The microsoft DirectX technique is utilized to achieve the display of fast moving waveforms with high resolution and full screen in the environment of WindowsXP. The waveforms can move fluently under the resolution of 1280 x 1024 with the fastest speed of 1 m/s without any dither.
Signal Processing, Computer-Assisted ; Software

According to the biomedical signal characteristics, a new biomedical signal processing toolkit is developed. The toolkit is programmed by Java. It is used in basic digital signal processing, random signal processing and etc. All the methods in toolkit has been tested, the program is robust. The feature of the toolkit is detailed explained, easy use and good practicability.
Signal Processing, Computer-Assisted ; Software

OBJECTIVEDue to random sampling of non-adaptive, high-quality reconstruction of the original signal, one-dimensional non-stationary multi-channel EEG signal can be achieved automatic detection and analysis.

METHODSA new multicomponent redundant dictionaries with the atoms of the Gaussian function and its first and second derivatives was built in the paper, and reconstructed signal base on compressed sensing measurement model.

RESULTSThe selected dictionary atoms can more effectively match the EEG signals in a variety of transient characteristics of the waveform, allowing the formation of EEG signal is more sparse matching pursuit decomposition. With the theory based on compressed sensing signal sampling, only half of the original signal with different sample size can be used to reconstruct the original signal quality, the important instantaneous features of the waveform can well be maintained.

CONCLUSIONSignal sampling based on the theory of compressed sensing contains enough information of the original signal, using the prior conditions of EEG signals (or compressibility) sparsity, high-dimensional signal and original image can be reconstructed through a certain decoding of linear or nonlinear model.

In order to deal with the disadvantages in ECG waveform detection by wavelet harr transform at level 3, we put forward a new set of algorithm which combines wavelet transform (WT) and morphological peak and valley detection. The combination algorithm can make up the limitation in detecting ECG swing by WT and improve the accuracy of ECG waveform detection effectively.
Algorithms ; Electrocardiography ; Humans ; Signal Processing, Computer-Assisted

This article add mode control module to the phased-array using digital sampling technology which achieved a phase accuracy of 3.75 degrees, making phase, phased signal duration, interval for continuous signal and repeat times pre-configured before the out put of phased signal, to realize the precise timing of phased signal. Experiments indicate that the output of phased signal modulated by mode control can reach the timing precision of 0.48 micros and will not affect the original phase control function t. In addition it can realize intermittent therapy mode which can reduce the injury of non-focal areas caused by ultrasound energy.
Equipment Design ; Signal Processing, Computer-Assisted ; Transducers

The basic theory of Higher Order Spectral Analysis and the most generally used Bispectrum are introduced in the paper. By certain experiments of EEG signal acquisition and bispectrum analysis, it is showed that the Higher Order Spectrum has an advantage over power spectrum, which is based on Second Order Statistics, in processing non-linear signal and restraining Gauss noise signal.
Electroencephalography ; methods ; Signal Processing, Computer-Assisted

In this paper, we using Mexican-hat wavelet transform to detect characteristic points of ECG signal based on the characteristic points corresponding with the extremes of Mexican-hat wavelet transform. It offers a new detection method of ECG signal analysis. This method is simple and it is proved to be accurate and reliable. The correct rate of QRS detection rate examined by the MIT-BIT arrhythmia database rises up to 99.9%.
Algorithms ; Electrocardiography ; Humans ; Signal Processing, Computer-Assisted

In an ECG auto-analysis system, correct QRS detection is most important. For this detection there are several methods, such as derivative-based algorithms, filter-bank methods and wavelet based methods and neural network approaches, but there is no single method that is extensively used. These methods are compared and analyzed in this paper.
Algorithms ; Electrocardiography ; Humans ; Signal Processing, Computer-Assisted

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.
Anesthesia ; methods ; Humans ; Signal Processing, Computer-Assisted

We proposed a research of a heart sound envelope extraction system in this paper. The system was implemented on LabVIEW based on the Hilbert-Huang transform (HHT). We firstly used the sound card to collect the heart sound, and then implemented the complete system program of signal acquisition, pretreatment and envelope extraction on LabVIEW based on the theory of HHT. Finally, we used a case to prove that the system could collect heart sound, preprocess and extract the envelope easily. The system was better to retain and show the characteristics of heart sound envelope, and its program and methods were important to other researches, such as those on the vibration and voice, etc.
Heart Sounds ; Humans ; Signal Processing, Computer-Assisted