In the last years the area of health monitoring has grown significantly, attracting the attention of both academia and commercial sectors. At the same time, the availability of new biomedical sensors and suitable network protocols has led to the appearance of a new generation of wireless sensor networks, the so-called wireless body area networks. Nowadays, these networks are routinely used for continuous monitoring of vital parameters, movement, and the surrounding environment of people, but the large volume of data generated in different locations represents a major obstacle for the appropriate design, development, and deployment of more elaborated intelligent systems. In this context, we present an open and distributed architecture based on a multiagent system for recognizing human movements, identifying human postures, and detecting harmful activities. The proposed system evolved from a single node for fall detection to a multisensor hardware solution capable of identifying unhampered falls and analyzing the users' movement. The experiments carried out contemplate two different scenarios and demonstrate the accuracy of our proposal as a real distributed movement monitoring and accident detection system. Moreover, we also characterize its performance, enabling future analyses and comparisons with similar approaches.
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http://dx.doi.org/10.1155/2015/192454 | DOI Listing |
ISA Trans
January 2025
College of Mechanical and Vehicle Engineering, Hunan University, Changsha, 410082, Hunan, China. Electronic address:
Approximation-free control effectively addresses uncertainty and disturbances without relying on approximation techniques such as fuzzy logic systems (FLS) and neural networks (NNs). However, singularity problems-where signals exceed preset boundaries under dynamic operating conditions-remain a challenge. This paper proposes an improved approximation-free control (I-AFC) method for the multi-agent system, which introduces a novel singularity compensator, providing a low-complexity design with exceptional adaptability while reducing the risk of singularity issues under changing working conditions (random initial values, system parameter variations, and changes in topology graph and followers' dynamics).
View Article and Find Full Text PDFJ Biomed Inform
January 2025
ITMO University, Saint Petersburg, Russia. Electronic address:
The optimization in the ambulance dispatching process is significant for patients who need early treatments. However, the problem of dynamic ambulance redeployment for destination hospital selection has rarely been investigated. The paper proposes an approach to model and simulate the ambulance dispatching process in multi-agent healthcare environments of large cities.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Medical Information Department, Civil Hospices of Lyon, Lyon, France.
J Med Internet Res
January 2025
School of Computer Science, University of Technology Sydney, Sydney, Australia.
The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during public health emergencies, capable of reaching billions through familiar digital channels. This paper explores the utility and implications of generalist conversational artificial intelligence (CAI) advanced AI systems trained on extensive datasets to handle a wide range of conversational tasks across various domains with human-like responsiveness. The specific focus is on the application of generalist CAI within messaging services, emphasizing its potential to enhance public health communication.
View Article and Find Full Text PDFSci Rep
January 2025
School of Information and Communication Engineering, Hainan University, Haikou, 570228, China.
This paper investigates regional proportional-integral-derivative consensus of switched positive multi-agent systems with multiple equilibria. A distributed proportional-integral-derivative control protocol is developed by integrating the communication protocol, agent state, and consensus error. A novel switched positive consensus error system is established and analyzed using copositive Lyapunov functions.
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