To study and monitor the adverse health consequences of using electronic cigarettes, a user’s puff topography, which are quantification parameters of the user’s vaping habits, plays a central role. In this work, we introduce a topography sensor to measure the mass of total particulate matter generated in every puff and to estimate the nicotine yield. The sensor is compact and low-cost, and is integrated into the electronic cigarette device to promptly and conveniently monitor the user’s daily puff topography. The topography sensor is comprised of a photometric sensor and a pressure sensor. The photometric sensor measures the mass concentration of the aerosol, based on scattering of near-infrared light from airborne particles, while the pressure sensor measures the flow rate. The topography sensor was tested under various conditions including a wide range of atomizer power, puff duration, and inhalation pressure. The sensor’s accuracy was validated by comparing the sensor’s readings with reference measurements, and the results matched closely with the trends reported by existing studies on electronic cigarettes. An example application for tracking a user’s puff topography was also demonstrated. Our topography sensor holds great promise in mitigating the health risks of vaping, and in promoting quality control of electronic cigarette products.
Smart Electronic Cigarettes with Built-in Aerosol Sensors
This work introduces an emerging application of aerosol sensors integrated inside electronic cigarettes. Using the aerosol sensors, particle size distribution, aerosol temperature, and target chemicals of the generated aerosols are measured before the aerosol is inhaled by a user. When a hazardous aerosol is detected, the user will be warned immediately to stop vaping. With extensive sensor data collected from every puff, an electronic cigarette becomes a smart mobile device, capable of tracking and improving a user's vaping habits. Experimental results on a prototype are presented and have shown great promises towards minimizing the health risks of vaping.
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- Award ID(s):
- 2138534
- PAR ID:
- 10386127
- Date Published:
- Journal Name:
- 2022 IEEE Sensors
- Page Range / eLocation ID:
- 1 to 4
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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