Polysomnography, a critical health study for evaluating sleep disorders, has increased relevance due to its impact on people’s health. Currently, it is conducted in specialized clinics, away from the patient’s usual sleeping environment, leading to variations in the study. Therefore, implementing a method to visualize the study signals at long distances could lead to more accurate sleep measurements. This study aims to determine whether the use of the Message Queue Telemetry Transport (MQTT) protocol, a key component of the Internet of Things (IoT), can effectively transmit the electrocardiogram (ECG) and electroencephalogram (EEG) signals from the polysomnography study to a long-distance visualization platform. The design and development of instrumentation channels for polysomnography signals, the analog-to-digital conversion of signal and connection to the Internet with an ESP32 microcontroller, and the development of a webpage for visualization are performed, along with the analysis of time measurements and signal accuracy to determine performance. The results of this study demonstrate that the MQTT protocol is capable and efficient in sending signals with a 0.6-millisecond difference of time and a 95% accuracy of the signal of interest, which is highly favorable for polysomnography monitoring. In conclusion, the developed system successfully maintained signal integrity and reliable transmission, achieving real-time visualization and meeting the objectives of remote monitoring. This work showcases the significant potential of the MQTT protocol for practical applications in real-time health monitoring, providing reassurance of its effectiveness.