胎儿心电监护中VD波型的观察和意义

胎儿心电监护中ＶＤ波型的观察和意义兰州军区总医院妇产科（兰州７３００５０）王彦明我科自１９８８年６月使用电子胎心电监护仪以来，对６００例孕妇进行了监测，以了解胎儿胎盘的储备能力，估计胎儿的安危，以期达到产科质量。在监护中发现不定型减速波型（以下简称Ｖ...     

一种新型心电监护治疗系统的研究与实现

介绍了一种新型的心电监护治疗系统，可有效的用于心血管疾病的预防、诊断、监护和治疗。采用小波变换的方法检测和处理心电信号。本文在介绍系统的硬件组成、软件设计的基础上，提出一种基于32位WINDOWS环境、采用多线程技术实现串行通信的新方法，有效地解决了传统多机监护系统串行通信中的迟滞性和不可靠性。     

胎儿心音分析用以实现胎儿心率监护的研究

作者分析了胎儿心音频谱特点。通过带通数字滤波及匹配滤波等方法,正确检测胎儿心率,为建立胎儿心音的胎儿心率监护仪提供了基础。     

基于移动智能终端的单通道胎儿心电监护系统

目的 设计基于移动智能终端的单通道胎儿心电监护系统,以实现扩展卡尔曼滤波(extended Kalman filtering,EKF)和奇异值分解(singular value decomposition,SVD)相结合的单通道胎儿心电提取算法,实时获取高信噪比的胎儿心电信号,完成胎心监护的远程移动医疗.方法 利用STM32单片机控制24位采样芯片ADS1298,对单通道的孕妇腹部信号进行采集,并将采集后的数据经蓝牙传送给移动智能终端,在基于Android的移动智能终端上实现EKF和SVD相结合的单通道胎儿心电提取算法,完成对胎儿心电的实时提取、显示、存储与分析,计算心律变异率,实现对整个监护系统进行控制等功能.结果 测试结果表明,该系统可从单通道孕妇腹部信号中准确提取出胎儿心电信号,准确度为95.60％,阳性预测率为98.71％,系统工作稳定,连续处理5个胎心周期的数据用时约为70μs,小于一个母体心动周期(约0.8 s)的时间,适于临床对胎儿心电的实时监护.结论 该系统实时性强、准确率高、工作稳定、操作简单、便于携带,实现了对胎心监护的可穿戴式远程移动医疗,适合社区医院和家庭使用.     

具有液晶显示的8098单片微机心电监护系统

以两片8098组成双微处理机系统,配以大屏幕点阵式液晶显示器,组成了便携式心电监护系统.系统有较强的心电数据处理功能,并且具有小型化便于携带的优点,有一定的实用价值.     

基于混合小波变换的瞬态信号检测方法

探讨了信号的小波变换与匹配滤波的关系,指出小波变换（WT）实际上就是可变检测模板的匹配滤液过程。根据这一思想,提出了基于混合小波的信号检测方法。本文中,“混合小波变换”是指在小波分解和重构中分别使用不同的基本小波。其中分解小波用于实现可变模板的信号检测,重构小波则用以增强被检测信号的特征。我们用该方法对实测脑电信号（EEG）中瞬态脉冲干扰进行检测。实验结果表明该方法能有效地检测出EEG中的瞬态脉冲。     

心电信号的小波变换滤波算法的改进

对心电信号的滤波算法进行了改进。在利用小波变换实现心电图信号滤波算法的基础上，增加了对2^3尺度下小波分解所得细节信号的模极大值对的检测功能，以修复因滤波受损的心电信号的QRS波。经MIT／BIH标准心电数据库验证，试验表明，该方法行之有效。     

新一代胎儿监护仪的研制

胎儿心电监护是预防围产期胎死的一项重要措施，作者介绍了一种基于８０９８单片机系统，利用匹配滤波技术进行信号处理以及采用大屏幕液晶显示的新一代胎儿心电心率监护仪，它具有体积小，重量轻，耗电量低，检测算法简单可靠的特点，经临床实验，成功地检出了胎儿心电波及胎儿心率。     

基于无线市话网络的远程心电监护系统

给出一种利用无线市话网络进行远程心电监护系统的设计方案.基于单片机的心电采集模块实时采集心电数据并通过USB接口传输到无线市话系统(personal wireless access system, PAS)手机,然后通过PAS系统网络发送到监护中心.相比其他移动心电监护方案,这种方法成本更低,而且数据传输率更高.     

