Resumo

BECERRA TAPIA, Víctor et al. Biomedical data transfer system with low consumption communication protocols. Rev. cienc. tecnol. [online]. 2023, vol.6, n.4, e284.  Epub 25-Jun-2024. ISSN 2594-1925.  https://doi.org/10.37636/recit.v6n4e284.

In the field of medical care, hospitals face numerous challenges in effectively managing biomedical data. This can lead to a decrease in the efficiency of care, as not all institutions have efficient methods for managing such data. In addition to personal data, physiological constants, such as heart rate and oxygen levels, need to be constantly monitored in order to detect any changes. However, obtaining this data from different instruments and ensuring its constant recording can be problematic. To address these challenges, a system based on the Internet of Things (IoT) has been developed. This system utilizes sensors connected to ESP32 cards, which are in constant communication, to obtain physiological constants and other relevant data. A prototype has been designed, which includes sensors placed on the wrist to measure three physiological constants. The MAX30102 pulse sensor is used to measure blood oxygenation and heart rate. This sensor can be placed on the fingers, lobe, or wrist to obtain accurate readings. Additionally, the MLX90614 sensor is used for temperature acquisition. All the data collected by these sensors is managed by an ESP32 card, which acquires the information and sends it for further use. They employ communication protocols that enable the simultaneous reading of multiple sensors for the parallel monitoring of more than one patient, a capability not addressed in current prehospital care systems. To ensure constant monitoring of physiological constants, a master-slave configuration is utilized. Each slave module collects information from individual patients and sends it to a master card. The data is encrypted during transmission. These devices can be used in various healthcare settings, including prehospital care, and can be carried by the patients themselves. The collected data is then transmitted to a central system using the MQTT protocol. A master ESP32, connected to a Raspberry Pi 4, acts as the main console, where the data is centralized. Once the data is in the MQTT broker, it can be accessed and analyzed from various devices for traceability purposes. Real-time data recording is achieved by utilizing Google services, specifically Firebase, which stores the data in a database.

Palavras-chave : IoT; MQTT protocol; ESP-NOW; Raspberry Pi; Physiological constants.