Biomedical Engineering Advances (Jun 2024)
Design and development of a cost-effective portable IoT enabled multi-channel physiological signal monitoring system
Abstract
In health care, early detection of diseases is important in order to increase survival rates. Regular monitoring of vital signs is necessary for the early detection of health issues. Due to the high cost, inadequacy, and complexity of monitoring devices, it is challenging for individuals to check their vital signs at home. Consequently, a cost-effective, broadly accessible, and easy-to-use system is necessary for health monitoring. For this purpose, we developed a portable and wireless acquisition electronic device to help patients record physiologically relevant signals such as ECG, EMG, EEG, and EOG for continuous monitoring. The key components of the acquisition system are a portable device, a Wi-Fi router, a SQL server, and a graphical user interface (GUI). In this study, a cost-effective, fairly low-power Internet-of-Things (IoT)-based health monitoring system was built employing a portable device incorporating analog front ends (AFE) and the ESP 32 Wroom-32. Continuous remote monitoring and diagnostics are made possible by including IoT in the architecture. In the proposed monitoring system, the lightweight Message Queue Telemetry Transport (MQTT) protocol was used. A GUI is constructed that shows near-real-time data in a web browser and can be accessed from any operating system. The accuracy of the acquired signals was validated by comparing the individual’s ECG recorded in a remote device through the IoT cloud with a conventional biomedical certified ECG machine. The AFEs were built and evaluated based on the amplitude and bandwidth of ECG, EMG, EEG, and EOG signals. The cost and power analysis, as well as other key parameters are presented. Compared to similar existing boards, our developed system demonstrates high configurable sampling frequency, high Common Mode Rejection Ratio (CMRR) and high transmission throughput with no packet loss while costing significantly less and consuming moderate power. This makes the proposed system suited for the acquisition of multichannel physiological signals for home applications.