面向家庭健康监护的心电监护系统设计

目的研制一款面向家庭的心电监护系统。方法以基于ARM920T的s3c2440为核心,控制心电信号采集,并结合嵌入式软件技术,实时显示、分析和记录心电信号,对患者进行监护。算法部分采用适用于嵌入式系统的动态差分阈值法检测QRS波波群。结果该监护系统能实时、动态显示心电波形,并可以识别4种心率异常,能较好地反映和分析患者的心电活动状况。结论该心电监护系统操作简便,运行稳定,能够满足一般家庭需求,具有良好的应用前景。     

Research of fetal ECG extraction using wavelet analysis and adaptive filtering

Extracting clean fetal electrocardiogram (ECG) signals is very important in fetal monitoring. In this paper, we proposed a new method for fetal ECG extraction based on wavelet analysis, the least mean square (LMS) adaptive filtering algorithm, and the spatially selective noise filtration (SSNF) algorithm. First, abdominal signals and thoracic signals were processed by stationary wavelet transform (SWT), and the wavelet coefficients at each scale were obtained. For each scale, the detail coefficients were processed by the LMS algorithm. The coefficient of the abdominal signal was taken as the original input of the LMS adaptive filtering system, and the coefficient of the thoracic signal as the reference input. Then, correlations of the processed wavelet coefficients were computed. The threshold was set and noise components were removed with the SSNF algorithm. Finally, the processed wavelet coefficients were reconstructed by inverse SWT to obtain fetal ECG. Twenty cases of simulated data and 12 cases of clinical data were used. Experimental results showed that the proposed method outperforms the LMS algorithm: (1) it shows improvement in case of superposition R-peaks of fetal ECG and maternal ECG; (2) noise disturbance is eliminated by incorporating the SSNF algorithm and the extracted waveform is more stable; and (3) the performance is proven quantitatively by SNR calculation. The results indicated that the proposed algorithm can be used for extracting fetal ECG from abdominal signals.     

Online Digital Filter and QRS Detector Applicable in Low Resource ECG Monitoring Systems

The present work describes fast computation methods for real-time digital filtration and QRS detection, both applicable in autonomous personal ECG systems for long-term monitoring. Since such devices work under considerable artifacts of intensive body and electrode movements, the input filtering should provide high-quality ECG signals supporting the accurate ECG interpretation. In this respect, we propose a combined high-pass and power-line interference rejection filter, introducing the simple principle of averaging of samples with a predefined distance between them. In our implementation (sampling frequency of 250 Hz), we applied averaging over 17 samples distanced by 10 samples (Filter10x17), thus realizing a comb filter with a zero at 50 Hz and high-pass cut-off at 1.1 Hz. Filter10x17 affords very fast filtering procedure at the price of minimal computing resources. Another benefit concerns the small ECG distortions introduced by the filter, providing its powerful application in the preprocessing module of diagnostic systems analyzing the ECG morphology. Filter10x17 does not attenuate the QRS amplitude, or introduce significant ST-segment elevation/depression. The filter output produces a constant error, leading to uniform shifting of the entire P-QRS-T segment toward about 5% of the R-peak amplitude. Tests with standardized ECG signals proved that Filter10x17 is capable to remove very strong baseline wanderings, and to fully suppress 50 Hz interferences. By changing the number of the averaged samples and the distance between them, a filter design with different cut-off and zero frequency could be easily achieved. The real-time QRS detector is designed with simplified computations over single channel, low-resolution ECGs. It relies on simple evaluations of amplitudes and slopes, including history of their mean values estimated over the preceding beats, smart adjustable thresholds, as well as linear logical rules for identification of the R-peaks in real-time. The performance of the QRS detector was tested with internationally recognized ECG databases (AHA, MIT-BIH, European ST-T database), showing mean sensitivity of 99.65% and positive predictive value of 99.57%. The performance of the presented QRS detector can be highly rated, comparable and even better than other published real-time QRS detectors. Examples representing some typical unfavorable conditions in real ECGs, illustrate the common operation of Filter10x17 and the QRS detector.     

Detection of fetal electrocardiogram signals using matched filters with adaptive normalisation

The authors discuss the application of matched filters to the detection of R-waves in fetal electrocardiogram (FECG) data, recorded during labour using a scalp electrode. When using the basic matched filter, one correlates a template representing the clean signal with the noisy signal. This method is optimal when the underlying noise is white in nature. However, it is known that false detection of R-waves can occur in the presence of extraneous peaks which have a similar shape to the fetal R-wave. It is proposed to switch between two different normalisations of the impulse response of the matched filter to alleviate this problem. When the signal-to-noise ratio is lower than a predetermined threshold, then normalisation to the geometric mean of the template and noisy data energies is carried out, otherwise only normalisation to the template energy is made. In the former case, the background noise and spikes that are larger than the underlying FECG are attenuated, hence increasing the probability of detection of the R-waves. In the latter case, noise which has a lower amplitude than the underlying R-wave, is reduced. The effectiveness of this method is demonstrated by application to scalp electrode data.     

