Nonlinear Dynamics Of The Development Of The Fetal Heart Monitor And Heart Rate Signal Analysis

It is convenient to diagnose the state of fetus in the womb by means of examining the heart beat rate and heart beat rate variability. The methods of traditional fetal monitor are based on linear and statistical analysis, so the multichannel fetal monitor comes forth under the endeavor of our group. At first, signals are inputted into computer through PC-6360. In order to collect the signals, a control interface of Visual Basic is completed. This control interface can accomplish real-time display and establish a file of case, at the same time, the numerical value of heart beat rate is sent to display circuit of fetal monitor, the synchronous display realized. If the heart beat rate is out of the normal scope, the lamps of alarm will be started. Then we will do some statistical and nonlinear analysis. We hope that we could approve a uniform criterion to the doctor by the analysis of all kinds of cases.In this paper, signals of heart beat rate are collected from 15 healthy youth, all of them are between 20 to 30 years old, the sampling time is about 30 minutes. From the results of linear analysis, it can be found that most of the people's heart beat rate centralize at 70-80 times/min. It's power spectrum is a continuous spectrum with a pinnacle, this shows that the heart beat rate signal obeys certain dynamical law. We reconstructed the phase space and calculated the nonlinear parameters such as correlation dimension, the largest Lyapunov exponent, approximate entropy, and L-Z complexity of the data. It can be conclud from the results that the reconstruction of heart beat rate signal is strange, its correlation dimension is between 5 to 7 and have the character of fractal dimension, its largest Lyapunov exponent is larger than zero, its approximate entropy and L-Z complexity are obviously differ from noise. We can draw a conclusionfrom all above: the heart beat rate signal isn't simple noise, it is high dimensional chaos obeys certain dynamical law. The results of recurrence plot analysis and recurrence quantification analysis approve the conclusion above.