0000000000393782
AUTHOR
Carlos Carrascosa
Psychological Influence of Double-Bind Situations in Human-Agent Interaction
This paper presents a new approach to integrate artificial intelligence in virtual environments. The system presented deals in a separated way the visualization and intelligence modules, applying in this last case a distributed approach (multi-agent systems) so that scalable applications may be built. Therefore, it is necessary to define agent architectures that allow agents to be integrated in the VW. Thus, a designer is abstracted from the peculiarities of interacting with a virtual environment. There is a first prototype of the framework using JADE as the supporting multi-agent systems platform.
An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks
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…
Vascular Contraction Model Based on Multi-agent Systems
This paper presents a first approximation to the simulation of vascular smooth muscle cell following an agent-based simulation approach. This simulation incorporates mathematical models that describe the behaviour of these cells, which are used by the agents in order to emulate vascular contraction. A first tool, implemented in Netlogo, is provided to allow the performance of the proposed simulation.