Synchronous Acquisition And Application Based On Multi-information Of Pulse Images And ECG Signals

Sub-health state is defined as a critical state between the health and diseases. It is a kind of physiological state that appears with vigor reducing, adaptive capacity failing in various degrees, although there isn't any identified disease in organism. Sub-health doesn't have the transformation of the health status, but also have the direction of a transformation to bad for the further development of various diseases, seriously affecting people's health. The performances of sub-health are very complex and its diagnosis mainly depends on a number of biochemical indicators and survey, so far there is no access to recognized standards at home and abroad.Pulse signal and ECG signal are two common physiological signals. They both contain a lot of wealth, physiological and pathological information that are closely related to human health, and they can also transmit and peep the changes of function inside the body. This paper hold the signal processing point of view, which identifying the sub-health state through the analysis of pulse and ECG signal, and the experiments verify the feasibility and effectiveness. This paper mainly includes the following:Firstly, based on the research status, this paper analyzes the feasibility of evaluating sub-health state by using the information from pulse and ECG signal.Secondly, the paper set up the pulse image and ECG signal of multi-information synchronous acquisition system by the use of pulse image sensor and MP425 data acquisition card. The camera can export pulse signal via the camera interface circuit when the camera is started. This pulse signal is taken as a synchronous signal which will connect with external trigger terminal of the data acquisition card, achieving the starting of two actions at the same time. Sub-health experiments are designed to complete the collection of pulse image and ECG signal of the multi- information synchronization.Then, the method of dynamic image processing technique is used to obtain pulse signal from the pulse image, which can reflect the pulse signal actually and completely. For the noise in the data collection process, wavelet transform is selected to denoise the signal to obtain cleaner signal. Based on the introduction of signal feature extraction method, features of pulse ECG signal are extracted by the way of time-frequency domain analysis and nonlinear analysis methods.Finally, the dimension of these features was reduced by utilizing principal component analysis (PCA) method for removing the redundant information between them. And the sub-health state classification is realized by using improved linear Discriminant Analysis (LDA) algorithm. Experimental results show that the extracted features can effectively reflect the changes of pulse and ECG signal. And the LDA algorithm in the identification of sub-health state achieves satisfactory results. The results also show that the method based on features of pulse and ECG signals is feasible for evaluating the sub-health state.