可视心电监测听诊器的临床应用

目的　评价自行改进的可视心电监测听诊器临床应用的有效性和实用性。方法　对 12 0例院外急救 ,出诊转运及心脏介入术后接送的心脏病患者 ,分别用可视听诊器与自行改进的可视心电监测听诊器进行临床应用对比 ,观察心电信号灵敏度 ( >10～ 2 0mm/mv) ,心电图心房“P”波显示率 ,抗干扰程度 (受呼吸体位变动及胸廓影响 )及连续实时心电监测情况。结果　可视心电监测听诊器心电信号灵敏度 ,心电图“P”波显示率 ,抗干扰率均达到 95 %以上 ,各项指标明显高于可视听诊器 ,可视心电监测听诊器连接电极导联后 ,可进行连续实时心电监护。结论　可视心电监测听诊器除了明显增强抗干扰能力 ,提高心电信号灵敏度外 ,还具备进行连续实时心电监测的功能 ,起到了便携式微型心电监护仪作用 ,既可用于急救监护 ,保健医疗 ,又可用于缺乏心电监测的飞机 ,车船进行转送病人 ,指导抢救工作。     

便携式液晶显示心电监护仪的研制

作者研制了一种基于80C196KC单片机的液晶显示心电监护仪,可实现心电信号的实时采集、显示和存储,并具有心电参数计算和自动节律分析功能,分析结果可显示在液晶显示模块上或由语音提示.该机具有体积小、重量轻、便于携带的特点,非常适合于急救及野外环境下使用.     

基于Android平台心电采集与管理应用程序开发与研究

介绍了基于GoogleAndroid平台的心电实时测量与管理应用程序的一种实现方法,完成Android客户端采集显示、分析处理、存储、上传、查询等一系列心电数据操作功能,方便老年人在家中进行常规生理参数的检测,同时,专业医护人员也可利用该方案实现移动化办公。经测试验证,应用程序功能完善,运行稳定,可移植性强。     

心率变异性分析诊断心脏神经症的临床应用

目的　探讨心率变异性 (HRV)分析诊断心脏神经症的临床意义。方法　对 87例临床诊断心脏神经症的患者进行 2 4hHRV分析 ,以时域法参数与正常人对照 ,参照中华医学会心电生理和起搏分会心电学组推荐的 2 4hHRV分析参数中R R间期均值的标准差 (SDNN)指标对临床诊断心脏神经症进行评价。结果　心脏神经症组与对照组的HRV分析时域法各参数有极显著差异 (P <0 .0 0 1) ;心脏神经症组的SDNN全部 <14 0ms ,其中 10 0ms≤SDNN <14 0ms(轻度降低 )者 5 4例 ,占 62 .1% ;5 0ms≤SDNN <10 0ms(中度降低 )者 33例 ,占 37.9% ,SDNN <5 0ms(明显降低 )者为 0。结论　心脏神经症患者的HRV分析各参数明显低于正常人 ;HRV分析是判断心脏神经症患者自主神经功能的客观量化指标 ,亦可解释一系列自主神经功能紊乱的临床表现 ;SDNN参数在HRV分析时域法中代表性较好、敏感性高     

一种新型无线多参数心电监护系统及其临床实验

目的:介绍一种能适用于中小医院、社区及家庭的新型的便携式无线多参数监护系统及其临床实现。方法:系统采用集成度高、功能强大的PTR5000作为无线通信模块,降低了成本与功耗;数据接收机和计算机连接采用全速USB接口,使用灵活方便;实时监护软件采用win32多线程程序设计,能保证多床位数据的及时读取、处理及显示。临床实验选择心脏病住院患者20例,男12例,女8例,年龄53岁～78岁,同时监测心电图波型及心率、呼吸频率、体温波型,并将心率自动计算与人工手动计算结果进行对比分析;体温检测结果与高精度电子体温计体表测量值对比分析。结果:能同时监护4个床位患者,实时显示心电波形及心电参数计算、心律失常分析结果,且波形清晰、平滑,很容易的分辨出P、Q、R、S、T波,符合医生的视觉要求及美观感。心率、呼吸频率、体温等参数计算与人工手动计算结果比较无统计学差别(P>0.05)。结论:该仪器可应用于中、小医院、社区及家庭高危人群监护。     

