Research of Electronic Sphygmomanometer Intelligent Aeration Based on Pulse Wave Identification / 中国医疗器械杂志

Through various common domestic and foreign electronic sphygmomanometers to test blood pressure, we find that when measuring high blood pressure or low blood pressure, there is a mismatch between the maximum inflation pressure and the blood pressure measurement, which often results in repeatedly inflating and deflating as well as the problem of high inflation pressure. In order to solve these problems and find a suitable maximum inflation pressure, two intelligent pneumatic solutions based on identifying of pulse wave are suggested and 700 groups of blood pressure experiments are done, then the two solutions are verified by experiments. The experiment proved that these solutions proposed have good stability and accuracy, they can solve the problems appeared in measuring blood pressure effectively, at the same time, the second solution that estimate the maximum inflation pressure during inflation is considered as the best one.

Anesthesia in the Signal Processing Methods / 中国医疗器械杂志

Anesthesia plays an essential role in clinical operations. Guiding anesthesia by EEG signals is one of the most promising methods at present and it has obtained good results. The analysis and process of the EEG signals in anesthesia can provide clean signal for further research. This paper used variance threshold method to remove the mutation fast and large interfering signals; and used notch filter to remove frequency interference, smoothing filter to remove baseline drift and Butterworth low-pass filter to remove high frequency noise at the same time. In addition to this, the translation invariant wavelet method to remove interference noise on the signals which was after the classical filter and retained non-stationary characteristics was used to evaluate parameter calculation. By comparing the calculated parameters from treated signal using this paper's methods and untreated signal and standard signal, the standard deviation and correlation has been improved, particularly the major parameters BetaR, which provides better signal for integration of multi-parameter to evaluate depth of anesthesia index for the latter.