Early detection model of normal and abnormal blood flow using pulse Oximetry non-invasive of pregnant heart rate

Abstract

The heart is an important organ in humans as an identification of early examinations in pregnant women carried out by doctors to determine normal and abnormal pregnancies in the fetus. Heart rate or BPM (beats per minute) is a parameter that indicates the condition of a person's heart. The normal human heart rate ranges from 60-100 beats per minute. In pumping blood throughout the body, the heart then holds it back after being cleaned by the lungs and this is closely related to the level of oxygen flowing in the bloodstream. Humans need sufficient oxygen levels in the body to survive. One of the vital monitoring tools for oxygen levels in the human body is pulse oximetry. Pulse oximetry is usually in units or rooms with high and rapid action cases such as the ICU. From these problems, it is necessary to make a research on a diagnostic instrument model for early detection of normal and abnormal blood flow using non-invasive pulse oximetry, a case study of the heart rate of pregnant women which can be identified early through the max 30100 sensor reading in the form of detecting the heart rate and oximeter, then processed by Arduino uno R3 where arduino uno processes data in the form of heart rate and oxymeter readings so that it can be displayed via a 16x2 LCD, the output is the identification of the value of the heart rate and oximeter input so that the normal and abnormal heart rate conditions are known. The purpose of this study is to detect early pregnant women and fetuses with normal or abnormal blood flow using non-invasive pulse oximetry in which case studies are implemented on the heartbeat of pregnant women. The method used in this study uses the hardware programming method by starting with project planning, research, part testing, mechanical design, electrical design, software design, functional test, integration, overall testing and optimization. The measurement results from the MAX30100 sensor are processed on Arduino UNO R3 and displayed on the LCD screen. The system as a whole can work with energy supply from the power supply. After measuring with a comparator that has been calibrated, the average error value of the measurement is 3.32 %.