Gia Bhatia

Electromagnetic Interference (EMI) from Consumer Devices and Its Impact on Implantable Pacemakers with AI for Signal Classification

Started June 25, 2025

Abstract or project description

Electromagnetic waves from everyday devices—including smartphones, WiFi routers, microwaves, and electric vehicles—pose potential risks to individuals with pacemakers. EMI can induce mimicking signals, mode switching, signal disruption, and temporary or permanent malfunctions, potentially compromising patient safety and delaying clinical intervention (1). This study investigates the interactions between EMI emitted by common electronic devices and pacemaker operation using a VVI pacemaker prototype on a breadboard. Data collected from controlled exposure experiments were analyzed with AI-based signal classification algorithms to identify interference patterns. Results indicate that devices emitting high-frequency electromagnetic waves in close proximity to pacemakers cause the most significant interference. Moreover, AI analysis enhances detection accuracy, enabling proactive mitigation strategies and the potential for real-time device alerts. These findings underscore the importance of integrating advanced signal monitoring and AI-assisted analysis into pacemaker safety protocols, contributing to improved patient protection in environments with pervasive electromagnetic exposure.