Design and analytical simulation of heart rate measurement and human body temperature with linear regression approach
Lukman Hakim, Briston Manurung · AIP conference proceedings · 2020
To find out the human heart rate in normal conditions and after exercise and human body temperature, a tool that can measure the condition is needed. In this study a heart rate and human body temperature measurement were made. This measuring instrument uses a pulse sensor to measure the heart rate and DS18B20 sensor to measure human body temperature. The Arduino Uno microcontroller was used as a signal controller and processor. a liquid crystal display (LCD) have 16x2 characters as a data viewer. Based on the sensor test obtained that the linear equation on the measurement of body temperature in normal state is y_reg = 0.2 + 0.026x. the value of standard deviation (δ) = 7.81.The uncertainty value of measurement results (UA_1) = 1.75 and the uncertainty of the UA_2 regression approach = 1.11 the linear equation when condition after completing exercise is y_reg = 2.68+0.002x.value of the standard deviation (δ) = 4.11.the uncertainty value of measurement results (UA_1) = 1.3 and the uncertainty regression UA_2 = 1.62. the linear equation of human body temperature measurement y_reg = 0.89-0.0012x.thevalueofstandard deviation (δ) = 0.89, the uncertainty value of the measurement results (UA_1) = 0.16, and the uncertainty value of the regression approach UA_2 = 0.37. From the all of value the uncertainty value of the regression approach that it show the heart rate and temperature of the human body work well.