微型动态心电记录仪在检测异常心电图中的价值

目的　了解两种记录仪在心电图异常检测中的价值。方法　使用微型动态心电记录仪与常规 12导联心电图(ECG)检测 2 60例患者并对结果进行比较。结果　微型动态心电记录仪异常心电图检出率 (73 .85 % )显著高于常规心电图记录仪 (2 4.2 3 % ) ,χ2 =12 8.85 ,P <0 .0 1,而异常心电图类型以ST -T改变、心律失常尤为明显 (P均 <0 .0 1)。结论　微型动态心电记录仪检测心电图异常的价值明显优于常规心电图。     

频域心电图在冠心病诊断中的应用

频域心电图(FCG)是一种无创伤性心电检测新技术,其特点是采用现代信息处理的方法,显示心电信号的频域特征,并对所选的两个导联心电信号的频率、振幅、相位和时差等进行多参数的相关分析。本文对79例冠心病患者和33例健康者进行了频域心电图分析,探讨其对冠心病的诊断价值。     

缺血性脑血管病的颅内血管支架治疗

1　诊断方法依据临床表现及辅助检查确诊。1 1　脑供血动脉超声检查 :联合B型超声成像与经颅多普勒检查检测脑供血动脉狭窄 ,其中经颅多普勒是目前最广泛应用的检测脑供血动脉狭窄的无创检测方法。B型超声扫描可实时的显示动脉的纵向剖面 ,多普勒检查有助于评价颈动脉的血流状况 ,基于预先设定的参数 ,评价颈动脉狭窄程度。1 2　CT血管造影 (CTA) :主要了解颈动脉系统颅外段有无狭窄、钙化斑块及其程度、范围。超声检查方法如不能肯定 ,可补充进行CTA检查。CTA可以精确地显示血管腔的直径 ,如果需要的话 ,在窗宽 85 0HU、窗位 2 0 0H…     

微型心电记录器的临床应用

<正> 微型心电记录器(MECGR)是一种由受检者携带,其本人或他人操纵的实时记录一短程心电活动的超小型记录器。本文就其临床应用问题作一简要介绍。一、各种国产MECGR的主要异同点共同点:①可记录不同环境和状态下的心电动态变化;②由受检者根据病情,实时记录最为可疑的短暂心电活动异常;③操作技术简单,回放只需一台普通心电图机。异点:①记录的心电信息量不同,从40～80秒不等;②抗干扰性不同;③形状,大小不同,以致携带方便程度不一。二、MECGR与Holter的比较①总信息量较小,不能反映24h总心率、最高和最低心率;③不能显示心率和ST-T的动态趋势;③单通道记录;④对无症状受检者     

Localizing the focus of ischemic stroke with near infrared spectroscopy

目的　用大鼠大脑中动脉梗塞模型评价血红蛋白近红外光谱 (NIRS)变化特征 ,实现对大脑梗塞灶的定位诊断。方法　计算并搭建了双波长 (85 0nm和 76 0nm)NIRS拓扑系统。用 2 0只SD大鼠建立大脑中动脉梗塞模型 ,并对梗塞灶成像 ;然后用磁共振 (MRI)和化学染色方法对同一只大鼠梗塞灶成像 ,并比较不同技术显示的梗塞灶位置和面积。结果　重建的NIRS拓扑图显示大鼠大脑左侧皮层有一低的光密度区 ,平均梗塞面积为 19 5 0mm2 (19 5 0± 0 35mm2 ,n =2 0 ) ;染色的解剖样品显示平均梗塞面积为 18 4 6mm2 (18 4 6± 0 38mm2 ,n =2 0 ) ;MRI显示平均梗塞面积为 2 0 71mm2 (2 0 71± 0 2 7mm2 ,n =2 0 ) ,三种技术显示的平均梗塞面积无显著性差异 (F(2 ,5 7) =2 4 7,P >0 0 5 )。NIRS与MRI、解剖样品之间相关系数分别为 (r=0 82 ,P <0 0 5 )、(r =0 89,P <0 0 1)。同时 ,NIRS拓扑图显示的梗塞灶的位置和几何形状也为同一只大鼠的MRI、解剖样品所证实。结论　研究结果提示 ,NIRS可以实时跟踪各种因素引起的大脑皮层血流变化。     

