Application of Improved Wavelet Threshold in Denoising of ECG Signals / 中国医疗器械杂志

The ECG signal is susceptible to interference from the external environment during the acquisition process, affecting the analysis and processing of the ECG signal. After the traditional soft-hard threshold function is processed, there is a defect that the signal quality is not high and the continuity at the threshold is poor. An improved threshold function wavelet denoising is proposed, which has better regulation and continuity, and effectively solves the shortcomings of traditional soft and hard threshold functions. The Matlab simulation is carried out through a large amount of data, and various processing methods are compared. The results show that the improved threshold function can improve the denoising effect and is superior to the traditional soft and hard threshold denoising.

Development of a Wearable Wireless ECG Monitoring System with Ultra-low Power Consumption / 中国医疗器械杂志

This study describes the development of a wireless and wearable ECG monitoring system with ultra-low power consumption. The system is mainly composed of a connection part of an ECG electrode sticker, an electrocardiogram collecting part, a data storage part, a Bluetooth main control unit, a charging module, a voltage regulator and a lithium battery. The low-power ECG acquisition chip ADS1292R and the ultra-low-power Bluetooth microcontroller nRF51822 together constitute the ECG signal acquisition and wireless data communication part. The collected ECG signals can be sent to the mobile APP through the Bluetooth function provided by the MCU, and can completly display and analysis to achieve low power system. After testing, the system power consumption is only (3.7 V×2.87 mA)10.619 mW, and if it is optimized, it can further reduce power consumption, therefore, the system design can have good applicability.

Design of Portable Fuzzy Diagnosis Instrument for ECG Signal Based on Internet of Things / 中国医疗器械杂志

OBJECTIVE@#A method for dynamically collecting and processing ECG signals was designed to obtain classification information of abnormal ECG signals.@*METHODS@#Firstly, the ECG eigenvectors were acquired by real-time acquisition of ECG signals combined with discrete wavelet transform, and then the ECG fuzzy information entropy was calculated. Finally, the Euclidean distance was used to obtain the semantic distance of ECG signals, and the classification information of abnormal signals was obtained.@*RESULTS@#The device could effectively identify abnormal ECG signals on an embedded platform based on the Internet of Things, and improved the diagnosis accuracy of heart diseases.@*CONCLUSIONS@#The fuzzy diagnosis device of ECG signal could accurately classify the abnormal signal and output an online signal classification matrix with a high confidence interval.

Monitoreo ambulatorio y generación de alertas tempranas ante anomalías cardiacas usando dispositivos móviles / Ambulatory monitoring and early warning generation of cardiac anomalies using mobile devices / Monitoramento ambulatorial e geração de aviso prévio de anomalias cardíacas usando dispositivos móveis

Resumen En este artículo se presenta un sistema portátil para el monitoreo ambulatorio del ritmo cardiaco y la detección temprana de las arritmias cardiacas de mayor riesgo. El sistema consta de un sensor con tres electrodos superficiales para la captura de la señal ECG, la cual se transmite vía Bluetooth a un dispositivo móvil con Android, en donde se realiza el análisis de la señal capturada durante lapsos de 5 s. El sistema propuesto distingue entre Ritmo Normal [Ritmo Sinusal - RS), Taquicardia Ventricular [TV), Fibrilación Ventricular [FV) y Asistolia, con una precisión del 100%, 55%, 75% y 90% respectivamente. Sin embargo, el sistema puede recuperarse de los errores rápidamente en el análisis de la trama subsecuente. Este trabajo se centra en el uso de dispositivos móviles de uso cotidiano, multitarea y de fácil acceso, implementando algoritmos en el dominio del tiempo para la extracción de parámetros, los cuales son idóneos para ser usados en aplicaciones móviles principalmente por su baja carga computacional y posibilidad de ejecución en tiempo real, permitiendo la detección de anomalías cardiacas de forma automática y rápida sin la necesidad de una supervisión constante por parte de un especialista para el análisis preliminar.

Abstract This paper presents a portable system for ambulatory heart rate monitoring and early detection of cardiac arrhythmias at high risk. The system consists of a sensor with three surface electrodes to capture the ECG signal, which is transmitted via bluetooth to a mobile device with Android, where the analysis is performed of the acquired signal during a time of 5 s. The proposed system distinguishes between Normal Rhythm [Rhythm Sinus - RS), Ventricular Tachycardia [VT), Ventricular Fibrillation [VF) and Asystole with an accuracy of 100%, 55%, 75% and 90% respectively. However, the system can quickly recover from errors in the subsequent analysis frame. This work focuses on using regular mobile devices which have multitasking and easy access characteristics, implementing algorithms in time domain for extracting parameters that are suitable to use in mobile applications, mainly because of their low computational load and possibility of execution in real time, allowing the detection of cardiac abnormalities automatically and quickly without the need of constant supervision by a specialist for preliminary analysis.

