An improved method for R-peak detection by using Shannon energy envelope

R-peaks in electrocardiogram (ECG) play a vital role in diagnosis of heart rhythm irregularities and also estimating heart rate variability. However, almost all existing R-peak detectors suffer from the non-stationary of both QRS morphology and noise. To overcome these difficulties, we propose a four-stage improved method to detect R-peak using Shannon energy envelope. In the first stage, noise is suppressed and QRS complex is enhanced by using band pass filter, first order differentiation, and amplitude normalization. In the second stage, Shannon energy envelope is extracted. In the third stage, peak is estimated without considering any threshold amplitude. In the final stage, true R-peaks are detected. Our proposed R-peak detection method is validated using 48 first channel ECG records of the MIT-BIH arrhythmia database with the accuracy of 99.84%, sensitivity of 99.95% and positive predictability of 99.88%. Our proposed method outperforms other well-known methods in case of pathological ECG signals.     

Effective simulation of signals for testing ECG analyzer

In this paper the solution of the specialized measuring system for electrocardiography (ECG) signal recording and introductory recognition is presented. The project aims at designing the complete PC-based Virtual Instrument as a "testing platform" for acquisition, processing, presenting, and distributing ECG data. A new design involving the latest technique in signal simulation was developed to create a controllable model of the electrocardiography signal. Then it was implemented for testing of the developed QRS detection algorithm, based on the time-frequency analysis method. The processing stage involving discrete wavelet transform was used to detect QRS complexes in the ECG signal. By using the controlled signal model and the real ones, the algorithm was shown to be advantageous in reducing ventilation artifacts and motion noise, resulting in good accuracy.     

An automated algorithm for online detection of fragmented QRS and identification of its various morphologies

Fragmented QRS (f-QRS) has been proven to be an efficient biomarker for several diseases, including remote and acute myocardial infarction, cardiac sarcoidosis, non-ischaemic cardiomyopathy, etc. It has also been shown to have higher sensitivity and/or specificity values than the conventional markers (e.g. Q-wave, ST-elevation, etc.) which may even regress or disappear with time. Patients with such diseases have to undergo expensive and sometimes invasive tests for diagnosis. Automated detection of f-QRS followed by identification of its various morphologies in addition to the conventional ECG feature (e.g. P, QRS, T amplitude and duration, etc.) extraction will lead to a more reliable diagnosis, therapy and disease prognosis than the state-of-the-art approaches and thereby will be of significant clinical importance for both hospital-based and emerging remote health monitoring environments as well as for implanted ICD devices. An automated algorithm for detection of f-QRS from the ECG and identification of its various morphologies is proposed in this work which, to the best of our knowledge, is the first work of its kind. Using our recently proposed time–domain morphology and gradient-based ECG feature extraction algorithm, the QRS complex is extracted and discrete wavelet transform (DWT) with one level of decomposition, using the ‘Haar’ wavelet, is applied on it to detect the presence of fragmentation. Detailed DWT coefficients were observed to hypothesize the postulates of detection of all types of morphologies as reported in the literature. To model and verify the algorithm, PhysioNet''s PTB database was used. Forty patients were randomly selected from the database and their ECG were examined by two experienced cardiologists and the results were compared with those obtained from the algorithm. Out of 40 patients, 31 were considered appropriate for comparison by two cardiologists, and it is shown that 334 out of 372 (89.8%) leads from the chosen 31 patients complied favourably with our proposed algorithm. The sensitivity and specificity values obtained for the detection of f-QRS were 0.897 and 0.899, respectively. Automation will speed up the detection of fragmentation, reducing the human error involved and will allow it to be implemented for hospital-based remote monitoring and ICD devices.     

A real‐time feature extraction method for PVC detection in bedside monitor

Abstract

This paper describes a fast and very efficient feature extraction method for discrimination of QRS and Premature Ventricular Contraction (PVC) beats in a microprocessor‐based bedside monitoring system. It converts each QRS and PVC beat into a positive‐pulse waveform by signal preprocessing. Two characteristic factors, the positive‐pulse and the pulse duration, are calculated when the onset and end points of each pulse have been detected by threshold detection. The prominent feature is extracted from a product of these two factors. This algorithm has been examined using 40 different patients’ electrocardiograph (ECG). The accuracy of QRS detection was 99.3 percent in the tests performed. The identification sensitivity of PVC was 81.2 percent with 18‐ different arrhythmia patients.     

