The Research On The Separation Of The Heartbeat And Respiratory Signals Detected By Bioradar

Bioradar is a new concept of radar technology combined with the biomedical engineering technique, which can detect the life parameters (such as respiratory and heartbeat signals) through clothing, bedclothes, pledget without any sensor or electrode touching the human subject. Since the detection is non-contact, long distance and without restriction, it has unusual significance in clinical application especially in military medicine. This method can be applied to some special clinical cases, such as to monitor the patients when sensors or electrodes are unsuitable for touching the skin. Those patients are usually in a condition of seriously burned, severely infected or badly wounded.However, there are still many crucial techniques to be solved to meet the requirements for practical use. First, the heartbeat signal can be well detected when the human subject held his or her breath. While the subject freely breathed, the heartbeat signal can't be detected. The reason is that the minute chest movement is caused not only by the heartbeat, but also by the interferences introduced by the respiration and the body movement. Therefore, an effective signal processing method should be applied to separate the respiratory and heartbeat signal in order to extract the heartbeat signal which has less energy than respiratory signal. Secondly, it's of great importance to find out the relationship between the two kinds of signals, which is the key point for us to choose a signal processing method. Taking into consideration of the nonlinear influence from the system and the uncertainty of the two signals, it's difficult for us to totally separate them by linear filtering. The nonlinear filtering method should also be considered. Thirdly, it has been proved that the life parameters detected by the bioradar are a kind of narrowband, semi periodicity and low amplitudes. And also the signal is characterized by low Signal Noise Ratio (SNR), strong randomness and usually converges towards low frequency portion. But by now the quantitative differences between groups and individuals haven't been studied in detail, which is necessary for the separation, when is practically applied in clinical.Taking into account of the problems discussed above, the study mainly involves the followings:1) Study on the correlation between the Ballistocardiogram (Heartbeat) signal in life detecting system and the Electrocardiograph signal The system is constructed which synchronously detects the electrocardiogram signals by the electrocardiograph and the ballistocardiogram signals by the non-contact life parameter detecting technology. Also, the detected signals are analyzed respectively in the time and frequency domain. The underlying clinical medicine usefulness of ballistocardiogram detected by the non-contact technology is approved, and the credible evidence for the succeeding signal analysis and the clinical application is provided.2) Analysis on the characteristics of the heartbeat signal detected by bioradar Due to the fact that the life signals are semi periodicity, strong randomness and dissimilarity, large quantities of experimental data are collected in different testing conditions. The data are also statistically compared, analyzed and summarized by the use of statistical parameters, such as correlation coefficients. The physiological basics, characteristics and study methods for ECG and cardiac sound are summed up. And the mechanisms study on the respiratory influence to heart is also introduced. Those are helpful for us to better understand the characteristics of the heartbeat signals.3) Extraction of the heartbeat signal based on the method of wavelet analysis Wavelet analysis and other non-steady signal processing method are contrasted in this part. The application of wavelet analysis to signal separation and the existent problems are also introduced. By the use of Sym8 wavelet basis function, the signal is decomposed to 5 levels and denoised. Finally, the separation results of wavelet method with or without FIR filtering method are contrasted by the parameter of SNR.4) Extraction of heartbeat signal based on the method of curve fitting It's taken on trial to collect the signal without preprocessing procedure of the hardware. This kind of mixed signal contains more information about heartbeat and respiration. By the use of the technique of cubic spline interpolation, the baseline wander is removed, which is mostly caused by respiration. The results have shown that compared with wavelet analysis, Curve Fitting method has advantages in dealing with the respiration signal which is in the form of baseline wander.The thesis obtained some results as follows:1) The application of wavelet analysis to the separation of heartbeat and respiration signals. And the existent problems are also pointed out. The necessity of FIR filtering method are approved. The results show that if only the level number of decomposition is fixed, FIR filtering can be left out. As a result of that, the operation will be simple.2) Curve fitting method is used to the separation.It has been shown that one of the mainly study aspect for bioradar is to concern the life status, which is to study the relationship between the detected life parameters and the activities of the living objects and its organs. As a result of the needs for medicine and other development for human, it's of great importance to solve the existent problems, which can make the technique of bioradar more widely used than before.