Sistema basado en Wearable Sensors e IoT para el monitoreo remoto del perfil biomecánico de una persona

Abstract

Abstract: The objective of this project is to develop a system based on Wearable Sensors and IoT for remote monitoring of a person's biomechanical profile. The hardware architecture of the implemented system is made up of: six OYMotion Gravity EMG sensors for the acquisition of myoelectric signals, a PulseSensor sensor for the acquisition of heart rate, and the Arduino MEGA 2560 development board for data digitization and transmission. These acquired data are transmitted to an application developed in Python that is responsible for displaying and storing the seven signals as a function of time. The software architecture of this application is made up of three modules: the data acquisition module, the data visualization module and the storage module. The device was evaluated on four test patients, who performed three exercises based on NIOSH recommendations. When analyzing the 84 signals acquired, it was concluded that the acquisition of the signals has the required sampling time, the duration time of constant data capture, and there are no data lost in the transfer.