基于笔记本计算机的心音分析仪

基于笔记本计算机的心音分析仪由心音传感器、心音信号预处理盒,笔记本计算机、打印,音箱和心音信号处理软件组成。它的开发目的是充分利用笔记本计算机的便携特点和强大功能。该系统在Ｗｉｎｄｏｗｓ９５操作系统下用ＶＩＳＵＡＬＢＡＳＩＣ编程。     

Analog signal processing of eye movements for on-line digital computer analysis.

An analog signal processing circuit is described which allows accurate measurement of the amplitude, velocity, and interval of both fast and slow components of eye movements. This system, in conjunction with an on-line minicomputer, can measure amplitudes up to 32° and velocity to 640° per sec. The analog signal processing methods and technique for achieving a reliable output signal are discussed. Data obtained from human and animal subjects are portrayed.     

Zur Methodik der kontinuierlichen Bestimmung der Phasenbeziehung zwischen Herzschlag und Atmung

A simple method for the continuous analysis of the phase relation between heart beat and respiration is described. By means of an analog computer the timing of the R wave of the ECG within the respiratory cycle is graphically displayed. In contrast to other investigations, the onset of the inspiration is used as starting signal. The results obtained with the analog computer were completed by a digital computer program, which allowed in addition to calculate histograms of the events. In order to evaluate our method we used an analog model of two coupled oscillators. Responses obtained at different coupling characteristics were compared with measurements in four subjects. The results indicate a mutual interaction between heart action and respiration as cause of the coupling of these two systems.     

An application of reconfigurable technologies for non-invasive fetal heart rate extraction

This paper illustrates the use of a reconfigurable system for fetal electrocardiogram (FECG) estimation from mother's abdomen ECG measurements. The system is based on two different reconfigurable devices. Initially, a field-programmable analog array (FPAA) device implements the analog reconfigurable preprocessing for ECG signal acquisition. The signal processing chain continues onto a field-programmable gate array (FPGA) device, which contains all the communication and interfacing protocols along with specific digital signal processing blocks required for fundamental period extraction from FECG waveforms. The synergy between these devices provides the system the ability to change any necessary parameter during the acquisition process for enhancing the result. The use of a FPGA allows implementing different algorithms for FECG signal extraction, such as adaptive signal filtering. Preliminary works employ commercially available development platforms for test experiments, which suffice for the processing of real FECG signals from biomedical databases, as the presented results illustrate.     

VEGF-PLCgamma1 pathway controls cardiac contractility in the embryonic heart

The strength of the heart beat can accommodate in seconds to changes in blood pressure or flow. The mechanism for such homeostatic adaptation is unknown. We sought the cause of poor contractility in the heart of the embryonic zebrafish with the mutation dead beat. We find through cloning that this is due to a mutation in the phospholipase C gamma1 (plcgamma1) gene. In mutant embryos, contractile function can be restored by PLCgamma1 expression directed selectively to cardiac myocytes. In other situations, PLCgamma1 is known to transduce the signal from vascular endothelial growth factor (VEGF), and we show here that abrogation of VEGF also interferes with cardiac contractility. Somewhat unexpectedly, FLT-1 is the responsible VEGF receptor. We show that the same system functions in the rat. Blockage of VEGF-PLCgamma1 signaling decreases calcium transients in rat ventricular cardiomyocytes, whereas VEGF imposes a positive inotropic effect on cardiomyocytes by increasing calcium transients. Thus, the muscle of the heart uses the VEGF-PLCgamma1 cascade to control the strength of the heart beat. We speculate that this paracrine system may contribute to normal and pathological regulation of cardiac contractility.     

A system for providing an on-line analogue display of beat-by-beat cardiac output

A system for an on-line analogue display of beat-by-beat cardiac output and other cardiovascular functions is described. The phasic aortic blood flow signal, derived from an electromagnetic flowmeter with the flow probe implanted around the ascending aorta, drives a multi-channel recorder with a combination of associated signal conditioning input couplers and peripheral electronic circuitry, to provide a continuous analogue display of beat-by-beat phasic stroke volume, integrated stroke volume, heart rate, and cardiac output. These cardiovascular functions, which permit instantaneous on-line feedback of these parameters, were all derived from the single aortic flow measurement.     

Automated data collection and presentation in the operating room

An 'Operating Room Data Integration System', is described which is used to collect, present and archive all important physiological parameters during open heart surgery. The system requires very little attention, and provides an easy to understand and coherent interface to the user. The system is adaptable to a large extend and thus data can be presented to the user in a manner, with which he or she is already familiar. Simple drivers can be written to enable connection of the system to almost any other piece of medical equipment, if the latter provides an analog or digital, output signal. Automatic logging of the acquired signals is then possible.     

