Vascular Wall Dynamic Information Detection And Diagnosis System Based On Remote Virtual Instrument Technique

BackgroundThe researches of modern medical found that there are tight link between incidence of cardiovascular disease with the flexibility function and geometric shape of blood vessel. Once a lesion is formed in blood vessel, it is bound to change the mechanical elasticity and geometric shape of blood vessel. Therefore, the early detection of human blood vessel elastic function has become one of the hot spots in the area of vascular diseases detection. Although there are a lot of methods to detect the vessel wall elastic property at present, they have obvious deficiencies.ObjectivesBased on previous study, this study has focused on the design of new method to detect and treat VWDI and the design of detection and analysis system according to this detection and treatment method. In this study, spectral analysis technique will be applied to the analysis of vascular wall dynamic information so that a new method of analysis of vascular wall dynamic information is proposed. The new method lay a theoretical and clinical application foundation for our further works which determine the research methods of vascular wall elastic function by a devil of clinical experiment, determine the detection index and its statistical significance and reference range.MethodsVirtual instrument technology and the theory of VWDI extraction were used to design the method of VWDI detection. Datasocket technique was used to transmit VWDI remotely. Filtering method of PDWVW information was designed base on the design idea of FIR filter. Base on analysis theory of power spectrum, analysis method of VWDI was proposed.ResultsThe remote transmission of VWDI and the remote control of acquisition process were realized. Power line interference in PDWVW information was filtered out. Typical oscillogram of PDWVW information and speed wave were gained from normal and vascular patients. The result of signal power spectrum analysis showed that all of the signal parameters deference have statistics significance between the normal and vascular patients groups except the parameter G of signal C and G.ConclusionsIn this research, we use common acquisition card collect data on the LabVIEW platform. After detection of VWDI in a certain amount of population, we found that the detection system based on method we proposed could detect VWDI accurately and scientifically. The analysis results were concluded that the deference of vascular wall pressure displacement wave and its speed wave between the normal and vascular patients groups have statistics significance.