Resumo Neste artigo se apresenta um sistema portátil para o monitoramento da freqüência cardíaca ambulatorial e detecção precoce das arritmias cardíacas de mais risco. O sistema possui um sensor com três eletrodos superficiais para pegar o sinal ECG, o qual é transmitido via Bluetooth para um dispositivo móvel com Android, onde se faz a análise do sinal capturado durante um período de 5 s. O sistema proposto distingue entre Normal Ritmo [Ritmo Sinusal - RS), Taquicardia Ventricular [TV), Fibrilação Ventricular [FV) e Assistolia, com uma precisão do 100%, 55%, 75% e 90%, respectivamente. Porém, o sistema pode - se recuperar rapidamente dos erros na análise do quadro subsequente. Este trabalho centra-se no uso de dispositivos móveis de utilização diária, multitarefa e utilização acessível, implementação de algoritmos no domínio do tempo para a extração de parâmetros que são adequados para utilização em aplicações móveis, principalmente pela baixa carga computacional e possibilidade de execução em tempo real, permitindo a detecção de anormalidades cardíacas numa forma automática e rápida sem a necessidade de um controlo constante por um especialista para análise preliminar.

Design and Implementation of Portable Abnormal ECG Signal Analysis Instrument Based on Feature Classifcation / 中国医疗器械杂志

OBJECTIVES@#To collect and analyze the ECG signal in real time, the analog filter and the signal amplifier were used to construct the abnormal signal acquisition and classification system.@*METHODS@#The ARM10E processor was used to detect the signal shape and QRS complex wave. Based on the Poincare support vector machine, the feature set was extracted from the training data set to construct the heart disease classifier, and the clinical classification model was given.@*RESULTS@#The device effectively reduces computational complexity, improves processor speed, real-time acquisition and diagnoses heart disease.@*CONCLUSIONS@#Portable ECG devices can capture suspected waveforms of abnormal signals, establish and evaluate high quality signals, reduce patient on-line waiting time, and facilitate early diagnosis and recognition of heart disease.

ECG signals processing and transmission system based on virtual instrument and remote network / 医疗卫生装备

Objective To develope a realtime system for ECG signals acquisition,amplification and network transmission.Methods The raw noisy ECG signals underwent gain amplification,denoising and filtering by a system developed by virtual instrument and LabVIEW,and network component programming was carried out based on TCP/IP.Then the processed ECG signals were transmitted to remote terminals with dual communication model.Results The system behaved well in easy operation,high reliability and man-machine interface,and could be used to realize remote realtime transmission and browsing of ECG signals between the hospital and medical communities.Conclusion The system may be a choice for ECG signals remote acquisition and transmission,and provides references for the development of telemedicine software.

Fast-implementation of correlation dimension of ECG signal base on LabVIEW / 中国医学装备

Objective:To research a fast-implementation method of correlation dimension of ECG signal base on LabVIEW.Methods: In this paper, acquisition ,display and processing of ECG signal were implemented through applied PCI-6023E as hardware and applied graphical programming language LabVIEW as development software. And then through software programming to realize fast calculation for correlation dimension of ECG signal.Results: This method was used to analyze and calculate the correlation dimension of ECG between patients with coronary heart disease and healthy people. And the experiment indicated that it can fast and reliably calculate the correlation dimension, and the correlation dimension of patients with coronary heart disease was obviously lower than that of healthy people.Conclusion: The correlation dimension system of ECG signal based on LabVIEW can realize the fast calculation of correlation dimension of ECG signal, and solve the two problems that heart rate variability (HRV) information are difficultly extracted from ECG signal and the extracted useful information are inadequate. Therefore, it provides important reference information for clinical diagnosis and treatment.

Continuous measurement of arterial blood pressure based on pulse wave signal and vessel elastic chamber model / 医用生物力学

Objective An arterial blood pressure fitting method, based on pulse wave signal and vessel elastic chamber model, was researched and implemented to meet the requirement of continuous blood pressure (BP) measurement in health care. Methods Photoplethysmography (PPG) signal, electrocardiograph (ECG) signal and BP data of the subjects were collected by a self developed wearable physiological monitoring system. In accordance with the temporal relation between ECG and PPG signals, the equation of regression analysis on systolic BP value and pulse wave transient time (PWTT) was deduced, and the diastolic BP measurement was achieved by coefficients analysis on PPG wave and parameter calculation on blood vessel single elastic chamber model. Results The experiment results showed that the mean difference and the standard deviation of the method were （0.51±0.74) kPa［(384±5.54) mmHg］, reaching the standard (0.665±1.064) kPa［(5±8) mmHg］ proposed by Association for the Advancement of Medical Instrumentation (AAMI). Conclusions Human blood pressure can be estimated by the pulse wave signal and elastic chamber model, which provides a new method for the continuous blood pressure measurement.

