FRIENDS GUI: A graphical user interface for data collection and visualization of vaping behavior from a passive vaping monitor

2025-11-19

AI Summary

Passive e-cigarette monitoring data from the open-hardware device FRIENDS suffer from low accessibility and interpretability. Method: We developed the first Python-based graphical user interface (GUI) software for FRIENDS, enabling serial communication–driven parsing of touch and puffing events, high-precision timestamp synchronization, event decoding, and generation of 24-hour time-series behavioral visualizations using standard plotting libraries. Contribution/Results: This work introduces the first end-to-end solution for FRIENDS—spanning data extraction, decoding, and interactive visualization—thereby significantly lowering the barrier to behavioral analysis of electronic nicotine delivery system (ENDS) use. Experimental validation on real-world 24-hour recordings demonstrates high accuracy and reliability. The software is publicly available as open-source on GitHub, enhancing data accessibility and analytical efficiency for ENDS behavioral research.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Application Domains: Humanities & Computational Social Science
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Web Mining and Content Analysis: Web data visualization
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

Understanding puffing topography (PT), which includes puff duration, intra puff interval, and puff count per session, is critical for evaluating Electronic Nicotine Delivery Systems (ENDS) use, toxicant exposure, and informing regulatory decisions. We developed FRIENDS (Flexible Robust Instrumentation of ENDS), an open-source device that records puffing and touch events of ENDS by attaching to it. This paper introduces the FRIENDS GUI that improves accessibility and interpretability of data collected by FRIENDS. The GUI is a Python-based open-source tool that extracts, decodes, and visualizes 24-hour puffing data from the FRIENDS device. Validation using 24-hour experimental data confirmed accurate timestamp conversion, reliable event decoding, and effective behavioral visualization. The software is freely available on GitHub for public use.

Problem

• Develops GUI for visualizing vaping behavior data from monitoring devices
• Enhances accessibility of puffing topography data for regulatory analysis
• Provides open-source tool to decode and interpret ENDS usage patterns

Innovation

• Open-source Python tool for data extraction
• Decodes and visualizes 24-hour vaping behavior
• Validated timestamp conversion and event decoding