PuffEM: An E-cigarette Sleeve for Estimating User Nicotine Intake

With the increasing prevalence of Electronic Nicotine Delivery Systems (ENDS), understanding vaping behaviors and nicotine intake is essential. Existing methods such as self-reports, gesture-based monitoring, and sensor-based methods lack reliability, adaptability, and real-time vaping event data. We introduce PuffEM, a low-power, versatile system that detects vaping events reliably using a touch sensor and on-the-surface magnetometer to estimate nicotine intake. Integrated with a mobile app, it collects sensor and contextual data, supporting vaping and addiction research and health interventions. Lab tests confirm PuffEM’s ability to detect vaping events, function across three ENDS devices, and estimate vaporized nicotine liquid. A five-day in-wild study (2 participants, 753 puffs, 41 sessions, 5.79 hours) demonstrated high usability and low burden, validating real-world feasibility. By combining specialized hardware (touch, magnetometer, IMU sensors) with a mobile platform, PuffEM enables reliable vaping detection, behavioral insights, and scalable smoking cessation interventions.CCS Concepts• Human-centered computing → Ubiquitous and mobile computing systems and tools; • Applied computing → Life and medical sciences; Health informatics.