Evidence map›Paper›PMID 34640848›Full record

ArticleSensors (Basel, Switzerland)2021

Using Smartwatches to Detect Face Touching.

Chen Bai, Yu-Peng Chen, Adam Wolach, Lisa Anthony, Mamoun T Mardini

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Chen BaiDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0003-0961-1927
Yu-Peng ChenDepartment of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA.
Adam WolachDepartment of Aging and Geriatric Research, College of Medicine, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0001-7626-6436
Lisa AnthonyDepartment of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA.ORCID 0000-0002-9617-2952
Mamoun T MardiniDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-5345-8811

Funding

Internally funded 000000
6 · The paper itself

Abstract

Frequent spontaneous facial self-touches, predominantly during outbreaks, have the theoretical potential to be a mechanism of contracting and transmitting diseases. Despite the recent advent of vaccines, behavioral approaches remain an integral part of reducing the spread of COVID-19 and other respiratory illnesses. The aim of this study was to utilize the functionality and the spread of smartwatches to develop a smartwatch application to identify motion signatures that are mapped accurately to face touching. Participants (

Indexed as

COVID-19FaceFemaleHumansMachine LearningSARS-CoV-2Support Vector MachineaccelerometerCOVID-19face touchingmachine learningrespiratory illnessessmartwatchwearables

Identifiers

PMID34640848
PMCPMC8513006

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.