Evidence map›Paper›PMID 37837050›Full record

ArticleSensors (Basel, Switzerland)2023

Photometric Monitoring of Electronic Cigarette Puff Topography.

Keith Kolaczyk, Hao Jiang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Keith KolaczykDepartment of Biomedical Engineering, Lawrence Technological University, 21000 W 10 Mile Road, Southfield, MI 48075, USA.ORCID 0009-0003-4986-4512
Hao JiangDepartment of Biomedical Engineering, Lawrence Technological University, 21000 W 10 Mile Road, Southfield, MI 48075, USA.ORCID 0000-0003-4450-1467

Funding

National Science Foundation 2138534
6 · The paper itself

Abstract

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.

Indexed as

Electronic Nicotine Delivery SystemsVapingAerosolsNebulizers and VaporizersNicotineAerosolsNicotineaerosolatomizerelectronic cigarettee-liquidnicotineparticulate matterphotometric sensorpressure sensorpuff topographyvaping

Identifiers

PMID37837050
PMCPMC10575377

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.