ABSTRACT
A new left ventricle segmentation method in two-dimensional echocardiography images is proposed. Image processing techniques combined with radial search and temporal information are used to extract the left ventricle boundary. Borders from sequential images are extracted using the proposed method, and a curve illustrating the area variation within a cardiac cycle is presented. Performance evaluation is performed by comparing the borders obtained from the presented method to those manually prescribed by a medical specialist. The new sequential radial search algorithm improved the border extraction from long-axis ultrasound images, specially the ones where the mitral valve was open. Segmentation errors due to low contrast were corrected.
Subject(s)
Algorithms , Artificial Intelligence , Echocardiography/methods , Heart Ventricles/diagnostic imaging , Image Interpretation, Computer-Assisted/methods , Pattern Recognition, Automated/methods , Ventricular Dysfunction, Left/diagnostic imaging , Humans , Image Enhancement/methods , Imaging, Three-Dimensional/methods , Reproducibility of Results , Sensitivity and Specificity , Subtraction TechniqueABSTRACT
The medical tracking of patients carried out from a distance by means of wireless technology, incorporating various sensors simultaneously connected to the body of an individual, can promote health in suitable time. This article proposes a simulator for the monitoring of human health. This prototype simulates the workings of a BSN (Body Sensor Network) functioning as a sensor (electrophysiological signal) that is to be monitored, which utilizes a strategy based on the concept of data fusion. This tool incorporates a policy of economizing energy which has as its main objective increasing the operating time of the system.
Subject(s)
Monitoring, Ambulatory/instrumentation , Signal Processing, Computer-Assisted , Computer Simulation , Humans , Monitoring, Ambulatory/methodsABSTRACT
A Body Sensor Network (BSN) must be designed to work autonomously. On the other hand, BSNs need mechanisms that allow changes in their behavior in order to become a clinically useful tool. The purpose of this paper is to present a new programming model that will be useful for programming BSN sensor nodes. This model is based on an intelligent intermediate-level compiler. The main purpose of the proposed compiler is to increase the efficiency in system use, and to increase the lifetime of the application, considering its requirements, hardware possibilities and specialist knowledge. With this model, it is possible to maintain the autonomous operation capability of the BSN and still offer tools that allow users with little grasp on programming techniques to program these systems.
Subject(s)
Computer Communication Networks/instrumentation , Diagnosis, Computer-Assisted/methods , Models, Theoretical , Monitoring, Ambulatory/instrumentation , Monitoring, Ambulatory/methods , Programming Languages , Software , Algorithms , Diagnosis, Computer-Assisted/instrumentation , Humans , Information Storage and Retrieval/methods , Software DesignABSTRACT
This work presents a new programming model for sensor networks embedded in the human body which is based on the concept of multi-programming application-oriented software. This model was conceived with a top-down approach of four layers and its main goal is to allow the healthcare professionals to program and to reconfigure the network locally or by the Internet. In order to evaluate this hypothesis, a benchmarking was executed in order to allow the assessment of the mean time spent in the programming of a multi-functional sensor node used for the measurement and transmission of the electrocardiogram.