网络化多参数体征监测仪的设计

目的：设计一种基于无线传感网络的多参数体征监测仪,取代传统有线式数据传输,提高便携式心电监测仪的适应能力。方法系统采用Zigbee无线传感技术,对人体心电、血氧饱和度、无创血压等生命体征参数进行动态监测,并通过小波变换对心电监测算法进行改进,提高心电监测的分辨率和精准度。结果实现了各种医疗监测模块的即插即用功能,以及特征监测数据的网络化传输。结论网络化心电检测仪结构简单、精度高、系统功耗低。     

An IoT-cloud Based Wearable ECG Monitoring System for Smart Healthcare

Public healthcare has been paid an increasing attention given the exponential growth human population and medical expenses. It is well known that an effective health monitoring system can detect abnormalities of health conditions in time and make diagnoses according to the gleaned data. As a vital approach to diagnose heart diseases, ECG monitoring is widely studied and applied. However, nearly all existing portable ECG monitoring systems cannot work without a mobile application, which is responsible for data collection and display. In this paper, we propose a new method for ECG monitoring based on Internet-of-Things (IoT) techniques. ECG data are gathered using a wearable monitoring node and are transmitted directly to the IoT cloud using Wi-Fi. Both the HTTP and MQTT protocols are employed in the IoT cloud in order to provide visual and timely ECG data to users. Nearly all smart terminals with a web browser can acquire ECG data conveniently, which has greatly alleviated the cross-platform issue. Experiments are carried out on healthy volunteers in order to verify the reliability of the entire system. Experimental results reveal that the proposed system is reliable in collecting and displaying real-time ECG data, which can aid in the primary diagnosis of certain heart diseases.     

Development of a Portable Linux-Based ECG Measurement and Monitoring System

Journal of Medical Systems - This work presents a portable Linux-based electrocardiogram (ECG) signals measurement and monitoring system. The proposed system consists of an ECG front end and an...     

SMART—An Integrated Wireless System for Monitoring Unattended Patients

Monitoring vital signs and locations of certain classes of ambulatory patients can be useful in overcrowded emergency departments and at disaster scenes, both on-site and during transportation. To be useful, such monitoring needs to be portable and low cost, and have minimal adverse impact on emergency personnel, e.g., by not raising an excessive number of alarms. The SMART (Scalable Medical Alert Response Technology) system integrates wireless patient monitoring (ECG, SpO₂), geo-positioning, signal processing, targeted alerting, and a wireless interface for caregivers. A prototype implementation of SMART was piloted in the waiting area of an emergency department and evaluated with 145 post-triage patients. System deployment aspects were also evaluated during a small-scale disaster-drill exercise.     

Evaluation of Digital Compressed Sensing for Real-Time Wireless ECG System with Bluetooth low Energy

In this paper, a wearable and wireless ECG system is firstly designed with Bluetooth Low Energy (BLE). It can detect 3-lead ECG signals and is completely wireless. Secondly the digital Compressed Sensing (CS) is implemented to increase the energy efficiency of wireless ECG sensor. Different sparsifying basis, various compression ratio (CR) and several reconstruction algorithms are simulated and discussed. Finally the reconstruction is done by the android application (App) on smartphone to display the signal in real time. The power efficiency is measured and compared with the system without CS. The optimum satisfying basis built by 3-level decomposed db4 wavelet coefficients, 1-bit Bernoulli random matrix and the most suitable reconstruction algorithm are selected by the simulations and applied on the sensor node and App. The signal is successfully reconstructed and displayed on the App of smartphone. Battery life of sensor node is extended from 55 h to 67 h. The presented wireless ECG system with CS can significantly extend the battery life by 22 %. With the compact characteristic and long term working time, the system provides a feasible solution for the long term homecare utilization.     

