MAX30102 photometric biosensor coupled to ESP32-webserver capabilities for continuous point of care oxygen saturation and heartrate monitoring

Innovative approaches in bioelectronics and biosensing platforms are of upmost importance to manage emergency situations such as the COVID-19 pandemic. Considering that many biomarker quantification approaches rely on either photometric or electrochemical determination without offering very often continuous monitoring to prevent critical events in the healthcare setting, the development of advanced interfacing strategies is noteworthy to improve patient safety. Regarding acute respiratory syndrome symptoms, peripheral oxygen levels (SpO₂) tend to steadily decrease upon aggravation. Notwithstanding, both SpO₂ and heartrate (HR) tend to dynamically shift according to patient health status. In this context, we investigated the use of MAX30102 photometric biosensing module coupled to personalized ESP32-based webserver to continuously gather and process SpO₂ and HR data from users (e.g. bedridden patients). Moreover, a user-friendly graphic interface was designed and implemented to better showcase biomarker levels for medical personnel and an anatomical case was 3D printed in thermoplastic polyester (polylactic acid - PLA). Results showcased that the data retrieved from MAX30102 photometric biosensor was similar to that of a standard pulse oximeter, while ESP32 webserver was able to gather, process and graphically display data in real time both in smartphones running Android and personal computers running Windows operating systems (IOS and Linux were not tested in this report). Although ESP32 showcased limitations regarding processing power, the implemented features herein described worked soundly. In conclusion, we showcased how biomarkers such as SpO₂ and HR can be continuously monitored and wirelessly interfaced to computers and smartphones through a low-cost microcontroller such as ESP32. For future investigations, we plan on implementing advanced internet of things and artificial intelligence tools to allow the herein described device to continuously evaluate patient status and predict patient critical events.