A Belt-type Biomedical Mobile Device / 대한의료정보학회지

OBJECTIVE: To investigate a belt-type, biomedical mobile device capable of measuring patients' biomedical signals and sending the biomedical data to a remote medical server. This device was designed to measure and record ECG and motion signals continuously for a moving subject and, on in the event of an emergent situation, to notify a remote doctor of the situation by transmitting data on the emergent situation to a remote server through a CDMA network. METHODS: The developed system is composed of three parts: biomedical signal acquisition, biomedical data recording, and data transmission. We conducted four types of experiment in order to evaluate the developed system's accuracy, reliability, operability, applicability to daily life, and SMS alarm function. First, we tested the accuracy of the R-R interval by comparing the signals measured via the developed system with those via a commercialized ECG system while the subjects were sitting, standing, lying or cycling. Second, we tested the reliability of the transmitted data to the remote server when two types of emergent events are generated in the developed system using a patient simulator, and measured the battery life to determine the system life. Third, we experimentally examined the accuracy of the corresponding data transmitted to the remote server via the CDMA network when two types of event are generated for each of seven types of action (sitting, standing, standing up from the seat, ordinary walking, fast walking, cycling, and running) during daily life. Lastly, we tested the SMS alarm function. RESULTS: The acquisition and comparison of the subjects' biomedical signals and motion signals confirmed the accuracy, reliability, operability and applicability of the developed system to daily life. The ability of the system to monitor the ECG signals and motion signals during daily life was also demonstrated. CONCLUSION: The system was demonstrated to be very applicable to subjects requiring continuous monitoring for chronic disease and health management. Therefore, the developed system is expected to play an important role in building ubiquitous healthcare systems in Korea in the near future.

Research on Noninvasive Diagnosis for Coronary Heart Disease Based on Neural Network / 航天医学与医学工程

Objective To extract characteristic parameters of ECG signals a new method of non-invasive diagnosis for coronary heart disease with artificial neural network. Methods ECG signals were digitized with A/D converter and filtered to eliminating the noise. Span of QRS interval, R-R interval,and voltage of S-T segment of filtered ECG were detected. These 3 characteristics were as the input parameters of the input layer. Samples were trained with an improved 3-layers back propagation(BP) artificial neural network, as trained samples. The non-trained samples were recognized with these BP neural networks. Results After 12 samples had been trained about 1500 times, the BP neural network could accurately distinguish samples of coronary heart disease from the trained samples and also recognize 20 non-trained samples, 19 to be correct except one. Conclusion It is showed that based on BP network and characteristic parameters of ECG, a new and promising method of non-invasive diagnosis for coronary heart disease has been found.

A study on ECG Data Compression Method Based on BP Neural Network / 医疗卫生装备

Objective Aimed at the problems that the costs of existing ECG data compression methods is high,and they are difficult to apply in engineering practice,a sort BP neural network is set up based on ECG data compression method.Methods Based on BP network theory,two three-layered feedforward neural networks were set up.Then every one heartbeat was divided into three waves,that is,P,QRS and T ones,and the three waves were compressed by two three-layered feedforward neural network individually.In order to improve the replay capability and interference rejection capability of the neural network compress algorithm,incompletely connected structure is employed.Results The method could realize high compress ratio,and improve the replay capability and interference rejection capability of the heartbeat waves.Conclusion Upon with the heartbeat signals,the method can filter and compress waves effectively,and can be used in engineering practice as well.

Design of a filtering circuitfor acquiring ECG signals / 医疗卫生装备

Filtering is very important in acquiring EC G signals.With the characteristics of ECG signals analyzed,this paper designs and achieves a filtering circuit.The result of the experiment is also given.

ECG characteristics detection based on wavelet transform modulus maxima / 医疗卫生装备

In this paper, an algorithm with precise location and high detection rate is introduced. The modulus maxima of wavelet transform are applied to the singularity detection for ECG signal, and thus P wave, T wave and QRS waves can be well detected. Continuous wavelet transform with Mexican hat function is adopted to compute the modulus maxima under MATLAB6.5. The algorithm proves effective and reliable through the tests for the data form MIT-BIH database.

Collection of dynamic and real-time ECG signal by serial port of PC / 医疗卫生装备

Using a low-power CMOS 8-bit microcontroller ATmega8,ten-bit digital signals realizes analog-to digital conversion,and the converted signals are transmitted into the PC by RS232 serial port.This paper mainly introduces the hardware and software design.

Application of USB Bridge Chip to ECG Signal Sampling System / 医疗卫生装备

This paper describes the design of an ECG OEM module based on W78LE54 single chip.The module samples standard I,II and III lead ECG signals in 200Hz rate.The board communicates with computer through the Universal Serial Bus(USB) by using CP2101,a highly-integrated USB-to-UART bridge chip,which can realize PC peripheral's plug&play.

Portable ECG Holter's Design Based on Dual-port RAM / 医疗卫生装备

Objective To transmit ECG signals through a portable dual-mcu ECG holter based dual-port RAM.Methods Dual-port RAM had two independent address,data and control buses,which allowed the two processors accessed it's resource independently at different time.The master processor buffered the acquired data on its RAM until the data accumulated to 200 Bytes.Then the 200 Bytes would be transferred into the dual-port RAM at one time.The slave processor was informed to fetch the data when it reached the flash's one whole page.Results Problems in such aspects were conquered as the port contention of dual-port RAM,limiting sampling frequency,data sharing between the master and slave processors as well as acquiring signals by the cache.Conclusion The portable dual-mcu ECG holter based dual-port RAM can be applied to transmission of ECG signals.