Sistema basado en Internet of Medical Things (IoMT) aplicado al estudio de Escoliosis

Abstract

Abstract: The objective of this project is the development of a prototype based on Internet of Medical Things (IoMT) architectures to apply it to the study of muscular and bone deformations of the back (Scoliosis). The hardware architecture of the implemented system is made up of: six OYMotion Gravity EMG SEN0240 analog sensors to acquire myoelectric signals, two MPU-6050 inertial sensors to obtain movement signals, a GSR sensor to measure skin conductance, a PulseSensor sensor for heart rate measurement and an MLX-90614 sensor for body temperature measurement, for data processing and transmission an Arduino MEGA 2560, an RTC DS3231 module and the HC-05 Bluetooth module were used. These acquired data are displayed in a graphical user interface developed in Python. The software architecture of this application is made up of four blocks: the data acquisition block, the processing block, the storage block, and the data visualization block. To evaluate the performance of the prototype, it was carried out by three test users who performed three exercises as recommended by the OWAS ergonomic method. When analyzing the 96 acquired signals, it was determined that the sampling frequency is 33 samples per second, the data capture time is constant and there was no data loss in the hardware and in the system communication.