声电图在颞下颌关节杂音分析中的应用

关节杂音是颞下颌关节紊乱病主要临床症状之一,由于产生的机制不同,不同类型颞下颌关节病的杂音各有其不同的特点。经快速傅立叶转换转化为声电图后,可在声波的频率、振动幅度、持续时间等方面对关节杂音进行区分,从而使临床上关节杂音的分析和应用更为准确、客观。本文综述了颞下颌关节杂音的分类、特点、产生机制及声电图特点,并介绍了不同类型颞下颌关节病的声电图特点。

声电图在可复性颞下颌关节盘前移位诊断中的临床价值

目的研究可复性颞下颌关节(TMJ)盘前移位关节杂音的波形和声电图特点,探讨其临床应用价值。方法利用计算机系统记录,用K6-I软件分析健康人群、可复性关节盘前移位、不可复性关节盘前移位、骨关节病的TMJ杂音声电图特点,并观察利用声电图辅助诊断可复性TMJ盘前移位的灵敏度和特异度。结果在可复性关节盘前移位关节杂音的声电图中反复出现一种波形,在健康TMJ、不可复性关节盘前移位、骨关节病TMJ杂音中未出现或很少出现该波形。利用声电图辅助诊断TMJ盘前移位的灵敏度为77·2%,特异度为93·3%。结论这种波形可能是可复性关节盘前移位关节杂音的特征波形,声电图检查可能是一种临床辅助诊断TMJ盘前移位的新方法。

无症状颞下颌关节的关节杂音声电图研究

目的探讨无症状颞下颌关节（TMJ）的关节杂音特点。方法利用K6-Ⅰ系统记录并分析42侧无症状的TMJ在下颌运动时的关节杂音，研究杂音声电图的波形、频率范围、峰值频率及振幅。结果42侧无症状的TMJ中有25侧在下颌运动时产生关节杂音，根据杂音的声电图波形、频率范围、峰值频率及振幅等，可将TMJ杂音分为4种类型。结论无临床症状的TMJ在下颌运动时可产生杂音，主要分为4种不同的类型。

Cardiac evaluation of liver transplant candidates

Physicians previously thought that heart disease was rare in patients with end stage liver disease. However, recent evidence shows that the prevalence of ischemic heart disease and cardiomyopathy is increased in transplant candidates compared to most other surgical candidates. Investigators estimate that up to 26% of all liver transplant candidates have at least one critical coronary artery stenosis and that at least half of these patients will die perioperatively of cardiac complications. Cardiomyopathy also occurs in greater frequency. While all patients with advanced cardiac disease have defects in cardiac performance, a larger than expected number of patients have classical findings of dilated, restrictive and hypertropic cardiomyopathy. This may explain why up to 56% of patients suffer from hypoxemia due to pulmonary edema following transplant surgery. There is considerable controversy on how to screen transplant candidates for the presence of heart disease. Questions focus upon, which patients should be screened and what tests should be used. This review examines screening strategies for transplant candidates and details the prognostic value of common tests used to identify ischemic heart disease. We also review the physiological consequences of cardiomyopathy in transplant candidates and explore the specific syndrome of "cirrhotic cardiomyopathy".

Noise-assisted MEMD based relevant IMFs identification and EEG classification

Noise-assisted multivariate empirical mode decomposition(NA-MEMD) is suitable to analyze multichannel electroencephalography(EEG) signals of non-stationarity and non-linearity natures due to the fact that it can provide a highly localized time-frequency representation.For a finite set of multivariate intrinsic mode functions(IMFs) decomposed by NA-MEMD,it still raises the question on how to identify IMFs that contain the information of inertest in an efficient way,and conventional approaches address it by use of prior knowledge.In this work,a novel identification method of relevant IMFs without prior information was proposed based on NA-MEMD and Jensen-Shannon distance(JSD) measure.A criterion of effective factor based on JSD was applied to select significant IMF scales.At each decomposition scale,three kinds of JSDs associated with the effective factor were evaluated:between IMF components from data and themselves,between IMF components from noise and themselves,and between IMF components from data and noise.The efficacy of the proposed method has been demonstrated by both computer simulations and motor imagery EEG data from BCI competition IV datasets.

ECG stress test induced atrial ischemia in a patient with old inferior myocardial infarction due to a distal coronary artery lesion

A 78-year-old man with a history of mitral valve prolapse underwent echocardiography during his cardiological check-up examination in 2011 in a symptom-free stage. Echocardiography revealed akinesis of the inferior septum and inferobasal free wall as a novel finding suggesting a distal right coronary artery （RCA） lesion （Figure 1）. The systolic left ventricular function was normal. Earlier echocardiographies did not show wall motion abnormalities.

Investigation on Major Noise Sources of Vehicle Diesel Engine Based on Sound Intensity Measurement

In order to reduce the noise and vibration of the diesel engine,it is crucial to exactly identify the engine noise source character.Based on "two-microphone" method,the sound intensity measurement of a vehicle four-stroke diesel engine was carried out in a hemi-anechoic chamber.Then the sound intensity contour maps were obtained from the measurement results and the main noise components of different frequencies on all the measurement surfaces were picked out to construct contour maps.By analysizing the relationship between the characteristics of contour maps and the space distribution of the engine compartment,the major sources of the exterior radiation noise of the diesel engine were identified.The results provided a creditable basis for improving the noise performance of the engine in the next phase.

Removal of White Noise from ECG Signal Based on Morphological Component Analysis

To effectively suppress white noise and preserve more useful components of electrocardiogram(ECG) signal, a novel de-noising method based on morphological component analysis(MCA) is proposed. MCA is a method which allows us to separate features contained in an original signal when these features present different morphological aspects. According to the features of ECG, we used the UWT dictionary to sparsely represent mutated component, and used the DCT dictionary to sparsely represent smooth component. The experimental results of the samples choosing from MIT-BIH databases show that the MCA-based method is effective for white noise removal.