Search results for "Computer science"
showing 10 items of 22367 documents
A Stochastic Routing Algorithm for Distributed IoT with Unreliable Wireless Links
2016
Punctual and reliable transmission of collected information is indispensable for many Internet of Things (IoT) applications. Such applications rely on IoT devices operating over wireless communication links which are intrinsically unreliable. Consequently to improve packet delivery success while reducing delivery delay is a challenging task for data transmission in the IoT. In this paper, we propose an improved distributed stochastic routing algorithm to increase packet delivery ratio and decrease delivery delay in IoT with unreliable communication links. We adopt the concept of absorbing Markov chain to model the network and evaluate the expected delivery ratio and expected delivery delay …
A validity and reliability study of Conditional Entropy Measures of Pulse Rate Variability
2019
In this work, we present the feasibility to use a simpler methodological approach for the assessment of the short-term complexity of Heart Rate Variability (HRV). Specifically, we propose to exploit Pulse Rate Variability (PRV) recorded through photoplethysmography in place of HRV measured from the ECG, and to compute complexity via a linear Gaussian approximation in place of the standard model-free methods (e.g., nearest neighbor entropy estimates) usually applied to HRV. Linear PRV-based and model-free HRV-based complexity measures were compared via statistical tests, correlation analysis and Bland-Altman plots, demonstrating an overall good agreement. These results support the applicabil…
Language complexity in on-line health information retrieval
2020
The number of people searching for on-line health information has been steadily growing over the years so it is crucial to understand their specific requirements in order to help them finding easily and quickly the specific in-formation they are looking for. Although generic search engines are typically used by health information seekers as the starting point for searching information, they have been shown to be limited and unsatisfactory because they make generic searches, often overloading the user with the provided amount of results. Moreover, they are not able to provide specific information to different types of users. At the same time, specific search engines mostly work on medical li…
ULearn: Personalized Medical Learning on the Web for Patient Empowerment
2019
Abstract. Health literacy constitutes an important step towards patient empowerment and the Web is presently the biggest repository of medical information and, thus, the biggest medical resource to be used in the learning process. However, at present web medical information is mainly accessed through generic search engines that do not take into account the user specific needs and starting knowledge and so are not able to support learning activities tailored to the specific user requirements. This work presents “ULearn” a meta engine that supports access, understanding and learning on the Web in the medical domain based on specific user requirements and knowledge levels towards what we call …
Teaching clinical reasoning and decision-making skills to nursing students: Design, development, and usability evaluation of a serious game
2016
Background\ud \ud Serious games (SGs) are a type of simulation technology that may provide nursing students with the opportunity to practice their clinical reasoning and decision-making skills in a safe and authentic environment. Despite the growing number of SGs developed for healthcare professionals, few SGs are video based or address the domain of home health care.\ud \ud Aims\ud \ud This paper aims to describe the design, development, and usability evaluation of a video based SG for teaching clinical reasoning and decision-making skills to nursing students who care for patients with chronic obstructive pulmonary disease (COPD) in home healthcare settings.\ud \ud Methods\ud \ud A prototy…
Usability and acceptability assessment of an empathic virtual agent to prevent major depression
2016
In Human-Computer Interaction, the adaptation of the content and the way of how this content is communicated to the users in interactive sessions is a critical issue to promote the acceptability and usability of any computational system. We present a user-adapted interactive platform to identify and provide an early intervention for symptoms of depression and suicide. In particular, we describe the work performed to assess users' system acceptability and usability. An empathic Virtual Agent is the main interface with the user, and it has been designed to generate the appropriate dialogues and emotions during the interactions according to the detected user's specific needs. This personalizat…
A Distributed Multi-Authority Attribute Based Encryption Scheme for Secure Sharing of Personal Health Records
2017
Personal health records (PHR) are an emerging health information exchange model, which facilitates PHR owners to efficiently manage their health data. Typically, PHRs are outsourced and stored in third-party cloud platforms. Although, outsourcing private health data to third-party platforms is an appealing solution for PHR owners, it may lead to significant privacy concerns, because there is a higher risk of leaking private data to unauthorized parties. As a way of ensuring PHR owners' control of their outsourced PHR data, attribute based encryption (ABE) mechanisms have been considered due to the fact that such schemes facilitate a mechanism of sharing encrypted data among a set of intende…
Cost-Effective eHealth System Based on a Multi-Sensor System-on-Chip Platform and Data Fusion in Cloud for Sport Activity Monitoring
2018
eHealth systems provide medical support to users and contribute to the development of mobile and quality health care. They also provide results on the prevention and follow-up of diseases by monitoring health-status indicators and methodical data gathering in patients. Telematic management of health services by means of the Internet of Things provides immediate support and it is cheaper than conventional physical presence methods. Currently, wireless communications and sensor networks allow a person or group to be monitored remotely. The aim of this paper is to develop and assess a system for monitoring physiological parameters to be applied in different scenarios, such as health or sports.…
Hybrid Deep Shallow Network for Assessment of Depression Using Electroencephalogram Signals
2020
Depression is a mental health disorder characterised by persistently depressed mood or loss of interest in activities resulting impairment in daily life significantly. Electroencephalography (EEG) can assist with the accurate diagnosis of depression. In this paper, we present two different hybrid deep learning models for classification and assessment of patient suffering with depression. We have combined convolutional neural network with Gated recurrent units (RGUs), thus the proposed network is shallow and much smaller in size in comparison to its counter LSTM network. In addition to this, proposed approach is less sensitive to parameter settings. Extensive experiments on EEG dataset shows…
Life Cycle Energy Consumption and Carbon Dioxide Emissions of Agricultural Residue Feedstock for Bioenergy
2021
The depletion of fossil fuels and climate change concerns are drivers for the development and expansion of bioenergy. Promoting biomass is vital to move civilization toward a low-carbon economy. To meet European Union targets, it is required to increase the use of agricultural residues (including straw) for power generation. Using agricultural residues without accounting for their energy consumed and carbon dioxide emissions distorts the energy and environmental balance, and their analysis is the purpose of this study. In this paper, a life cycle analysis method is applied. The allocation of carbon dioxide emissions and energy inputs in the crop production by allocating between a product (g…