Comparison of FFT and adaptive ARMA methods in transcranial Doppler signals recorded from the cerebral vessels

In this work, transcranial Doppler signals recorded from the temporal region of the brain on 35 patients were transferred to a personal computer by using a 16-bit sound card. Fast Fourier transform and adaptive auto regressive-moving average (A-ARMA) methods were applied to transcranial Doppler frequencies obtained from the middle cerebral artery in the temporal region. Spectral analyses were obtained to compare both methods for medical diagnoses. The sonograms obtained using A-ARMA method give better results for spectral resolution than the FFT method. The sonograms of A-ARMA method offer net envelope and better imaging, so that the determination of blood flow and brain pressure can be calculated more accurately. All diseases show higher resistance to flow than controls with no difference between males and females. Whereas values between disease classes differed, resistance within each class was remarkably constant.     

Frequency analysis of high-intensity transient signals of transcranial Doppler ultrasound in patients supported with a left ventricular assist device

Left ventricular assist devices (LVADs) have become more important than ever for patients with terminal heart disease. The chronic shortage of donors for heart transplantation may enhance the importance of LVADs as destination therapy. To prevent cerebral complications, the evaluation of high-intensity transient signals (HITS) of transcranial Doppler (TCD) ultrasound is important. In the present study, HITS were measured on seven occasions in patients supported with LVADs. The high-frequency counts in HITS were greater than the low-frequency counts (47 ± 42 vs. 9 ± 9 in 3 min, P = 0.025), and declined further with oxygen delivery to the patient. The high frequency of signals may imply air microemboli, and the counts may increase with time. Presented in part at the 2007 Joint Congress of the 45th Annual Conference of the Japanese Society for Artificial Organs and the 2nd Annual Conference of the International Federation for Artificial Organs, Osaka     

Usage of eigenvector methods to improve reliable classifier for Doppler ultrasound signals

A new approach based on the implementation of the automated diagnostic systems for Doppler ultrasound signals classification with the features extracted by eigenvector methods is presented. In practical applications of pattern recognition, there are often diverse features extracted from raw data which needs recognizing. Because of the importance of making the right decision, the present work is carried out for searching better classification procedures for the Doppler ultrasound signals. Decision making was performed in two stages: feature extraction by the eigenvector methods and classification using the classifiers trained on the extracted features. The aim of the study is classification of the Doppler ultrasound signals by the combination of eigenvector methods and the classifiers. The present research demonstrated that the power levels of the power spectral density (PSD) estimates obtained by the eigenvector methods are the features which well represent the Doppler ultrasound signals and the probabilistic neural networks (PNNs), recurrent neural networks (RNNs) trained on these features achieved high classification accuracies.     

Introduction of an embolus detection system based on analysis of the transcranial Doppler audio-signal

A new embolus detection system (EDS) is presented, built with the intention of detecting ongoing cerebral embolization in patients at risk of transient ischaemic attacks or stroke. It is based on the analysis of the audio-Doppler signal of a transcranial Doppler machine. The algorithm of the EDS estimates the intensity, duration and zero-crossing dynamics of the audio signal. The EDS has a multi-layer neural network which classifies events into micro-emboli signals (MES) or artefacts. The decision-making component of the software has been validated against human experts. Data from patients in the post-operative phase of carotid surgery were used for the validation process. The results showed agreement in MES and artefact classification of > 93%. Apart from a monitoring display, the monitoring system includes a verification unit that allows the user to listen and to look at all data of individual MES and artefacts. Moreover, the system allows the user to record, store and re-calculate all data files. Data are stored using European Data Format, which allows data transportation over the Internet. The EDS may have a potential in stroke risk stratification, evaluating the effect of novel anti-thrombotic therapies, and in peri-operative and remote monitoring of carotid endarterectomy.     

Real-time identification and archiving of micro-embolic Doppler signals using a knowledge-based DSP system

Identification of micro-emboli in the cerebral circulation using transcranial Doppler ultrasound provides valuable clinical information, but, currently, embolic signal detection and analysis are significantly limited because they mainly rely on costly off-line analysis by human experts. In this study, a reliable, high-resolution, real-time automated system for the detection and archiving of embolic signals was designed and implemented using expert system theory and modern DSP technology. Preliminary tests were conducted to evaluate the functions and the performance of the system using data from ten carotid endarterectomy patients and two normal volunteers. Using the widely accepted 7 dB threshold for human reliability and a human expert, majority-decision gold standard, the real-time system reached sensitivity and specificity of 93.6% and 99.3%, respectively, which were close to the results obtained by three human experts under ideal laboratory conditions (90.1% and 99.8%, 98.4% and 99.9%, 98.9 and 99.9%). The new system has the potential to be used either as a bedside monitoring and signal acquisition device, or as a laboratory investigation tool.     

