Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Aug 2005
[Data reconstruction algorithm on echo-planar magnetic resonance spectroscopic imaging].
When a conventional phase-encoding magnetic resonance spectrascopic imaging(MRSI) method is in use, the data acquisition is very time consuming and thus it is not well accepted in clinical settings. Echo planar spectroscopic imaging (EPSI) technology has been applied for rapid acquisition of MRSI data. It significantly reduces scan time by simultaneously encoding the spectral dimension and the spatial dimension. ⋯ Fast Fourier transform (FFT) is applied in odd echoes and even echoes respectively and then shift method is used to combine them together. For the kx dimension, the data are unevenly sampled and have to be interpolated onto a Cartesian grid before FFT is applied. For the phase-encoding dimension (ky), the Fourier transform can be readily done with FFT since the data are evenly spaced.
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Aug 2005
[Experimental study of excitation of peripheral nerves in transverse electric field stimulation].
The classical cable function has been used to represent the response of peripheral nerves stimulated by external parallel electric field. Experiments show that peripheral nerves can be activated by perpendicular electric field induced by magnetic pulses, indicating that the activation mechanism needs to be thoroughly investigated. Several excitation properties of peripheral nerves in transverse-field were explored in the present paper. ⋯ The relation between stimulation threshold and stimulation duration was researched with sciatic nerves from toad in vitro. The experimental results verify that the modified cable function is much efficient than the classical cable function. The research will improve the nerve magnetic stimulating technique and be beneficial to further application.
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Aug 2005
[Pulse pressure and mean pressure relationship of intracranial pressure and lumbar cerebrospinal fluid pressure].
Intracranial pressure fluctuates due to heart beat, respiration, neuro-regulation, etc. Traditional intracranial pressure study focuses on the static pressure and related factors, putting emphasis on mean intracranial pressure, while paying little attention to the pulse components. This study was composed of two parts: animal experiment and theoretical analysis. ⋯ The same result was obtained in the lumbar cerebrospinal fluid pressure. Therefore, the lumbar cerebrospinal fluid pressure is consistent with the intracranial pressure. Intracranial pulse pressure is in linear relationship with mean pressure, and the slope of their linear relationship predicts the perform of intracranial autoregulation.
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Feb 2005
[The solving and simulation of cable equation under the stimulation of point electrical source].
The character of the membrane of fiber can be simulated by nonpower RC network on condition that the offset of distance between the transmembrane potential of unmyelinated nerve fiber and the resting potential of nerve fiber cell is small enough. Thus, it is possible to found the successive cable equation with external stimulation under subthreshold linear state. ⋯ In this paper are reported the method of integral transform and the analytical expression of cable equation under the stimulation of point electrical source firstly. And at the same time, computer-aided simulation of transmembrane potential of nerve fiber and analysis of the possibility of activating action potential are presented.
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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Feb 2005
[Determination of optimal complexity for long ECG sequence].
In this article is reported a study on the optimal complexity of the long electrocardiogram (ECG) signal. At first, the original signal sequence was symbolized, then its complexity was calculated by Lempel-Ziv algorithm, and different factors of the complexity were discussed, and three different kinds of ECG signals, i.e., normalcy, angina and myocardial infarction, were studied. The results indicate that the optimal threshold-value to symbolize the original signal and the optimal signal length are two main factors that affect the complexity value, and the optimal complexity value can effectively distinguish normal ECG and patients' ECG.