The objective of this article was to use the Cubic Spline as an auxiliary tool in the monitoring of a glycemic curve using data acquired from a person with diabetes, linked to an application called Glic. In this context, the concepts of diabetes were presented, addressing the types, glycated hemoglobin, diet and physical exercises. Then, an approximation curve called Cubic Spline. An application was developed, which analyzed the behavior of the Cubic Spline in the interpolation of data collected using Glic. By analyzing the results, it was possible to conclude that the Cubic Spline is efficient in the process of making a data set dense, presenting a smoothed geometric image indicating a smaller variation in them ratified by the statistical parameter standard deviation, thus providing a more reliable analysis in relation to the values of glycated hemoglobin linked to the glycemic rates used.
|
