Evidence map›Paper›PMID 33746626›Full record

ArticleIEEE sensors journal2021

A Discreet Wearable IoT Sensor for Continuous Transdermal Alcohol Monitoring - Challenges and Opportunities.

Baichen Li, R Scott Downen, Quan Dong, Nam Tran, Maxine LeSaux, Andrew C Meltzer, Zhenyu Li

Open access · greenAbstract read
In one paragraph

Article in IEEE sensors journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Development and Performance Evaluation of an IoT-Integrated Breath Analyzer.International journal of environmental research and public health · 2023
    Article
  9. Review
  10. 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

7 authors at 1 institution in 1 country.

Baichen LiDepartment of Biomedical Engineering, George Washington University, Washington, DC, 20052 USA.
R Scott DownenDepartment of Biomedical Engineering, George Washington University, Washington, DC, 20052 USA.
Quan DongDepartment of Biomedical Engineering, George Washington University, Washington, DC, 20052 USA.
Nam TranDepartment of Biomedical Engineering, George Washington University, Washington, DC, 20052 USA.
Maxine LeSauxDepartment of Emergency Medicine, George Washington University, Washington, DC, 20052 USA.
Andrew C MeltzerDepartment of Emergency Medicine, George Washington University, Washington, DC, 20052 USA.
Zhenyu LiDepartment of Biomedical Engineering, George Washington University, Washington, DC, 20052 USA.
George Washington University · US

Funding

Wearable Lab-on-a-patch for non-invasive Alcohol Sensing in SweatR41AA024648 · NIAAA · ZANSORS, LLC · PI LI, BAICHEN, LI, ZHENYU · 2015 to 2015
$225k
NIAAA NIH HHS R41 AA024648
6 · The paper itself

Abstract

Non-invasive continuous alcohol (ethanol) monitoring has potential applications in both population research and in clinical management of acute alcohol intoxication or chronic alcoholism. Current wearable monitors based on transdermal alcohol content (TAC) sensing have limited accessibility and blood alcohol content (BAC) quantification accuracy. Here we describe the development of a self-contained discreet wearable transdermal alcohol (TAC) sensor in the form of a wristband or armband. This sensor can detect vapor-phase alcohol in perspiration from 0.09 ppm (equivalent to 0.09 mg/dL sweat alcohol concentration at 25 °C under Henry's Law equilibrium) to over 500 ppm at one-minute time resolution. Additionally, a digital sensor was employed to monitor the temperature and humidity levels inside the sensing chamber. Two male human subjects were recruited to conduct studies with alcohol consumption using calibrated prototype TAC sensors to validate the performance. Our preliminary data demonstrated that, under well-controlled conditions, this sensor can acquire TAC curves at low doses (1-2 standard drinks). Moreover, TAC data for different doses can be easily distinguished. However, substantial interpersonal and intrapersonal variabilities in measurement data were also observed in experiments with less controlled conditions. Our observations suggest that perspiration rate might be an important contributing factor to these variabilities. Further studies with sufficient sample sizes are required to validate and characterize the impact of different perspiration rates on TAC sensors, which may inform more reproducible and accurate sensor designs in the future.

Indexed as

BACethanolfuel cellIoTTACtransdermal alcohol sensorvariabilitywearable sensor

Identifiers

PMID33746626
PMCPMC7978232
OpenAlexW3127138247

What OpenQuestion holds

Textmetadata
LicenceTDM
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.