Probabilistic neural networks employing Lyapunov exponents for analysis of Doppler ultrasound signals

The implementation of probabilistic neural networks (PNNs) with the Lyapunov exponents for Doppler ultrasound signals classification is presented. This study is directly based on the consideration that Doppler ultrasound signals are chaotic signals. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. Decision making was performed in two stages: computation of Lyapunov exponents as representative features of the Doppler ultrasound signals and classification using the PNNs trained on the extracted features. The present research demonstrated that the Lyapunov exponents are the features which well represent the Doppler ultrasound signals and the PNNs trained on these features achieved high classification accuracies.     

The information content of Doppler ultrasound signals from the fetal heart

Knowledge of the content of Doppler ultrasound signals from the fetal heart is essential if the performance of fetal heart rate (FHR) monitors based upon this technology is to be improved. For this reason instrumentation was constructed to enable the simultaneous collection of Doppler audio signals and the transabdominal fetal ECG (for signal registration), with a total of 22 recordings being made with an average length of around 20 minutes. These data demonstrate the transient nature of the Doppler audio data with wide variations in the signal content observable on a beat-to-beat basis. Short-time Fourier analysis enabled the content of the Doppler signals to be linked to six cardiac events, four valve and two wall motions, with higher frequency components being associated with the latter. This differing frequency content together with information regarding the direction of movement that can be discerned from Doppler signals provided a potential means of discriminating between these six events (which are unlikely to all contribute to the Doppler signal within the same cardiac cycle). Analysis of 100 records showed that wall contractions generate the most prominent signals, with atrial contraction recognisable in all records and ventricular wall contraction in 95% (although its amplitude is only around 30% of that of the atrial signal). Valve motion, with amplitudes between 15 and 25% that of the atrial wall signal, were visible in 75% of records. These results suggest means by which the six events that contribute to the Doppler signal may be distinguished, providing information that should enable an improvement in the current performance of Doppler ultrasound-based FHR monitors.     

Online measurement of cardiac indices from frequency transformed TAV Doppler ultrasound signals

A system is described for the analysis of blood flow signals in the aortic artery which enables indices of stroke volume and cardiac output to be derived. A commercial Doppler ultrasound monitor is used, the demodulated return signals are digitised, and frequency analysis is performed in real time using an FFT signal processing circuit. A Z-80 microprocessor controls the synchronisation of the data acquisition, transformation and display of the signals. Algorithms have been developed to identify the maximum velocity profile of each heartbeat and perform the necessary calculations to produce indices of stroke volume and cardiac output. The system has been evaluated against an existing offline method for a series of recordings on normal subjects and has demonstrated good repeatability. It has also been used in a clinical study on the effects of anaesthesia on chronic spinal injury patients. The results have shown that the system can be used to follow serial changes in cardiac performance within individual subjects.     

超声多普勒血流和管壁搏动信号的分离研究

目的针对超声多普勒血流检测中,传统的高通滤波法在滤除管壁搏动信号的同时也会滤除低频血流信号的问题,本研究提出一种以心电信号（electrocardiography,ECG）作为参考信号的自适应滤波的方法消除管壁干扰。方法包括两方面：其一,采用心电信号作为参考信号对超声多普勒信号进行自适应滤波;其二,采用多级自适应滤波并选择不同的参考信号的滤波方案。分别使用上述方法和高通滤波法对仿真的超声多普勒信号进行处理,并将结果进行比较。结果与传统的高通滤波法相比,该方法在有效抑制管壁搏动信号的同时保留一部分低频血流信号成分。结论该方法能较准确地提取出完整的血流超声多普勒信号,具有一定的临床应用价值。     

