Advancing Healthcare with IoT: Digital Twins and AI-Driven Cardiac Diagnostics

Healthcare monitoring techniques have gone through substantial evolution over the years, and IoT coupled with Digital Twin technology represents one of the most promising ways towards providing quality healthcare services in a more patient-centric manner. In this regard, the current study proposes to design a real-time cardiac monitoring solution based on ESP32 microcontroller, AD8232 electrocardiogram sensor, MAX30100 pulse oximetry and heart rate sensor, as well as DS18B20 digital temperature sensor. Data about the vital signs will be uploaded to the cloud and used to create a Digital Twin that will be constantly updated with the new information. Healthcare specialists can interact with the digital twin to analyze historical information, run different simulations of possible health problems and come up with customized treatment strategies without having direct contact with a patient. Programming will be done in the Arduino environment, data will be stored and analyzed using Firebase Firestore, and the web application interface will use React platform. Preliminary results indicate that the suggested approach can dramatically decrease time needed to deliver a response after the abnormal cardiac condition occurs, as well as decrease in-person visit frequency required by patients from rural or underdeveloped areas.