Insusceptibility Measurement And Analysis Approach Study Of The Ballistocardiogram Signal

The heart is the vital organ in body. Its working condition is an important index to evaluate whether the body is healthy or not, and could be assessed by detecting electrophysiological and pump function in clinic. However, cardiopath maybe sudden outburst, and cardiac function detecting method used in clinical will be failed to find this situation in time. So it is necessary to study a kind of cardiac function real-time monitoring device to detect abnormal situation and give cue.Heart pumping makes the force on the closely contact body support change, which can be recorded as ballistocardiogram(BCG). BCG signal contains working condition of cardiovascular system and could be easy acquired without any sensors attaching to body. Insusceptibility measurement approach based on BCG signal could gain heart working status in the condition that the subject can't feel measuring status, so it is suitable for long-time heart monitoring without psychological burden. According to these advantages, a new kind of BCG signal insusceptibility measurement approach is proposed and studied by experiments, and the main works are as follows:Physiological basis of cardiac systolic and diastolic activity is described, and generation principle of BCG signal is indicated. After analyzing the outer body model, inner body model and direct model, an improved direct modeling method of BCG signal based on inner body analysis is proposed and studied in simulation.According to its measurement principle, a new sitting BCG signal insusceptibility measurement approach is proposed, and the detecting device is designed and realized. Sensor circuit is a home chair refitted by resistance strain weighing sensors used in electronic weight scale. Signal processing circuit with high gain and low noise is composed of former amplifier with feedback circuit, filter circuit and main amplifier. The dynamic and static characteristics of the device are verified by experiment. The results show that the device is suitable for measuring BCG signal. In practical testing, the proposed device gains synchronous BCG signal with cardiac activity, so the design is reasonable.BCG signal is defined as a kind of determinate vibration signal with randomicity based on its characters. Time domain preprocessing method is used to removing trend trem and smoothing the BCG signal directly gained from the designed device, and the autocorrelation function proves the BCG signal is periodic and has noise irrelevant to actual BCG signal. The auto-power spectrum and 1/3 octave spectrum is calculated to gain frequency range of BCG signal.Translation invariant and adaptive least mean square de-noising method based on orthogonal wavelet transform are studied. After discussing wavelet base choice principle and improving a kind of wavelet decomposition scale selection method, the wavelet base and the decomposition scale suitable for BCG signal is selected. Then an improved threshold function is proposed and applied to BCG signal translation invariant de-noising with estimating the noise variance. The reason why orthogonal wavelet transform could improve the convergence rate of least mean square algorithm is discussed and a kind of order determination method of adaptive filter is proposed. Then the method is used to de-noising BCG signal and realizing its least mean square de-noising.An adaptive time-frequency empirical mode decomposition based on joint time-frequency distribution is studied. The principle and limitations of empirical mode decomposition and time-frequency empirical mode decomposition based on discrete cosine transform is discussed. Then the approach is proposed that signal component is adaptively extracted using joint time-frequency distribution and decomposed by empirical mode decomposition method. The approach solves the problem that empirical mode decomposition is unsuitable to process the signals with identical frequency content at different times and overcomes the disadvantages that time-frequency empirical mode decomposition based on discrete cosine transform can't choose reconstructing components adaptively. The proposed approach is applied to de-noising BCG signal based on filter principle of empirical mode decomposition.Characters are extracted from de-nosing BCG signal. An adaptive J wave extracting method is proposed and used to extracting J wave amplitude, width of IJK complex wave, and other time domain characters. BCG signal is proved a feasible method to measure cardiac cycle compared with ECG signal, from the statistical view. An improved time-frequency characters extracting method is proposed based on time frequency moments singular value decomposition. BCG signal is segmented by JJ interval and singular values of matrixes, which are composed of 1-4 order time and frequency domain statistical moments calculated from each signal segment separately, are extracted as time-frequency characters. The experiment results show that, the characters gained by this method make the difference significant between abnormal and normal heart activity, which verify the validity of the method. Dynamic characters of BCG signal are extracted based on phase space reconstruction, recurrence plot and recurrence quantification analysis. The experiment results show that, the characters is sensitive to anomalies of heart activity.The signal acquisition circuit is designed, and the BCG signals of long time and containing artificial disturbance gained by detecting device respectively are serially outputted to computer. Breathe signal and cardiac cycle is gained from long time BCG signal, and partial J wave positions are determined from the no disturbance part of the artificial disturbance BCG signals according to proposed approaches.