Cardiac Rhythm Monitoring with ChatGPT Integration

Cardiovascular diseases remain a leading global cause of mortality, highlighting the need for accessible, real-time cardiac monitoring solutions. This paper presents, a low-cost, open-source ECG monitoring system that integrates wearable IoT hardware with AI interpretation through the ChatGPT API, called CardiaTalker. Based on ESP32 microcontroller, ECG (AD8232) and accelerometer (ADXL335) front-ends, the system captures biosignals which are processed on edge devices and analyzed in the cloud. The architecture enables two-way interpretation: one from a remote clinician and one from ChatGPT, offering conversational, educational feedback to users. Experimental evaluations demonstrate reliable data acquisition, low-latency wireless communication, and effective AI-generated insights. While ChatGPT showed promising interpretative and assisting abilities for basic rhythm analysis, limitations remain in detecting detailed ECG features. This work highlights the potential of combining wearable technologies with large language models for scalable, intelligent cardiac health monitoring, particularly in remote or local environments.