Towards Improved Healthcare Performance: Examining Technological Possibilities and Patient Satisfaction with Wireless Body Area Networks

This paper investigates the benefits of using less intrusive wireless technologies for heart monitoring. By replacing well established heart monitoring devices (i.e. Holter) with wireless ECG based Body Area Networks (BAN), improved healthcare performance can be achieved, reflected in (1) high quality ECG recordings during physical activities and (2) increased patient satisfaction. A small scale clinical trial was conducted to compare both technologies and the results illustrate that the wireless ECG monitor was able to detect ECG signals intended for arrhythmia diagnostics. Furthermore, from a patient’s perspective, both technologies were evaluated using three dimensions, namely; hygienic aspects, physical activity, and skin reactions. Results demonstrate that the wireless ECG BAN showed better performance, especially regarding the hygienic aspects. It was also favourable for use during physical activities, and the signal quality of the wireless sensor system demonstrated good performance regarding signal noise and artefact disturbances. This paper concludes that wireless cardiac monitoring systems have significant benefits from a patient’s perspective, and further clinical trials should be conducted to further evaluate the new ECG based BAN system, to identify the possibility of widespread adoption and utilisation of wireless technology for arrhythmia diagnostics.     

基于TMS320DM368处理器的便携式内窥镜视频系统的电路设计

目的：设计一种便携式内窥镜视频系统的控制电路。方法以TMS320DM368处理器为主控制器,嵌入式Linux为操作系统,利用MT9P301图像传感器采集图像。通过视频输入及输出电路、存储单元电路、按键显示电路、LED照明电路、WIFI电路等把获得的图像显示在LCD上,并通过WIFI同步显示在HDTV上。系统采用锂电池进行供电,并可通过市电或太阳能进行充电。结果经过临床测试,该电路可实现内窥镜视频系统图像的拍摄、缩放、存储、传输等功能。结论电路性能稳定,功耗低、自我续航能力强,可满足便携式内镜视频系统的运需求。     

Fetal Electrocardiogram Extraction and Analysis Using Adaptive Noise Cancellation and Wavelet Transformation Techniques

Birth defect-related demise is mainly due to congenital heart defects. In the earlier stage of pregnancy, fetus problem can be identified by finding information about the fetus to avoid stillbirths. The gold standard used to monitor the health status of the fetus is by Cardiotachography(CTG), cannot be used for long durations and continuous monitoring. There is a need for continuous and long duration monitoring of fetal ECG signals to study the progressive health status of the fetus using portable devices. The non-invasive method of electrocardiogram recording is one of the best method used to diagnose fetal cardiac problem rather than the invasive methods.The monitoring of the fECG requires development of a miniaturized hardware and a efficient signal processing algorithms to extract the fECG embedded in the mother ECG. The paper discusses a prototype hardware developed to monitor and record the raw mother ECG signal containing the fECG and a signal processing algorithm to extract the fetal Electro Cardiogram signal. We have proposed two methods of signal processing, first is based on the Least Mean Square (LMS) Adaptive Noise Cancellation technique and the other method is based on the Wavelet Transformation technique. A prototype hardware was designed and developed to acquire the raw ECG signal containing the mother and fetal ECG and the signal processing techniques were used to eliminate the noises and extract the fetal ECG and the fetal Heart Rate Variability was studied. Both the methods were evaluated with the signal acquired from a fetal ECG simulator, from the Physionet database and that acquired from the subject. Both the methods are evaluated by finding heart rate and its variability, amplitude spectrum and mean value of extracted fetal ECG. Also the accuracy, sensitivity and positive predictive value are also determined for fetal QRS detection technique. In this paper adaptive filtering technique uses Sign-sign LMS algorithm and wavelet techniques with Daubechies wavelet, employed along with de noising techniques for the extraction of fetal Electrocardiogram.Both the methods are having good sensitivity and accuracy. In adaptive method the sensitivity is 96.83, accuracy 89.87, wavelet sensitivity is 95.97 and accuracy is 88.5. Additionally, time domain parameters from the plot of heart rate variability of mother and fetus are analyzed.     

A Simple Computer-Based Measurement and Analysis System of Pulmonary Auscultation Sounds

Listening to various lung sounds has proven to be an important diagnostic tool for detecting and monitoring certain types of lung diseases. In this study a computer-based system has been designed for easy measurement and analysis of lung sound using the software package DasyLAB. The designed system presents the following features: it is able to digitally record the lung sounds which are captured with an electronic stethoscope plugged to a sound card on a portable computer, display the lung sound waveform for auscultation sites, record the lung sound into the ASCII format, acoustically reproduce the lung sound, edit and print the sound waveforms, display its time-expanded waveform, compute the Fast Fourier Transform (FFT), and display the power spectrum and spectrogram.