Real-time multi-face detection on FPGA for video surveillance applications

In the field of face recognition and in the establishment of a face database, face detection is a crucial step. In current security and surveillance systems, most of the face detection proposed now is focused on software algorithms to improve the detection rate and decrease false alarms. However, these more complex algorithms require more computation time, which hinders real-time applications. In this paper, we propose a real-time multi-face detection system based on hardware design to enhance processing time. The proposed hardware architecture is implemented on an Altera DE2-70 field-programmable gate array development board to test the feasibility of our hardware design. To implement, our system requires 15,223 logic elements. The proposed system can operate in real-time at a frame rate of 30?fps, and detects up to five faces simultaneously. Our experimental results show that the proposed face detection architecture provides a reliable real-time system operating at low cost and providing a high detection rate.     

基于静态特征的硬件木马检测

分析了集成电路全球化设计、制造致使集成电路易被植入硬件木马(HT)从而使其存在遭受恶意攻击隐患的硬件安全形势,以及现有硬件木马检测方法的技术特点,在此基础上提出了一种基于静态特征的硬件木马检测新方法——HTChecker。HTChecker基于硬件木马的静态特征利用子图同构技术来检测木马。与其他的检测方法相比,它可以快速精确地找出已知特征的硬件木马。为了不受限于机器内存的大小,该方法借助图数据库来存储电路,这样它对超大规模的电路也可以进行检测。使用ISCAS’89和OpenCores benchmark电路对HTChecker进行了评估,木马电路被随机地插入到这些电路中。实验结果显示HTChecker可以快速精确地找出木马,并且不需要"Golden Chip"的辅助。HTChecker可以有效地处理实际的VLSI设计。     

Robustness of electrocardiogram signal quality indices

Electrocardiogram (ECG) signal quality indices (SQIs) are essential for improving diagnostic accuracy and reliability of ECG analysis systems. In various practical applications, the ECG signals are corrupted by different types of noise. These corrupted ECG signals often provide insufficient and incorrect information regarding a patient’s health. To solve this problem, signal quality measurements should be made before an ECG signal is used for decision-making. This paper investigates the robustness of existing popular statistical signal quality indices (SSQIs): relative power of QRS complex (SQI_p), skewness (SQI_skew), signal-to-noise ratio (SQI_snr), higher order statistics SQI (SQI_hos) and peakedness of kurtosis (SQI_kur). We analysed the robustness of these SSQIs against different window sizes across diverse datasets. Results showed that the performance of SSQIs considerably fluctuates against varying datasets, whereas the impact of varying window sizes was minimal. This fluctuation occurred due to the use of a static threshold value for classifying noise-free ECG signals from the raw ECG signals. Another drawback of these SSQIs is the bias towards noise-free ECG signals, that limits their usefulness in clinical settings. In summary, the fixed threshold-based SSQIs cannot be used as a robust noise detection system. In order to solve this fixed threshold problem, other techniques can be developed using adaptive thresholds and machine-learning mechanisms.     

Digital computer diagnosis of cardiac arrythmias in a single-lead electrocardiogram

The objective of this study was to develop a method to diagnose cardiac arrythmias from a singlelead ECG utilizing a digital computer programmed to identify R-R intervals and QRS widths, but no P-waves. This method is part of a larger system for on-line computer monitoring of several physiological variables in postoperative and intensive care patients.The ECG signal was transmitted to a PDP-9 computer where it was sampled 60 times/sec, converted to digital data, and then further converted to first order descending difference values upon which all identification procedures were done. A QRS complex, for example, was identified when the absolute first order descending difference value was greater than a certain level for each test ECG. Means, standard deviations and other statistical parameters were calculated from the R-R interval and QRS durations. Other, more complex, logical processes were used to evaluate the degree of irregularity. This was all done rapidly enough to provide real-time analysis. Eighteen types of arrythmias may be identified from these variables. Their validity was tested by comparison with the diagnoses made by a cardiologist. At present, the program can diagnose normal tracings, tachycardia and bradycardia, premature atrial contractions, premature ventricular contractions, atrial fibrillation with a high degree or reliability (90–95 per cent), intermittent and complete bundle branch blocks and sinus arrythmias with a moderate degree of reliability (80 per cent). For several other arrythmias, such as ventricular and paroxysmal tachycardias, sinus arrest, bigeminy and trigeminy, there is not sufficient evidence as yet to test validity.With only a single-lead and without P-wave identification, the system seems to identify quite reliably many of the arrythmias which threaten postoperative patients.     