An arrhythmia classification system based on the RR-interval signal

OBJECTIVE: This paper proposes a knowledge-based method for arrhythmic beat classification and arrhythmic episode detection and classification using only the RR-interval signal extracted from ECG recordings. METHODOLOGY: A three RR-interval sliding window is used in arrhythmic beat classification algorithm. Classification is performed for four categories of beats: normal, premature ventricular contractions, ventricular flutter/fibrillation and 2 degrees heart block. The beat classification is used as input of a knowledge-based deterministic automaton to achieve arrhythmic episode detection and classification. Six rhythm types are classified: ventricular bigeminy, ventricular trigeminy, ventricular couplet, ventricular tachycardia, ventricular flutter/fibrillation and 2 degrees heart block. RESULTS: The method is evaluated by using the MIT-BIH arrhythmia database. The achieved scores indicate high performance: 98% accuracy for arrhythmic beat classification and 94% accuracy for arrhythmic episode detection and classification. CONCLUSION: The proposed method is advantageous because it uses only the RR-interval signal for arrhythmia beat and episode classification and the results compare well with more complex methods.     

Computer analysis of frequency spectrum of a phonothyreogram

An analysis of phonothyreograms and phonocardiograms was made with the aid of an ND minicomputer and a CYBER 73 computer system using an electrocardiogram signal as a reference time signal. Programs were written to estimate the power spectral density function of these signals. In patients with Graves' disease and those with nodular goiter the intrinsic thyroid murmur was found to differ from the sound transmitted from the heart in healthy subjects by a large contribution of frequencies in the 250–750 Hz range, this factor being particularly pronounced in patients with Graves' disease.     

Reliable and Precise Identification of R-Waves in the EKG with a Simple Peak Detector

A simple instrument is described which reliably and accurately identifies R-waves in the EKG signal. These R-waves are obtained by “Modified Lead 2′’and other similar methods. By using a peak detector instead of a Schmitt trigger, three important advantages are obtained. If the instrument is connected to a time interval counter, reliable and accurate acquisition of heart beat interval and heart rate data may be achieved with a relatively simple operation.     

An online sampled-data waveform control system

The study of frequency-discrimination mechanisms in hearing could be facilitated if it were possible to force the basilar membrane in the cochlea to vibrate with specified complex motions. It is difficult to remotely produce forcing functions suitable for the transient analysis of neural excitation mechanisms at points on the basilar membrane. The difficulties have been overcome with the use of a digital minicomputer system incorporating an independent digital-analogue generator. This control system pre-equalises the input signal for the combined transmission characteristics of all frequency-dependent stages (electronic, acoustic and mechanical) up to the basilar membrane or other point whose motion is to be controlled. Sampled data from this output constitutes feedback to the computer which synthesises a corrected input-drive waveform. The specified complex periodic motion is produced iteratively, enabling the control system to function independently of nonlinearities at any stage. An integral feature of the system is the phase-locked detection of the output signal which may be buried in noise.     

QRS复合波检测技术综述

心电图是诊断各种心脏疾病的一个重要手段,而准确识别QRS复合波也是多种自动化心电图分析方法的一个前 提。检测QRS复合波的传统方法主要有差分阈值算法、双阈值检测算法、经验模态分解法、小波变换算法等,这些算法的 主要步骤包括对心电信号进行预处理、特征提取和检测等,对心电信号质量要求比较高,且通用性不是很强。相对于传统 方法检测QRS复合波,人工智能的发展特别是深度学习的出现为QRS复合波检测提供一种新的方法,利用深度学习可自 主提取QRS复合波特征信息,从而进行精准定位,相比传统方法,鲁棒性更好,对信号质量不佳的数据检测效果更好。本 研究主要对用于QRS复合波预处理以及检测的技术进行综述,并对检测技术的发展进行展望。     

The comparison of different feed forward neural network architectures for ECG signal diagnosis

The electrocardiograms (ECGs) record the electrical activity of the heart and are used to diagnose many heart disorders. This paper proposes a two-stage feed forward neural network for ECG signal classification. The research is aimed at the design of an intelligent ECG diagnosis tool that can recognise heart abnormalities while reducing the complexity, cost, and response time of the system. A number of neural network architectures are designed and compared for their ability to classify six different heart conditions. Two network architectures based on one stage and two stage feed forward neural networks are chosen for this investigation. The training and testing ECG signals are obtained from MIT-BIH database. The network inputs are comprised of 12 ECG features and 13 compressed components of each heart beat signal. The performance of the different modules as well as the efficiency of the whole system is presented. Among different architectures, a proposed multi-stage network named NET_BST possesses the highest recognition rate of around 93%. Therefore, this network proves to be a suitable candidate in ECG signal diagnosis systems.     

A unique, versatile, real-time software package for controlling a Nicolet 1074 averager from a laboratory minicomputer

The use and operation of a newly-developed real-time software interface between a Nicolet 1074 digital signal averager and PDP-11/34A minicomputer is described. The system was developed for rapid, iterative, simultaneous measurements and correlations between electrical membrane properties of living cells and optically measured intracellular chemical changes. When such hard-wired averagers are interactively interfaced to minicomputers, the combination presents an overwhelmingly powerful experimental tool and enables data manipulations not performable by the hard-wired signal averager alone. Both the necessary hardware modifications to the standard Nicolet C-11 interface, major controlling assembly language software programs, and the versatility and adaptability of the system to a wide variety of laboratory applications are described.     

