La presión arterial (PA) y la señal electrocardiografica (SECG) o la señal eléctrica del corazón, son mediciones físicas que permiten conocer el comportamiento del sistema cardíaco. Este trabajo, presenta una metodología novedosa, donde por primera vez se muestra la relación entre PA y SECG. Inicialmente, para poder realizar este estudio, se realizó la toma de muestra de señales SECG, a 20 pacientes, 18 sanos entre los 17 y 26 años y 2 pacientes con PA anormal entre 50 y 78 año, para el registro de la SECG se utilizó el equipo powerlab, donde se usaron electrodos para capturar la señal del corazón a través de la derivación DI, una vez obtenidas las muestras de las señales, se estudió en espacial las ondas R y las ondas T, con el fin de tener caracterizada la presión arterial sistólica y diastólica separadamente.Para poder obtener la PA a través de las señales SECG, usamos transformada wavelet para identificar las ondas R y las ondas T, para luego realizar una segmentación a la señal y extraer las porciones de sístole y diástole de la señal original. Seguidamente a este procedimiento se aplicó a redes neuronales con el fin de tener un sistema que diera valores de presión sistólica y diastólica basados en las SECG. Una vez aplicada a las redes neuronales, se logró un porcentaje total de acierto de 97,305 para sistole y de 95,65 para diástole. Finalmente, se puede decir que este articulo muestra que existe una relación entre PA y SECG
Blood pressure (BP) and the electrocardiographic (ECG) signal, or electrical signal of the heart, are physical measurements that provide insight into the behavior of the cardiac system. This paper presents a novel methodology, where for the first time the relationship between BP and ECG signal is shown. Initially, to perform this study, a signal sampling of ECG signals was performed on 20 patients: eighteen healthy, between 17 and 26 years old, and two with normal BP between 50 and 78 years old. Powerlab equipment was used to record the ECG signal, with electrodes used to capture the heart signal through the lead. Once the signal samples were obtained, the R and T waves in particular were studied with the aim of reading the systolic and diastolic blood pressure separately. In order to obtain the BP with the ECG signals, we used a wavelet transform to identify the R waves and T waves, and then to perform segmentation on the signal and extract the systole and diastole portions from the original signal. Following this procedure, neural networks were applied in order to have a system with systolic and diastolic pressure values based on the ECG signals. This application led to a total success rate of 97.305% for systole and 95.65% for diastole. In conclusion, this article can be said to demonstrate the existence of a relationship between BP and ECG signals.Blood pressure (BP) and the electrocardiographic (ECG) signal, or electrical signal of the heart, are physical measurements that provide insight into the behavior of the cardiac system. This paper presents a novel methodology, where for the first time the relationship between BP and ECG signal is shown. Initially, to perform this study, a signal sampling of ECG signals was performed on 20 patients: eighteen healthy, between 17 and 26 years old, and two with normal BP between 50 and 78 years old. Powerlab equipment was used to record the ECG signal, with electrodes used to capture the heart signal through the lead. Once the signal samples were obtained, the R and T waves in particular were studied with the aim of reading the systolic and diastolic blood pressure separately. In order to obtain the BP with the ECG signals, we used a wavelet transform to identify the R waves and T waves, and then to perform segmentation on the signal and extract the systole and diastole portions from the original signal. Following this procedure, neural networks were applied in order to have a system with systolic and diastolic pressure values based on the ECG signals. This application led to a total success rate of 97.305% for systole and 95.65% for diastole. In conclusion, this article can be said to demonstrate the existence of a relationship between BP and ECG signals.
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