The Design of Wearable Sub-Health Monitoring System

2015 ◽  
Vol 727-728 ◽  
pp. 670-674
Author(s):  
Hao Ma ◽  
Xiu Juan Fan ◽  
Xiao Yun Yin
Keyword(s):  
Neural Network ◽  
Monitoring System ◽  
Health Monitoring ◽  
Bp Neural Network ◽  
Health Data ◽  
Physiological Signals ◽  
State Assessments ◽  
Accurate Calculation ◽  
Health Monitoring System ◽  
Scientific Decision

This paper describes a wearable technology sub-health monitoring system based on the description of the system and physiological signals by Zigbee module sub-health data collection, acquisition and transfer process, as well as PC using BP neural network for sub-health algorithm model state assessments; simulation tests to verify the rationality and practicality of the system. In short, the system has a simple and accurate calculation of benefits for sub-health can quickly assess and provide comprehensive, objective and scientific decision-making reference, extensive prospects.

scholarly journals Developing a Public Health Monitoring System in a War-torn Region: A Field Report From Iraqi Kurdistan

2019 ◽  
Vol 14 (5) ◽  
pp. 620-622
Author(s):  
Stefania Moramarco ◽  
Faiq B. Basa ◽  
Haveen H. Alsilefanee ◽  
Sivar A. Qadir ◽  
Leonardo Emberti Gialloreti
Keyword(s):  
Public Health ◽  
Health System ◽  
Monitoring System ◽  
Health Monitoring ◽  
Electronic System ◽  
Health Data ◽  
Health Monitoring System ◽  
Iraqi Kurdistan ◽  
Epidemiological Monitoring ◽  
Field Report

ABSTRACTWars, terrorism, and embargos destroyed facilities and shattered the public health system of Iraq. Today, there is limited documented knowledge about the health situation of the Iraqi population, particularly because health data are not systematically collected. Therefore, the capacity of the health system to address the major health problems of the population is considerably reduced. This report describes the implementation, started in 2015, of an electronic system for epidemiological monitoring and health surveillance, designed to collect and manage health care data in Iraqi Kurdistan. The aim of the program is to network all of the main health centers and hospitals of the region, then of the whole country, and to train medical and administrative staff in the management and analysis of health data. In countries recovering from war, a functioning health monitoring system is essential in guiding the development of appropriate public health interventions, a key instrument to prepare the health system to respond to future emergencies.

scholarly journals Simplified-Boost Reinforced Model-Based Complex Wind Signal Forecasting

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Qiushuang Lin ◽  
Chunxiang Li ◽  
Chao Wu
Keyword(s):  
Neural Network ◽  
Structural Health Monitoring ◽  
Convolutional Neural Network ◽  
Monitoring System ◽  
High Precision ◽  
Health Monitoring ◽  
Wind Engineering ◽  
Stage Model ◽  
Health Monitoring System ◽  
Non Gaussian

Wind signal forecasting has become more and more crucial in the structural health monitoring system and wind engineering recently. It is a challenging subject owing to the complicated volatility of wind signals. The robustness and generalization of a predictor are significant as well as of high precision. In this paper, an adaptive residual convolutional neural network (CNN) is developed, aiming at achieving not only high precision but also high adaptivity for various wind signals with varying complexity. Afterwards, reinforced forecasting is adopted to enhance the robustness of the preliminary forecasting. The preliminary forecast results by adaptive residual CNN are integrated with historical observed signals as the new input to reconstruct a new forecasting mapping. Meanwhile, simplified-boost strategy is applied for more generalized results. The results of multistep forecasting for five kinds of nonstationary non-Gaussian wind signals prove the more excellent adaptivity and robustness of the developed two-stage model compared with single models.

Opportunities Lost: Political Interference in the Systematic Collection of Population Health Data During and After the 2003 War in Iraq

2020 ◽  
pp. 1-7
Author(s):  
Frederick M. Burkle
Keyword(s):  
Public Health ◽  
Monitoring System ◽  
Health Monitoring ◽  
Health Data ◽  
Data Systems ◽  
Mortality And Morbidity ◽  
Health Monitoring System ◽  
Public Health Monitoring ◽  
Political Interference ◽  
Field Report

ABSTRACT The review of the article, “Developing a Public Health Monitoring System in a War-torn Region: A Field Report from Iraqi Kurdistan,” prompted the writing of this commentary. Decisions to implement health data systems within Iraq require exploration of many otherwise undisclosed or unknown historical facts that led to the politicization of and ultimate demise of the pre-2003 Iraq war systematic health data monitoring system designed to mitigate both direct and indirect mortality and morbidity. Absent from the field report’s otherwise accurate history leading up to and following the war is the politically led process by which the original surveillance system planned for the war and its aftermath was destroyed. The successful politicization of the otherwise extensively planned for public health monitoring in 2003 and its legacy harmed any future attempts to implement similar monitoring systems in succeeding wars and conflicts. Warring factions only collect military casualty data. The field report outlines current attempts to begin again in building a systematic health monitoring system emphasizing it is the “only way to manage the complex post-war events that continue to lead to disproportionate preventable mortality and morbidity.”

A Neural Network-Based System for Bridge Health Monitoring

2012 ◽  
Vol 452-453 ◽  
pp. 557-563 ◽  
Author(s):  
Tzu Kang Lin ◽  
Ming Chih Huang ◽  
Jer Fu Wang
Keyword(s):  
Neural Network ◽  
Transfer Function ◽  
Monitoring System ◽  
Health Monitoring ◽  
Network Technology ◽  
Health Monitoring System ◽  
Bridge Health Monitoring ◽  
Analytical Results ◽  
Neural Network Technology

A bridge health monitoring system based on neural network technology is proposed in this paper. Two major ground excitations recorded in Taiwan were used to establish the NARX-based system. Analytical results from different methods including transfer function, ARX-based model, and the proposed neural network-based system were used to evaluate the efficiency in health monitoring. The result shows that the proposed system can be used successfully with superior advantages after major earthquakes for bridge health monitoring.

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