This paper constructs and implements the three-dimension presentation models of the two kinds of cell-telephone products based on the technologies such as Java3D,geometry modeling and texture mapping.The photos token from the surfaces of the products are as the input data of this system,the models of the products are constructed in Java3D,then the photos are mapped onto the corresponding surfaces of the models,and the high-quality computer imitation result is gotten.This method with ease input,high quality presentation,user friendly interaction can be applied widely to cell-telephone products display,advertising and so on.

The system devised by ourselves is used to detect the Heart Sound(HS) signal. The HS data was sampled at the precardium, and Lead I of the ECG was recorded simultaneously to label the heart sound. Using wavelet transform and timefrequency analysis method, the S3 and S4 of normal children, normal adults, normal elder and old subjects with Coronary Heart Diseases(CHD) were statistically analyzed. The results indicated that all normal persons has S3 and S4, and the significant difference(p=0.0164) was found in main peak frequencies of S3 between normal elder and old group with CHD. It shows that S3 is helpful in diagnosis the cardiovascular diseases.

This article analyzed some shortages of Bernoulli experimentation on the real equipments. A program of simulating this experimentation was put proposed in Quick Basic language. It is more convenient to do, the result is more reliable and the experimentation time becomes shorter.

研究第三心音(S3)在临床上的意义.在心前区采集心音数据,并采集一导心电信号来定位心音.采样频率为103Hz.用小波变换时频分析方法,研究了135例(正常少儿34例、正常成年人31例、正常老年人30例和冠心病老年人40例)心音图中的S3.表明所有正常人均有S3;正常老年人与老年一般冠心病患者的S3存在明显差异(p=0.0164),后者S3的频谱主峰频率明显上移.S3的检测有重要的临床诊断意义.

建立了12导联同步心电异常波形数据库生成系统,并在此基础上研究了12导联心电图实时分析与基于小波变换的QRS波自动识别算法.本研究可为临床医疗、教学和科研及心电自动分析软件和仪器的研制奠定基础,便于与国际心电数据库接轨.

目的:建立我国正常人和各类心脏病患者的心音数据库及心音彩色三维图谱库.方法:应用自行研制的心音数据库生成系统采集105例正常人和244例心脏病患者的数据,应用小波变换和自回归模型方法对入库数据进行分析.结果:①成功建立了心音数据库及三维图谱库;②小波变换可成功提取心音不同频段的信息;③彩色三维图谱分析可提取不同心音信号的特征信息.结论:心音数据库及彩色三维图谱库的建立,为自动化心音分析及心音诊断学研究打下了基础.

The wavelet transform analysis method was applied in studying heart sounds of normal and typical heart disease pa-tients.By this method,heart sounds could be studied according to differ ent wavelet analysis scales and time,frequency,ampli-tude.The three-dimensional phonocardiogram after wavelet analyzing could describe all the information of frequency domain,time domain and amplitude domain perfectly.The parameters of time and frequency analysis showed significant different between dif fer-ent groups.As an advantageous and convenient method of heart sounds analysis for clinical diagnosis and assisted instruction of cardiopathy,this study also supplied foundational data for further studying.

n this article, an application of a new data processing tool-wavelet transform is introduced. It can be used for science study in physiology and the other subjects. Here we offer a method of extracting respiration frequency and heart beat ratefrom blood pressure waveform curve with wavelet transform and FFT.

目的:通过心音三维分析了解小儿心肌炎的心音特征.方法:对34例健康儿童和26例心肌炎患儿在同一条件下进行心电心音同步采样,将获取的心音信息用计算机三维分析软件从频率、时间、强度三维领域分析研究.结果:心肌炎患儿第二心音(S2)波峰前后60-ms面积与第一心音(S1)面积之比值RTS高于健康儿童,0.05>P>0.01.S2第1谱峰峰值前后5-Hz范围内功率谱曲线所围面积(A1)与0～200-Hz的功率谱曲线所围面积(A2)之比值RF△S低于健康儿童,P<0.001.以频率响应25～200-Hz高频分析收缩期杂音(SM)和舒张期杂音(DM),显示心肌炎患儿SM和DM的RF△S明显高于健康儿童,P≤0.001 .以频率响应0～10-Hz低频分析,其RF△S值低于健康儿童,0.05>P>0.01.结论:心肌炎患儿S1强度明显减弱,S2第1谱峰低频成分减少,SM和DM明显且高频成分增多,SM低频成分减少.

目的：获取心音信号中对心脏疾病诊断有意义的信息。材料与方法：利用自回归模型方法对169个受检者（包括3组正常人和4组心脏病患者）的第1～4心音和收缩期杂音、舒张期杂音信号进行了谱分析，并各提取了5项对疾病诊断有意义的特征参数（频域3项，时域2项）进行正常与异常心音信号的比较研究。结果：统计结果表明时、频域许多参数均有显著性差异。结论：研究结果可为心音研究的进一步深入和临床心脏病的辅助诊断提供基础数据和客观定量指标。

用小波变换时频分析的方法对老年人的第三第四心音进行了分析研究,在心前区采集心音数据,为对心音定位,同步采集了一导心电信号.本研究对30例正常老年人(年龄在50～69岁)和40例冠心病老年人(年龄在53～85岁)的第三第四心音数据进行了统计分析,发现正常老年人S3的频谱主峰频率与冠心病老年人S3的频谱主峰频率有明显的差异.由于S3和S4的幅度和频率都很低,用听诊方法常被漏掉.本研究为心脏疾病的诊断提供了新的途径.