基于心电信号采集与处理的刺绣型织物电极研究

为实现对心电信号的长期穿戴式监测和生理状态的反馈,选用140D的镀银尼龙纱线,采用刺绣法制备织物电极,从织物电极的形状、尺寸以及使用过程中偏置电压的变化情况进行静态分析,得出电极本身因素和穿戴时间对电极使用效果的影响。然后,将小波变换除杂后织物电极采集的心电信号与标准电极采集的心电信号经过Matlab处理,分析织物电极采集心电信号的可行性。利用R波检测算法和QRS波群提取原理提取出两种特征波以及程序语言得到特征波形的规律,并反馈出受试者的生理状态。借助SPSS软件对两者采集的心电信号进行了相关性检验和回归分析,结果表明,刺绣型织物电极采集的心电信号与标准电极采集的心电信号具有强相关性。     

FPGA软硬件协同处理实时图像处理系统

基于PC机图像处理系统实时性不强,DSP+FPGA图像处理系统的成本高、资源利用率低,单纯使用FPGA硬件实现的图像算法类型较为单一,针对这一系列问题,提出了一种基于FPGA软硬件协同处理的实时图像处理系统.采用一片FPGA芯片作为系统的核心,利用CCD相机等采集图像,通过SSRAM将图像缓存,以SOPC为控制核心,协调软硬件共同进行图像处理.易于使用硬件实现的图像处理模块(如滤波、形态学算法、图像校正、边缘检测等)均使用Verilog HDL语言实现,通过SOPC控制这些图像处理模块,实现相应的图像处理功能;而硬件难于实现的部分(如流程控制、复杂的分支判断)则使用SOPC中的CPU来实现.实验表明,系统卖时性强、图像处理速度快、可进行复杂图像算法的运算,同时具有设计简单、应用灵活、成本低的特点.     

New Method for Measuring Statistical Distributions of Partial Discharge Pulses

A new digital detection system is described for measuring pulsating partial discharges (PDs). The PD detection system can continuously record all PD pulses that occur over extended periods of time, with a minimum inter-pulse time separation of 6 μs and a vertical amplitude resolution of 12 bits. Earlier PD detection systems detected PD pulse amplitude and time using complex custom-designed hardware while the present system continuously records the complete electrical waveform that carries the PD pulses using a commercial data acquisition board and extracts, in real time, the time and amplitude information of all PD pulses in software. The current approach considerably reduces the development and maintenance cost of the PD detection system, significantly increases the system portability, and may prove to be a crucial step for transferring the digital PD detection and analysis technology developed in laboratories to industry. The features of the new system are illustrated by the study of dc-excited PD pulses occurring in a point-to-plane gap in air. A new surface-mediated burst mode of PDs is discovered in which a PD pulse has a certain probability to induce another pulse. The probability is determined for several gap voltages and is found to vary strongly with the applied voltage.     

硬件友好的3GPP-LTE Turbo交织器设计

研究了第三代合作伙伴计划长期演进技术(3GPP-LTE)中的二次置换多项式(QPP)交织器的硬件设计优化,提出了一种零延时、低复杂度的QPP交织器设计方案。该方案从算法层面出发简化了QPP交织器中定义的复杂运算。得益于算法优化的结果,优化后的QPP交织器能够以较低的代价映射到硬件电路上。结果表明:与一些传统方案相比,该方案设计的QPP交织器大大降低了硬件实现的复杂度,在SMIC 40nm工艺下,交织器的面积只有0.040mm~2。另外,所设计的QPP交织器具有零时延的特点,能够有效提高Turbo译码的译码效率。基于该交织器所设计的Turbo译码器能够稳定工作在400MHz下,译码速率达到572.85Mbps(10次半迭代),而译码器面积仅有0.82mm~2。     

A New Database Intrusion Detection Approach Based on Hybrid Meta-Heuristics

A new secured database management system architecture using intrusion detection systems (IDS) is proposed in this paper for organizations with no previous role mapping for users. A simple representation of Structured Query Language queries is proposed to easily permit the use of the worked clustering algorithm. A new clustering algorithm that uses a tube search with adaptive memory is applied to database log files to create users’ profiles. Then, queries issued for each user are checked against the related user profile using a classifier to determine whether or not each query is malicious. The IDS will stop query execution or report the threat to the responsible person if the query is malicious. A simple classifier based on the Euclidean distance is used and the issued query is transformed to the proposed simple representation using a classifier, where the Euclidean distance between the centers and the profile’s issued query is calculated. A synthetic data set is used for our experimental evaluations. Normal user access behavior in relation to the database is modelled using the data set. The false negative (FN) and false positive (FP) rates are used to compare our proposed algorithm with other methods. The experimental results indicate that our proposed method results in very small FN and FP rates.     