Real-time multichannel abdominal fetal ECG monitor using Digital Signal CoProcessor

A real-time multichannel fetal ECG monitor based on a personal computer (PC) and a MOTOROLA DSP56001 Digital Signal CoProcessor (DSP) is introduced. The DSP board is plugged into the PC, which functions as a HOST computer. An analog 8 Leads Interface and Analog to Digital circuits module is connected to the DSP through a synchronous, opticalisolated communication channel.

The fetal ECG detection is based on a cross-correlation technique. An averaged maternal ECG waveform is generated using a cross-correlation alignment procedure and a user-defined template. The fetal ECG signals present in the maternal waveform is suppressed during the averaging procedure, since both are uncorrelated. The average maternal ECG waveform is then subtracted from the abdominal real time signals, and maternal-free fetal ECGs signals are obtained, including fetal QRS complexes that coincide with maternal ones. Using the abdominal ECGs signals after subtraction, an averaged fetal waveform is generated. The maternal and the fetal heart rate are calculated during the process.

The algorithm described above can be performed in real time on up to eight abdominal ECG traces by the DSP, and the desired results are passed to the HOST PC, to be stored and displayed. Electrodes positioning procedures for detecting the fetal QRS complexes with the best signal to noise ratio are not needed. Using the multichannel system, the user can select the best channel for fetal QRS detection, and accurate results for the heart rate signal are obtained. Averaged fetal waveforms are obtained from all the leads.     

12导联同步心电图异常波形数据库生成系统与波形分析初步

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。     

基于Android平台的心电监护仪设计

目的：设计一种基于Android平台的心电监护系统,可以将数据发送至手机界面,并显示心电波形和心率。方法：系统基于Android平台,结合飞思卡尔单片机9SXSl28和蓝牙模块设计,完成了心电信号的获取、放大和滤波、A／D转换和蓝牙发送的功能。系统包含电源模块、心电获取硬件模块、数据采样单片机系统、蓝牙发送模块、Android手机及软件五大部分组成。结果：通过肢体导联获取心电信号,之后经单片机AD采样,通过串口转蓝牙将数据发送至手机界面,并显示心电波形和心率。结论：本文设计并实现了心电采集模块的硬件电路和软件程序,编写了Android系统手机上的简单心电监护应用程序,心电采集模块与手机之间运用蓝牙无线方式传输心电数据。系统通过肢体导联获取人体心电信号并最终实时显示在手机上。该系统轻便小巧、低功耗、操作简单。经调试,系统运行稳定,心电信号可实时显示在手机界面,心率测量准确。通过这种设计有效缓解了就医难的问题,在医疗资源相对集中的国情下,基于Android手机的健康监护有着较大前景。     

长程动态心电图监护分析系统（Holter系统）的开发研究

系统地介绍了Ｈｏｌｔｅｒ系统的开发研究，着重了其中的若干关键技术，低功耗的硬件设计、实时高效的算法，高速可靠的回放接口以及完整友善的界面设计等。     

便携式心电监护系统中心电信号的实时分析方法设计

目的：设计并实现一种适用于便携式心电监护系统的心电波形实时动态检测和分析的方法。方法 ：作者首先应用5点平滑滤波消除信号的高频噪声和50 Hz干扰,然后通过对分段心电信号的长度变换来增强R波,并用长度阈值检测到R波位置,再通过去错检和查漏检算法提高R波检测准确率;正确检测到R波后,利用区域极值和斜率突变特点从R波开始向前、向后搜索找出Q、S波,然后从已开始的Q、S波位置再分别向前向后找到Q波起点和S波终点;最后根据已检测到的QRS波群计算了心率和ST段参数。结果：通过对包含各种噪声的心电信号的分析证明该算法能准确地检测到QRS波群,不受基线漂移和高频噪声的影响;算法用C语言实现后在嵌入式心电监护系统中的应用也表明其处理速度完全满足移动设备的实时动态分析要求。结论：本文设计的心电波形识别方法算法简单、速度快、抗干扰能力强、准确率高,并成功应用于基于32位嵌入式系统的心电监护仪。相信能给便携式心电监护设备研发中心电信号自动检测和分析功能的实现带来一些启发。     

小波分析在心电信号处理中的应用

主要从三个方面(心电信号的预处理、参数检测和波形检测以及心电图的压缩)综述了小波分析在心电信号处理中的应用，对各种算法进行了比较和评价，并对目前所存在的问题进行了初步探讨。