ABSTRACT
Objective:According to the existing hospital static mixing method, the problem of dynamic allocation model for half a year period is put forward, in order to solve emergency equipment safe are deployed in a timely manner. Methods: The hospital can allocate all emergency equipment evaluation, grade and tabulation, according to the score for sorting, system of sorting table provides emergency center allocate use half a year. Results: According to the deployment of table realized in emergency equipment safety in time in case of major events are deployed and able to skillfully use effect. Conclusion: The use of emergency equipment dynamic allocation model can not only improve the social benefit of the hospital, and reduce the pressure of the functions of the hospital departments.
ABSTRACT
In order to discriminate normal and abnormal heart sounds accurately and effectively, a new method is proposed to analyze heart sounds, namely heart sound characteristic waveform (HSCW) method. Digital stethoscope is used to collect heart sound signals. The recorded data are transmitted to a computer by USB interface for analysis based on HSCW, which is extracted from an analytical model of single degree-of-freedom (SDOF). Furthermore, a case study on the normal and abnormal cardiac sounds is demonstrated to validate the usefulness and efficiency of the proposed HSCW method. Besides, in order to test the accuracy of discriminating normal and abnormal heart sounds, 40 normal and 20 abnormal heart sounds are collected and analyzed, the accuracy performances are achieved by 92.5% and 95.0%, respectively.
Subject(s)
Humans , Algorithms , Heart Auscultation , Methods , Heart Sounds , Physiology , Phonocardiography , Methods , Signal Processing, Computer-AssistedABSTRACT
This paper is composed with the cardiac sound measurement and analysis system for in-home use of heart abnormality monitoring. The heart sound acquiring system is composed of a traditional chest-piece, earphone, microphone, and IC recorder. The recorded data is transmitted to a computer by USB interface for analysis based on the cardiac sound characteristic waveform (CSCW) method, which is extracted from an analytical model of single degree-of-freedom (SDOF). Furthermore, the characteristic parameters [T1, T2, T11, T12] are defined by the time intervals between the crossed points of the CSCW and a threshold value (THV), which are related to the first sound and the second sound and are used for discriminating normal and abnormal heart sounds. Also, an easy-understanding graphical representation for these parameters is considered, so that, even for an inexperienced user, he or she is able to monitor his or her cardiac status easily. Finally, a case study on the abnormal/normal cardiac sounds is demonstrated to validate the usefulness and efficiency of this proposed system and the cardiac sound characteristic waveform method.