Prediction of Individual Dynamic Thermal Sensation in Subway Commute Using Smart Face Mask.

Md Hasib Fakir, Seong Eun Yoon, Abdul Mohizin, Jung Kyung Kim

Abstract read

In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Md Hasib FakirDepartment of Integrative Biomedical Science and Engineering, Graduate School, Kookmin University, Seoul 02707, Republic of Korea.ORCID 0000-0001-6831-7926

Seong Eun YoonDepartment of Mechanical Engineering, Graduate School, Kookmin University, Seoul 02707, Republic of Korea.

Abdul MohizinSchool of Mechanical Engineering, Kookmin University, Seoul 02707, Republic of Korea.

Jung Kyung KimDepartment of Integrative Biomedical Science and Engineering, Graduate School, Kookmin University, Seoul 02707, Republic of Korea.ORCID 0000-0002-4164-6655

Funding

Korea Evaluation Institute of Industrial Technology 1415177965/20011377National Research Foundation of Korea NRF-2022R1A4A5018891

6 · The paper itself

Abstract

Wearable sensors and machine learning algorithms are widely used for predicting an individual's thermal sensation. However, most of the studies are limited to controlled laboratory experiments with inconvenient wearable sensors without considering the dynamic behavior of ambient conditions. In this study, we focused on predicting individual dynamic thermal sensation based on physiological and psychological data. We designed a smart face mask that can measure skin temperature (SKT) and exhaled breath temperature (EBT) and is powered by a rechargeable battery. Real-time human experiments were performed in a subway cabin with twenty male students under natural conditions. The data were collected using a smartphone application, and we created features using the wavelet decomposition technique. The bagged tree algorithm was selected to train the individual model, which showed an overall accuracy and

Indexed as

MasksRailroadsHumansSkin TemperatureTemperatureThermosensingexhaled breath temperaturemachine learningskin temperaturesmart face maskthermal sensation votewearable biosensors

Identifiers

PMID36551060

DOI10.3390/bios12121093

PMCPMC9775212

What OpenQuestion holds

Textmetadata

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.