Evidence map›Paper›PMID 36068802›Full record

ArticlePhotoacoustics2022

Photoacoustic heterodyne breath sensor for real-time measurement of human exhaled carbon monoxide.

Biao Li, Chaofan Feng, Hongpeng Wu, Suotang Jia, Lei Dong

Open access · goldAbstract read
In one paragraph

Article in Photoacoustics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
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

7 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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

5 authors at 2 institutions in 1 country.

Biao LiState Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan 030006, China.
Chaofan FengState Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan 030006, China.
Hongpeng WuState Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan 030006, China.
Suotang JiaState Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan 030006, China.
Lei DongState Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan 030006, China.
State Key Laboratory of Quantum Optics and Quantum Optics DevicesShanxi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A breath sensor for real-time measurement of human exhaled carbon monoxide is reported. This breath sensor is based on a novel photoacoustic heterodyne gas sensing technique, which combines the conventional photoacoustic spectroscopy with the beat-frequency detection algorithm, thus offering a fast response time and a convenient optical alignment, as well as eliminating the needs for frequency calibration and wavelength locking. The principle of photoacoustic heterodyne gas sensing was explained in detail. The performance of the photoacoustic heterodyne breath sensor was evaluated in terms of minimum detection limit, response time, and linearity. The exhaled carbon monoxide levels of eight volunteers were measured and the results demonstrate the reliability and feasibility of this breath sensor.

Indexed as

Beat-frequency signalBreath sensorExhaled carbon monoxidePhotoacoustic heterodyne sensingPhotoacoustic spectroscopy

Identifiers

PMID36068802
PMCPMC9441263
OpenAlexW4290786207

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.