海洋资料浮标声学特征采集系统设计

为利用我国现有的10 m大型资源浮标,实现对海上侵权船只进行探测和识别,介绍了一种加装在浮标上的声学特征采集系统设计。该系统设计包括声学基阵设计,信号采集处理机设计,目标探测与方位估计算法和声学基阵方位补偿方法等。2014年6月进行了一次湖上试验,试验结果表明：声学特征采集系统的硬件可靠,目标探测、方位估计和方位补偿算法有效。该系统已在我国特定敏感区域开展的维权执法目标探测识别与信息传输技术的信息综合监视中示范应用。     

基于TDLAS的批量种子活力检测装置设计

针对我国缺乏对批量种子活力检测装置的研究,以及传统检测方法可能会对种子样品造成不可逆损伤的问题,提出了一种通过可调谐半导体激光吸收光谱（tunable diode laser absorption spectroscopy,TDLAS）技术检测种子呼吸强度来判定其活力等级的无损检测方法,并设计了相应的检测装置,以实现对种子活力的批量检测。首先,从整体上设计了批量种子活力检测装置的结构,确定了上料—检测—分选—复位的工艺流程和要求。然后,对该检测装置的关键部件——种子盒进行了结构设计,同时对其内部光路进行了理论设计,并结合Zemax光学设计软件对内部光路进行了仿真分析。接着,对该检测装置控制系统的软、硬件进行了设计。最后,搭建了检测装置样机,并开展了上料、检测和分选试验。试验结果表明,所设计的批量种子活力检测装置样机的稳定性较好,其综合成功率达96.67%。研究结果可为批量种子活力检测装置的商品化和市场化提供参考。     

Efficient Data Compression of ECG Signal Based on Modified Discrete Cosine Transform

This paper introduced an efficient compression technique that uses the compressive sensing (CS) method to obtain and recover sparse electrocardiography (ECG) signals. The recovery of the signal can be achieved by using sampling rates lower than the Nyquist frequency. A novel analysis was proposed in this paper. To apply CS on ECG signal, the first step is to generate a sparse signal, which can be obtained using Modified Discrete Cosine Transform (MDCT) on the given ECG signal. This transformation is a promising key for other transformations used in this search domain and can be considered as the main contribution of this paper. A small number of wavelet components can describe the ECG signal as related work to obtain a sparse ECG signal. A sensing technique for ECG signal compression, which is a novel area of research, is proposed. ECG signals are introduced randomly between any successive beats of the heart. MIT-BIH database can be represented as the experimental database in this domain of research. The MIT-BIH database consists of various ECG signals involving a patient and standard ECG signals. MATLAB can be considered as the simulation tool used in this work. The proposed method's uniqueness was inspired by the compression ratio (CR) and achieved by MDCT. The performance measurement of the recovered signal was done by calculating the percentage root mean difference (PRD), mean square error (MSE), and peak signal to noise ratio (PSNR) besides the calculation of CR. Finally, the simulation results indicated that this work is one of the most important works in ECG signal compression.     

自动测试系统资源模型化设计

通过对通用自动测试系统设计方法的分析,提出了自动测试系统资源模型化的描述方法.该方法从数学的角度将系统的硬件资源纳入统一的逻辑表达范畴,按照硬件资源的功能设计了5大系统模型,并根据各个模型的特点设计了相应的数学函数,进而实现了系统资源的完备性描述,并实现了硬件资源与测试系统软件的交互.在实际工作中,将资源模型化设计纳入了适配器的设计过程中,取得了良好的效果.同时该工作为测试程序集的开发和仪器互换性设计奠定了基础.     

基于SGS模型与AHP的侦测无人机造型设计研究

目的 为了满足无人机用户需求,完善侦测无人机造型设计方法,进一步拓展产品设计路径。方法 将管理学中的门径管理模型(SGS)融入产品系统开发设计流程;调研用户需求并结合层次分析法(AHP)构建判断矩阵,计算各个设计指标权重并排序,以此促进设计决策,完成侦测无人机造型设计方案;采用7点量表法进行初步方案设计评价,验证设计模型和过程的科学性。结论 以侦测无人机造型设计为例,通过构建SGS产品系统开发模型,运用AHP分析方法进行设计方案指标决策,为侦测无人机造型设计拓展设计路径,为相关产品的设计提供新思路。     

基于CAN总线的FFU控制系统设计与实现

为实现对多风机过滤器单元(FFU)群控系统的有效控制,设计了一种基于CAN总线的FFU控制系统,该设计以dsPIC30F4012为控制核心,利用CAN总线组网技术,实现了对多FFU风机的远程监控制.阐述了该控制系统的组成和实现方法,并给出了软硬件设计.通过实验验证了该设计方案的正确性和可靠性.     

基于机器视觉的方便面包装品质检测系统设计

目的设计一套基于机器视觉的方便面包装品质检测系统,以解决人工检测人眼易产生疲劳和不稳定的问题,提高包装品质在线检测效率。方法给出方便面包装品质检测系统的整体设计方案,阐述硬件设计结构和软件设计流程,分析机器视觉检测系统的原理和过程。结果采用机器视觉的方便面包装品质检测系统具有较高的生产工艺识别率。结论该检测系统具有较低的过检率、漏检率,以及较高的检测效率,能够满足生产需求。