Técnicas de Adquisición y Procesamiento de Señales Electrocardiográficas en la Detección de Arritmias Cardíacas

The development of ambulatory monitoring systems and its electrocardiographic (ECG) signal processing techniques has become an important field of investigation, due to its relevance in the early detection of cardiovascular diseases such as the arrhythmias. The current trend of this technology is oriented to the use of portable equipment and mobile devices such as Smartphones, which have been widely accepted due to the technical characteristics and common integration in daily life. A fundamental characteristic of these systems is their ability to reduce the most common types of noise by means of digital signal processing techniques.  Among the most used techniques are the adaptive filters and the Discrete Wavelet Transform (DWT) which have been successfully implemented in several studies. There are systems that integrate classification stages based on artificial intelligence, which increases the performance in the process of arrhythmias detection. These techniques are not only evaluated for their functionality but for their computational cost, since they will be used in real-time applications, and implemented in embedded systems. This paper shows a review of each of the stages in the construction of a standard ambulatory monitoring system, for the contextualization of the reader in this type of technology.El desarrollo de sistemas de  monitoreo  ambulatorio  y  sus  técnicas  de  procesamiento  de  la  señal  electrocardiográfica (ECG) se han convertido en un importante campo de investigación, debido a su relevancia en la detección temprana de enfermedades cardiovasculares, tales como arritmias. La tendencia actual de esta tecnología está orientada al uso de equipos portátiles y dispositivos móviles como los Smartphones, que han sido ampliamente aceptados debido a sus características técnicas y a su integración, cada vez más común, en la vida diaria. Una característica fundamental de estos sistemas es su capacidad de reducir los tipos más comunes de ruido mediante técnicas de procesamiento de señales digitales. Entre las técnicas más utilizadas se encuentran los filtros adaptativos y la Transformada Discreta Wavelet (DWT, por sus siglas en inglés), los cuales han sido implementados exitosamente en diversos estudios. Así mismo, se reportan sistemas que integran etapas de clasificación basadas en inteligencia artificial, con lo cual se aumenta el rendimiento en el proceso de detección de arritmias. En este sentido, estas técnicas no solo son evaluadas por su funcionalidad, sino por su costo computacional, debido a que deben ser utilizadas en aplicaciones en tiempo real, e implementadas en sistemas embebidos. Este documento presenta una revisión del estado del arte de cada una de las etapas en la construcción de un sistema de monitoreo ambulatorio estándar, para la contextualización del lector en este tipo de tecnologías

System Design And Motion Artifact Removal Algorithm Implementation For Ambulatory Women Ecg Measurement System:e-Bra System

Cardio Vascular Disease (CVD) leads to sudden cardiac death due to irregular phenomenon of the cardiac signal by the abnormal case of blood vessel and cardiac structure. For last three decades, there is an enhanced interest in research for cardiac diseases.. As a result, the death rate by cardiac disease in men has been falling gradually compared with relatively increasing the death rate for women due to CVD. The main reason for this phenomenon is due to the lack of seriousness to female CVD and different symptoms of female CVD compared with the symptoms of male CVD. Usually, because the CVDs for women accompany with ordinary symptoms not attributable to the heart abnormality signal such as unusual fatigue, sleep disturbances, shortness of breath, anxiety, chest discomfort, and indigestion dyspepsia, most women CVD patients do not realize that these symptoms are actually related to the CVD symptoms. Therefore, periodic ECG signal observation is required not only for women who have been diagnosed with heart disease but also for persons who want to examine their heart activity. Electrocardiogram (ECG) is used to diagnose abnormality of heart. Among the medical checkup methods for CVDs, it is very an effective method for the diagnosis of cardiac disease and the early detection of heart abnormality to monitor ECG periodically. This dissertation proposes an effective ECG monitoring system for woman by attaching the system on woman\u27s brassiere by using augmented chest lead attachment method. The suggested system called E-Bra system in this dissertation consists of an ECG transmission system and a computer installed program called E-Bra pro in order to display and analyze the ECG transmitted from the transmission module. The ECG transmission module consists of three parts such as ECG physical signal detection part with 3 stage amplifier and two electrodes, data acquisition with AD converter, and data transmission part with GPRS (General Packet Radio Service) communication, and it has very compact size that is attachable at the bottom layer of a brassiere for women. However, the ECG signal measured from the transmission module includes not only pure ECG components information; P waves QRS complex, and T wave, but also a motion artifact component (MA) due to subject movements. The MA component is one of the reasons for misdiagnosis. Therefore, the main purpose of the E-Bra system is to provide a reliable ECG data set identical to the quality of an ECG data set collected in hospital. Unfortunately, removing MA is a big challenge because the frequency range of the MA is duplicated on the frequency range of the pure ECG components, P-QRS-T. In this dissertation, two motion artifact removal algorithms (MARAs) with adaptive filter structure and independent component analysis concept are suggested, and the performance of the two MARAs will be evaluated by correlation values and signal noise ratio (SNR) values