Carlos Abreu

QoS-based management of biomedical wireless sensor networks for patient monitoring

Biomedical wireless sensor networks are a key technology to support the development of new applications and services targeting patient monitoring, in particular, regarding data collection for medical diagnosis and continuous health assessment. However, due to the critical nature of medical applications, such networks have to satisfy demanding quality of service requirements, while guaranteeing high levels of confidence and reliability. Such goals are influenced by several factors, where the network topology, the limited throughput, and the characteristics and dynamics of the surrounding environment are of major importance. Harsh environments, as hospital facilities, can compromise the radio frequency communications and, consequently, the network’s ability to provide the quality of service required by medical applications. Furthermore, the impact of such environments on the network’s performance is hard to manage due to its random and unpredictable nature. Consequently, network planning and management, in general or step-down hospital units, is a very hard task. In such context, this work presents a quality of service based management tool to help healthcare professionals supervising the network’s performance and to assist them managing the admission of new sensor nodes (i.e., patients to be monitored) to the biomedical wireless sensor network. The proposed solution proves to be a valuable tool both, to detect and classify potential harmful variations in the quality of service provided by the network, avoiding its degradation to levels where the biomedical signs would be useless; and to manage the admission of new patients to the network.

Wireless sensor networks for biomedical applications

Biomedical wireless sensor networks empowers the development of new applications and services to improve the quality of medical care provided to the citizens. In such context, these networks need to be integrated on the existing network infrastructure and information systems and, at the same time, guarantee high levels of quality of service. These requirements of quality of service must be addressed on the project and development stages and monitored during the network operation. On the project stage, the requirements of quality of service must be identified and accurately characterised; on the development stage, it is necessary to implement the mechanisms that ensure its accomplishment; finally, during the network operation, it is crucial to monitor the network to evaluate its performance and manage the admission of new nodes. Another important issue related with biomedical wireless sensor networks is the network lifetime, designed to be as long as possible. This work discusses these topics and presents some achievements on the evaluation of the quality of service at the development time, on the real-time monitoring of the network performance at run time, as well as on network lifetime extension.

Preventing Alzheimer's Wandering: The Potential of Involving Communities

With increased life expectancy, the incidence of age-related cognitive impairments, faced by the elderly and older generations, is growing. Among the population with cognitive impairments, those that suffer from Alzheimers disease are the most common. The Alzheimers disease is a chronic degenerative brain disorder that is characterised by a failure of memory and, in some instances, by disorders in language, perception and planning. As a consequence of the progressive damages imposed by the illness, patients will increasingly seek and need assistance. This paper presents a tool to aid the development and managing of caregiving communities, comprising immediate family members, relatives, neighbours and healthcare professionals, to assist patients with Alzheimers disease. Such communities could have a strong impact on the quality of care provided to the patients. At the same time, it is hoped that involving communities will significantly improve the quality of life of Alzheimers patients and their families while reducing the costs related to the care provided.

Smart context-aware QoS-based admission control for biomedical wireless sensor networks

Wireless sensor networks are being used as the enabling technology that helps to support the development of new applications and services targeting the domain of healthcare, in particular, regarding data collection for continuous health monitoring of patients or to help physicians in their diagnosis and further treatment assessment. Therefore, due to the critical nature of both medical data and medical applications, such networks have to satisfy demanding quality of service requirements. Despite the efforts made in the last few years to develop quality of service mechanisms targeting wireless sensor networks and its wide range of applications, the network deployment scenario can severely restrict the networks ability to provide the required performance. Furthermore, the impact of such environments on the network performance is hard to predict and manage due to its random nature. In this way, network planning and management, in complex environments like general or step-down hospital units, is a problem still looking for a solution. In such context, this paper presents a smart context-aware quality of service based admission control method to help engineers, network administrators, and healthcare professionals managing and supervising the admission of new patients to biomedical wireless sensor networks. The proposed method was tested in a small sized hospital. In view of the results achieved during the experiments, the proposed admission control method demonstrated its ability, not only to control the admission of new patients to the biomedical wireless sensor network, but also to find the best location to admit the new patients within the network. By placing the new sensor nodes on the most favourable locations, this method is able to select the network topology in view of mitigating the quality of service provided by the network.