基于极限学习机的室性早搏判别算法的实现

室性早搏是常见的心律异常疾病,给人的生命带来威胁,准确的心律异常诊断对于帮助人们预防心血管疾病起到重要的作用。以MIT-BIH心律异常数据库中的数据作为分析对象,提出一种基于极限学习机算法的诊断方法,主要包括信号预处理、特征提取和分类,实现心电信号室性早搏异常的判别。采用小波变换结合形态学算法,对信号进行预处理,去除干扰,得到纯净的心电信号。通过K-means聚类算法提取QRS波群等特征参数,根据这些参数建立正常窦性心律和室性早搏的正样本和预测样本,再结合极限学习机分类器进行样本训练匹配和分类识别。选取1 260个周期信号进行实验,结果表明,该算法能准确诊断出室性早搏异常,最终阳性平均检测率达到95%,平均灵敏度达到96%。该算法相比其他算法,在识别精度相当的情况下,可极大提高算法的实时性,具有很高的研究价值,同时在移动医疗和临床医疗方面也具有一定的实用价值。     

Long-Term Mathematical Model Involving Renal Sympathetic Nerve Activity,Arterial Pressure,and Sodium Excretion

This paper presents a physiological long-term model of the cardiovascular system. It integrates the previous models developed by Guyton, Uttamsingh and Coleman. Additionally it introduces mechanisms of direct effects of the renal sympathetic nerve activity (rsna) on tubular sodium reabsorption and renin secretion in accordance with experimental data from literature. The resulting mathematical model constitutes the first long-term model of the cardiovascular system accounting for the effects of rsna on kidney functions in such detail. The objective of developing such a model is to observe the consequences of long-term rsna increase and impairment of rsna inhibition under volume loading. This model provides an understanding of the rsna-related mechanisms, which cause mean arterial pressure increase in hypertension and total sodium amount increase (sodium retention) in congestive heart failure, nephrotic syndrome and cirrhosis.     

A computerized device for long-term measurements of the contraction frequency of cultured rat heart cells under stable incubating conditions

A new computer-controlled measurement system for assessing beat rates of spontaneously contracting cultured heart cells is presented. The system overcomes several disadvantages of established techniques such as: (i) lack of precise control of the environment (pH, temperature, humidity); (ii) restriction to the measurement of one culture at a time; (iii) inability to obtain long-term measurements. The beat rate is recorded by subjecting monolayer cultures to dark field illumination and recording contraction-related changes in light scattering. A maximum of environmental stability is achieved because measurements are performed in the incubator. Beat rates of up to 16 individual culture dishes can be assessed repeatedly during freely selectable time intervals. Control of the experiments, data acquisition and data analysis are carried out by a computer. The specific advantage of the method lies in the ability to measure the beat rate of several culture dishes continuously over time intervals limited only by the viability of the cultures, i.e. up to several weeks.     

A system for interactive film analysis.

An interactive, minicomputer system has been constructed for analyzing dynamic phenomena recorded on movie film in a developmental biology laboratory. The minicomputer interfaces a stop-motion, variable speed projector, a digitizing pen, and real-time graphics display equipment. An analyst uses the pen to digitize features in a film, e.g. by following a cell. A computer-generated animation portraying all data entered is superimposed on the film image and synchronized with it. Noteworthy system features include: image overlays on a large screen, data entry with the projector running, large data capacity, computer control of the projector, and convenient data entry tools.     

PC-based system for collection and analysis of physiological data

A personal computer based system for data acquisition and analysis appropriate to physiological experiments is described in detail. The system is independent of the details of the analog signal generation. The software, written in C, is modular and easily portable to other PC systems. The system is capable of: (a) sampling many analog signals at an appropriate rate (100 Hz), (b) storing large quantities of digitized data, (c) analysing digitized waveforms to obtain signal parameters, and (d) storing signal parameters in a format suitable for statistical analysis. Computer processed cardiopulmonary data are compared with data derived from standard ICU equipment.     

Computer analysis of physiologic signals in a cardiovascular research laboratory

A comprehensive computer program which provides immediate computation and feedback has been developed for data acquisition and analysis of signals in a cardiovascular animal laboratory. The system is based on a microcomputer equipped with analog-to-digital converter and supports function modules which digitize, filter, and differentiate up to 8 simultaneously sampled cardiovascular signals. The program detects, analyses, and plots incoming and averaged beats. Beat-by-beat signal averaging for each channel is performed and cardiac cycles are partitioned automatically. For each cardiac and average cycle the amplitude at 6 physiologic fiducial markers are measured and derived calculations are made. Channel vs channel plots and loop area measurements are also computed and displayed. The computer algorithms have been shown to give accurate, precise, and reproducible results when tested on canine cardiovascular data. Also, it has been demonstrated that signal averaging is an appropriate analysis technique for cardiovascular signals.