The Accuracy of Temperature Monitoring of the Incubator for Newborns

The objective of this paper is to investigate the performance of the Incubator for Newborns at the departments of intensive care in Jafer Ibn Aouf Reference Children Hospital, is governmental Children specialized hospital. Using the INCUTM Incubator Analyzer to analyzing various aspects of performance of neonatal incubator and its compliance with the set requirements and regulations according to the technical standard IEC (International Electro technical Commission) 60601-2-19. The data used in this study were obtained by interpreting of the performance test results of neonatal incubator. Numerically, According to the results presented in Tables (1 & 3), the neonatal incubator have achieved acceptable performance and sustaining the requirements of the standard IEC 60601-2-19. In other words, the temperature at points T1, T2, T3, and T4 does not differ from the neonatal incubator average temperature by more than 0.8°C, and this temperature does not differ more than 1.5 °C from the incubator control temperature. Compared to the established technique, the estimation error is negligible

Neonatal Infrared Thermography Image Processing

Tesina feta en col.laboració amb RWTH AachenThe temperature changes inside incubator a ect the newborns, who are the most delicate patients. The project proposes an innovative method to monitor the skin temperature of the neonates. The temperature monitoring is carried out by a virtual sensor. This virtual sensor is based in an infrared thermal camera that is placed outside the incubator. In order to obtain the infrared radiation through the incubator Plexiglas, an infrared transparent window is required. The experiment carried out was focused on obtaining the transparent properties in the infrared spectral range measurement of this window. On the other hand, the thermal imaging processing is necessary to obtain the thermal information from the infrared imager and to be able to track the region of interest throughout the eld of view

Wearable Computing for Health and Fitness: Exploring the Relationship between Data and Human Behaviour

Health and fitness wearable technology has recently advanced, making it easier for an individual to monitor their behaviours. Previously self generated data interacts with the user to motivate positive behaviour change, but issues arise when relating this to long term mention of wearable devices. Previous studies within this area are discussed. We also consider a new approach where data is used to support instead of motivate, through monitoring and logging to encourage reflection. Based on issues highlighted, we then make recommendations on the direction in which future work could be most beneficial

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 376)

This bibliography lists 265 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Jun. 1993. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

Coupled radiative and convective heat losses from preterm infant inside an incubator with radiant heaters

Preterm infants face difficulties in maintaining their body temperature due to low metabolic rates of heat generation. Therefore, using incubators and radiant warmers is crucial for their comfort and health. The objective of the present work is to analyze the heat transfer processes for a preterm infant nursed in a simplified incubator under two different operating conditions: in the first one a classical simple incubator is considered and in the second case radiant heaters are used. This is achieved by using ANSYS Fluent 19.0 which his based on the finite volume method to discretize the Navier-Stokes, energy and radiation transfer equations. Conduction, convection and radiation heat transfer modes are modelled in the simulations and coupled to empirical correlations for metabolic heat generation and evaporative heat losses. The different incubator scenarios considered here are compared in terms of convection and radiation heat losses and skin temperature to access the thermal comfort of the preterm infant

Personalized data analytics for internet-of-things-based health monitoring

The Internet-of-Things (IoT) has great potential to fundamentally alter the delivery of modern healthcare, enabling healthcare solutions outside the limits of conventional clinical settings. It can offer ubiquitous monitoring to at-risk population groups and allow diagnostic care, preventive care, and early intervention in everyday life. These services can have profound impacts on many aspects of health and well-being. However, this field is still at an infancy stage, and the use of IoT-based systems in real-world healthcare applications introduces new challenges. Healthcare applications necessitate satisfactory quality attributes such as reliability and accuracy due to their mission-critical nature, while at the same time, IoT-based systems mostly operate over constrained shared sensing, communication, and computing resources. There is a need to investigate this synergy between the IoT technologies and healthcare applications from a user-centered perspective. Such a study should examine the role and requirements of IoT-based systems in real-world health monitoring applications. Moreover, conventional computing architecture and data analytic approaches introduced for IoT systems are insufficient when used to target health and well-being purposes, as they are unable to overcome the limitations of IoT systems while fulfilling the needs of healthcare applications. This thesis aims to address these issues by proposing an intelligent use of data and computing resources in IoT-based systems, which can lead to a high-level performance and satisfy the stringent requirements. For this purpose, this thesis first delves into the state-of-the-art IoT-enabled healthcare systems proposed for in-home and in-hospital monitoring. The findings are analyzed and categorized into different domains from a user-centered perspective. The selection of home-based applications is focused on the monitoring of the elderly who require more remote care and support compared to other groups of people. In contrast, the hospital-based applications include the role of existing IoT in patient monitoring and hospital management systems. Then, the objectives and requirements of each domain are investigated and discussed. This thesis proposes personalized data analytic approaches to fulfill the requirements and meet the objectives of IoT-based healthcare systems. In this regard, a new computing architecture is introduced, using computing resources in different layers of IoT to provide a high level of availability and accuracy for healthcare services. This architecture allows the hierarchical partitioning of machine learning algorithms in these systems and enables an adaptive system behavior with respect to the user's condition. In addition, personalized data fusion and modeling techniques are presented, exploiting multivariate and longitudinal data in IoT systems to improve the quality attributes of healthcare applications. First, a real-time missing data resilient decision-making technique is proposed for health monitoring systems. The technique tailors various data resources in IoT systems to accurately estimate health decisions despite missing data in the monitoring. Second, a personalized model is presented, enabling variations and event detection in long-term monitoring systems. The model evaluates the sleep quality of users according to their own historical data. Finally, the performance of the computing architecture and the techniques are evaluated in this thesis using two case studies. The first case study consists of real-time arrhythmia detection in electrocardiography signals collected from patients suffering from cardiovascular diseases. The second case study is continuous maternal health monitoring during pregnancy and postpartum. It includes a real human subject trial carried out with twenty pregnant women for seven months

Neonatal Infrared Thermography Image Processing

Tesina feta en col.laboració amb RWTH AachenThe temperature changes inside incubator a ect the newborns, who are the most delicate patients. The project proposes an innovative method to monitor the skin temperature of the neonates. The temperature monitoring is carried out by a virtual sensor. This virtual sensor is based in an infrared thermal camera that is placed outside the incubator. In order to obtain the infrared radiation through the incubator Plexiglas, an infrared transparent window is required. The experiment carried out was focused on obtaining the transparent properties in the infrared spectral range measurement of this window. On the other hand, the thermal imaging processing is necessary to obtain the thermal information from the infrared imager and to be able to track the region of interest throughout the eld of view