彩色多普勒超声在椎动脉粥样硬化诊断中的研究进展

后循环缺血（PCI）是一种临床常见病和多发病,系指椎基底动脉系统短暂性脑缺血发作和脑梗死。椎动脉粥样硬化是PCI常见的病因之一。 PCI的影像学检查包括经颅多普勒超声（TCD）、数字减影血管造影术（DSA）、计算机控制体层摄影造影术（CTA）、磁共振血管造影术（MRA）及彩色多普勒超声（CDU）等。TCD可作为PCI的初步筛查工具,DSA是目前椎动脉疾病诊断的“金标准”;CTA和DSA同属有创检查,且都需要造影剂,不易被患者接受;MRA属于无创检查,但其可能夸大血管狭窄程度;CDU可较准确测量椎动脉内径及评价血流动力学参数,可作为PCI无创伤性的检查手段,具有直接、准确、方便及可重复性等优点,为PCI的明确诊断和疗效评价提供客观依据。就CDU在椎动脉粥样硬化患者诊断中的研究进展作一综述。     

Functional transcranial Doppler sonography as a tool in psychophysiological research

Functional transcranial Doppler sonography (fTCD) allows the noninvasive and uncomplicated registration of intracranial blood flow parameters under defined conditions of stimulation. Although local distribution patterns of regional blood perfusion can be measured with high spatial resolution through neuroimaging methods (e.g., PET or SPECT), these methods are limited by their low temporal resolution. The high temporal resolution provided by fTCD, however, allows the recording of the dynamic component of cerebral blood perfusion by continuously measuring the cerebral blood flow velocity in the basal cerebral arteries. Hence, this method is especially appropriate for the investigation of fast neuronal activation processes, which are generally accompanied by changes in local blood perfusion. In this review, we present methodical issues regarding fTCD, as well its application in the field of psychology, especially psychophysiology. The relevant studies available to date investigate processes of attention and perception, higher cognitive functions, and emotional and psychomotor processes. Considering the current state of methodology and research, fTCD can be seen to be an important complement to the other psychophysiological methods for studying brain function.     

Effect of human head flexion on the control of peripheral blood flow in microgravity and in 1 g

This study evaluated, in six healthy subjects, whether head flexion, which stimulates the vestibular system and the tonic neck receptors, interferes with cardiovascular regulation. Arterial parameters were measured continuously using a pulsed Doppler ultrasound probe during parabolic flights with subjects either in the supine craned-head position (control) or in the supine anterior neck flexion bent-neck position. Exposure to 0 g induced a fluid shift towards the head (stroke volume +8%, P<0.05). Compared to the control situation the mean (SD) blood flow in the femoral artery decreased [ –10 (9)% vs +1 (10)%; P<0.05], and the ratio cerebral artery:femoral artery blood flow ( : ) increased [+8 (14)% vs –4 (7)%; P<0.05], in the bent-neck position. Thus, neck flexion without otolith loading (subject in 0 g) favoured cerebral perfusion during the exposure to 0 g. The return to 1 g, even in the supine position, induced a fluid shift towards the lower limbs. From 0 to 1 g, reduced less [ +6 (8)% vs –1 (8)%; P<0.05], and the : decreased more [–11 (9)% vs 0 (10)%; P<0.05], in the bent-neck position than in the control position. Thus the redistribution of peripheral blood flow in response to the fluid shift towards the legs was less efficient in the bent-neck position. In 0 g environment the passive flexion of the neck (neck receptor stimulation only) increased resistance in the femoral artery [R _fa +20 (21)%; P<0.05] and reduced the [–15(10)%; P<0.07] which increased the redistribution of flow towards the brain [ ; +12 (7)%; P<0.07]. This response was of lower amplitude when both otoliths and neck muscle were stimulated (neck flexion in 1 g) [R _fa+9 (7)%, P<0.05; –9 (12), NS; : 0 (12), NS]. We suggest that otolith and neck muscle stimulation (by neck flexion) trigger opposite vascular effects in response to a fluid shift towards the legs. Electronic Publication     

Online identifying and quantifying Doppler ultrasound waveforms

A microcomputer-based system is described for automatically identifying and quantifying the maximum peripheral arterial velocity waveforms obtained with a Doppler ultrasound spectrum analyser. A waveform identification algorithm is used to determine the beginning and end points of each waveform without the use of an e.c.g. trigger. A second algorithm calculates the pulsatility index. Experience in the use of these algorithms over a two-year period on 2500 patients is discussed. On 400 consecutive normal and abnormal recordings, wareform identification was 96% correct.     