Handbook of Research on Computational Simulation and Modeling in Engineering

Multiple disciplines depend on computer programs and software to predict project challenges, outcomes, and solutions. Through the use of virtual prototyping, researchers and professionals are better able to analyze data and improve projects without direct experimentation, which can be costly or dangerous. The Handbook of Research on Computational Simulation and Modeling in Engineering is an authoritative reference source on the computer models and technologies necessary to enhance engineering structures and planning for real-world applications. This publication is an essential resource for academicians, researchers, advanced-level students, technology developers, and engineers interested in the advancements taking place at the intersection of computer technology and the physical sciences. This publication features chapters on the advanced technologies developed within the field of engineering including prediction tools, software programs, algorithms, and theoretical and computational models.

Deployment of wireless sensor networks for biomedical applications

Biomedical wireless sensor networks are a key technology to enable the development of new healthcare services and/or applications, reducing costs and improving the citizens quality of life. However, since they deal with health data, such networks should implement mechanisms to enforce high levels of quality of service. In most cases, the sensor nodes that form such networks are small and battery powered, and these extra quality of service mechanisms mean significant lifetime reduction due to the extra energy consumption. The network lifetime is thus a relevant feature to ensure the quality of service requirements. In order to maximise the network lifetime and its ability to offer the required quality of service new strategies are needed to increase the energy efficiency and balance in the network. The focus of this work is the use of the remaining energy in each node combined with information on the reliability of the wireless links, as a metric to form reliable and energy-aware routes throughout the network. This paper presents and discusses an implementation of a lifetime-extending methodology based on energy-aware routing and relay nodes simulated for three different logical topologies. Our conclusion is that such methodology may increase the network lifetime an average of 45%.

Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks

The use of wireless sensor networks in healthcare has the potential to enhance the services provided to citizens. In particular, they play an important role in the development of state-of-the-art patient monitoring applications. Nevertheless, due to the critical nature of the data conveyed by such patient monitoring applications, they have to fulfil high standards of quality of service in order to obtain the confidence of all players in the healthcare industry. In such context, vis-a-vis the quality of service being provided by the wireless sensor network, this work presents an adaptive and context-aware method to detect and classify performance degradation events. The proposed method has the ability to catch the most significant and damaging variations on the metrics being used to quantify the quality of service provided by the network without overreacting to small and innocuous variations on the metric’s value.

Stabilization of model-based networked control systems

A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.

Towards long-term intracranial pressure monitoring based on implantable wireless microsystems and wireless sensor networks

Ambient Assisted Living (AAL) aims to provide support to healthcare professionals making use of sensing, and information and communication technologies. Brain related information is becoming more and more relevant for many pathologies, but access to long-term information from brain to feed such AAL technologies is still giving the first steps. One main issue when recording signal from the brain is the available room for sensing device placement. Since available room is limited, battery-less solutions are welcome. Also, AAL solutions to be developed should consider not only the sensing device, but also the entire supporting framework. This paper introduces a solution for long-term monitoring of intracranial pressure using a wireless microdevice and a wireless sensor network. This work introduces a solution to achieve an enough miniaturized pressure sensor, powered by a wireless link, and analyzes the suitability of a wireless sensor network to support the data dissemination.

Estimating the impact of adding sensor nodes to biomedical wireless sensor networks

Biomedical wireless sensor networks enable the development of real-time patient monitoring systems, either to monitor chronically ill persons in their homes or to monitor patients in step-down hospital units. However, due to the critical nature of medical data, these networks have to meet demanding quality of service requirements, ensuring high levels of confidence to their users. These goals depend on several factors, such as the characteristics of the network deployment area or the network topology. In such context, this work proposes a method to find the best network physical topology in order to maximise the quality of service provided by the network. The proposed method makes use of “virtual sensor nodes” to estimate the impact of adding real sensor nodes to the network in a specific location. Thus, assessing different locations, it is possible to find the best location to place the new sensor node while maximising the quality of service provided by the network. In particular, this work studies the f...