver. We provide results using a test data recorded from a pH sensor. The results demonstrate satisfying functionality, area, and power constraints even when a degree of programmability is incorporated in the system