心电图信号的频域分析

提出了一种简便有效的、由心电图（ECG）曲线提取QRS-T复合波的新方法，从而获得P波（当房颤未发生时）或f波（当房颤时）；利用功率谱、自相关、互相关等信号处理技术，对它进行了处理和分析，特别是，比较了未房颤时和发生房颤时的相关信息的显著差别。     

心电图数据压缩技术

本文介绍了在计算机上实现的二种心电图数据压缩方法，并详述了每种压缩法对心电图压缩技术的压缩比、失真度的影响。     

A new ECG beat clustering method based on kernelized fuzzy c-means and hybrid ant colony optimization for continuous domains

The kernelized fuzzy c-means algorithm uses kernel methods to improve the clustering performance of the well known fuzzy c-means algorithm by mapping a given dataset into a higher dimensional space non-linearly. Thus, the newly obtained dataset is more likely to be linearly seprable. However, to further improve the clustering performance, an optimization method is required to overcome the drawbacks of the traditional algorithms such as, sensitivity to initialization, trapping into local minima and lack of prior knowledge for optimum paramaters of the kernel functions. In this paper, to overcome these drawbacks, a new clustering method based on kernelized fuzzy c-means algorithm and a recently proposed ant based optimization algorithm, hybrid ant colony optimization for continuous domains, is proposed. The proposed method is applied to a dataset which is obtained from MIT–BIH arrhythmia database. The dataset consists of six types of ECG beats including, Normal Beat (N), Premature Ventricular Contraction (PVC), Fusion of Ventricular and Normal Beat (F), Artrial Premature Beat (A), Right Bundle Branch Block Beat (R) and Fusion of Paced and Normal Beat (f). Four time domain features are extracted for each beat type and training and test sets are formed. After several experiments it is observed that the proposed method outperforms the traditional fuzzy c-means and kernelized fuzzy c-means algorithms.     

Event-driven,pattern-based methodology for cost-effective development of standardized personal health devices

Experiences applying standards in personal health devices (PHDs) show an inherent trade-off between interoperability and costs (in terms of processing load and development time). Therefore, reducing hardware and software costs as well as time-to-market is crucial for standards adoption. The ISO/IEEE11073 PHD family of standards (also referred to as X73PHD) provides interoperable communication between PHDs and aggregators. Nevertheless, the responsibility of achieving inexpensive implementations of X73PHD in limited resource microcontrollers falls directly on the developer. Hence, the authors previously presented a methodology based on patterns to implement X73-compliant PHDs into devices with low-voltage low-power constraints. That version was based on multitasking, which required additional features and resources. This paper therefore presents an event-driven evolution of the patterns-based methodology for cost-effective development of standardized PHDs. The results of comparing between the two versions showed that the mean values of decrease in memory consumption and cycles of latency are 11.59% and 45.95%, respectively. In addition, several enhancements in terms of cost-effectiveness and development time can be derived from the new version of the methodology. Therefore, the new approach could help in producing cost-effective X73-compliant PHDs, which in turn could foster the adoption of standards.     

Wearable Organic Electrochemical Transistor Array for Skin-Surface Electrocardiogram Mapping Above a Human Heart

Electrocardiogram (ECG) mapping can provide vital information in sports training and cardiac disease diagnosis. However, most electronic devices for monitoring ECG signals need to use multiple long wires, which limit their wearability and conformability in practical applications, while wearable ECG mapping based on integrated sensor arrays has been rarely reported. Herein, ultra-flexible organic electrochemical transistor (OECT) arrays used for wearable ECG mapping on the skin surface above a human heart are presented. QRS complexes of ECG signals at different recording distances and directions relative to the heart are obtained. Furthermore, the ECG signals are successfully analyzed by the devices before and after exercise, indicating potential applications in some sports training and fitness scenarios. The OECT arrays that can conveniently monitor spacial ECG signals in the heart region may find niche applications in wearable electronics and healthcare products in the future.     

多病床两级报警无线心电监护系统的设计

设计了一种多病床两级报警无线传输心电监护系统.说日月了系统的硬件电路设计和软件设计思想,重点介绍了心电监护终端的硬件设计和PC机集中监控中心的功能.系统的探测部分完成心电信号的数据采集、无线传输、心律失常实时分析、检测、一级报警功能,集中监护中心部分完成各病床病人心电信号的实时监测、数据存储、心电图显示、二级报警功能.     

结合数据融合和数据挖掘的医疗监护报警

介绍家庭远程医疗监护和咨询智能系统,它能自动进行监护数据分析及异常情况识别和网络报警、远程实时诊断。在心电信号分析方面,采用了一种基于最小均方差的自适应噪声滤除方法,介绍了QRS综合波和P波的检测方法及共时域特征的提取,以及基于小波分析的心电信号频域特征的提取。在结合数据融合和数据挖掘的医疗监护模型的建模方面,采用多层感知器网络和决策树方法建立报警决策器的模型。     

基于ATmega64的高分辨心电信号采集电路的研制

实时动态心电图仪一直是临床广泛应用的医疗器械之一,为使对心电信号(ECG)的采集和初步处理比传统测量方法更加准确可靠,利用USB串行通信和计算机组成了高智能化心电监护仪;该设计以ATmega64及高速16位ADC(AD7677)为核心,利用双极性肢体导联采集微弱电压经放大,带通滤波,工频肌电陷波后通过模数ADC(AD7677)进行采样,而研制了一套高分辨心电信号采集电路,数据最终送入计算机进行处理;结果表明心电信号纯净并可实时显示。     

一种抑制心电信号50Hz工频干扰的新方法

针对心电信号中50 Hz的工频干扰,在传统Levkov滤波法的基础上改进,将R波波峰临近几点拟合成折线,然后采用线性段的方法滤波。结果表明新方法在有效滤除R波附近工频干扰的同时,还较好的保留了有用信息。总体滤波速度较快,适合在嵌入式设备中使用。