经颅多普勒超声诊断颅内段后循环动脉狭窄或闭塞的应用价值

目的 探讨经颅多普勒超声（TCD）诊断颅内段后循环动脉狭窄或闭塞的敏感性和特异性.方法 选取颅内段后循环动脉狭窄或闭塞的患者72例,进行TCD和CT血管造影术（CTA）检查,并进行对比分析.结果 与CTA相比,TCD对颅内段后循环动脉检查的敏感性为82.50％,特异性为94.64％,阳性预测值为91.67％,阴性预测值为88.33％,准确性为89.58％.结论 TCD对颅内段后循环动脉病变的诊断特异性高,敏感性一般,其中对颅内段椎动脉的诊断准确性最高.TCD可作为颅内动脉病变的早期筛查手段.     

彩色多普勒超声诊断胎儿单脐动脉的临床价值

目的探讨超声对胎儿单脐动脉的诊断意义。方法应用彩色多普勒超声连续观察21405例中晚孕期孕妇单脐动脉的发生情况并测量其脐动脉血流频谱（PI、RI及S/D比值）。结果共发现单脐动脉胎儿140例,99例单纯性单脐动脉,41例合并畸形,它们分别与正常胎儿的PI、RI、S/D值比较均无显著性差异（P〉0.05）。结论应用彩色多普勒超声可准确诊断胎儿单脐动脉的发生情况,为遗传生殖提供临床价值。     

TCD观察深刺风池穴对肌紧张性头痛患者脑血液动力学的影响

目的:比较分析肌紧张性头痛采用深刺风池穴治疗前后脑血液动力学变化与临床关系;方法:利用彩色经颅多普勒超声(TCD)技术对400例肌紧张性头痛患者进行双侧椎动脉重要参数检测,并观察用深刺风池穴持续治疗3个疗程前后收缩期血流峰值的差异,并对结果作对照分析;结果:双侧椎动脉的流速变化有显著性差异(P<0.01);结论:深刺风池穴对治疗肌紧张性头痛有一定的效果。     

彩色多普勒检测子宫动脉预测妊高征的价值研究

目的探讨彩色多普勒检测子宫动脉预测妊娠高血压综合征（妊高征）的价值及临床意义。方法应用彩色多普勒超声对587例20～24周妊娠妇女的子宫动脉进行检测,通过观察追踪随访孕妇至分娩,根据是否出现高血压,把检测20～24周妊娠妇女的子宫动脉参数分为两组：正常组（560例）和高危组（27例）,进行对照研究,对比分析两组受检者子宫动脉血流动力学变化及声像图表现。结果①高危组子宫动脉收缩期峰值血流速度（Vd）较正常组快,舒张期最小血流速度（Vs）和平均血流速度（Vm）减慢（P〈0.01）,高危组子宫动脉阻力指数（RI）、搏动指数（PI）和收缩期峰值血流速度/舒张期最小血流速度（S/D）比正常组高（P〈0.01）,②高危组子宫动脉多普勒频谱表现典型者出现舒张早期＂V＂切迹。结论高危组患者子宫动脉血流动力学和多普勒频谱形态与正常组妊娠妇女有明显的不同,常规定期监测20～24周妊娠妇女子宫动脉血流动力学变化及多普勒频谱形态,对早期发现和治疗妊高征,保障母婴健康具有极其重要的意义。     

Detection of early atherosclerosis by analysis of ultrasonic Doppler signals produced by mural flow disturbances

The paper describes an in vitro study using a multi-gate Doppler ultrasound system to investigate flow disturbances in a blood analogue caused by small stenoses (2–25% cross-sectional area reduction), using steady flow (100–600 ml min⁻¹) in a 6 mm diameter rigid artery model. The results indicate that stenoses greater than 5% were detectable.     

经颅多普勒超声在椎动脉型颈椎病诊断中的应用

为分析经颅多普勒 (TCD)检测椎动脉型颈椎病 (CSA)的诊断价值 ,采用配对研究方法 ,用 2MHz脉冲多普勒探头经枕骨大孔窗口 ,检测左、右椎动脉及基底动脉的血流速度、流向、音频、血管博动指数等血流动力学指标 ,结果显示 10 8例患者有 80例异常 ,异常率 74 7%,并发现CSA组低流速者占 45 4 %,高流速者占 2 8 7%,正常流速者占 2 5 9%,与正常对照组间有显著差异 (P <0 0 1) ,总体而言 ,低流速型是CSA的主要特征之一。