Cargando…

Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours

One of the main factors in controlling infectious diseases such as COVID-19 is to prevent touching preoral and prenasal regions. Face touching is a habitual behaviour that occurs frequently. Studies showed that people touch their faces 23 times per hour on average. A contaminated hand could transmit...

Descripción completa

Detalles Bibliográficos
Autores principales: Fathian, Ramin, Phan, Steven, Ho, Chester, Rouhani, Hossein
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9937467/
https://www.ncbi.nlm.nih.gov/pubmed/36800355
http://dx.doi.org/10.1371/journal.pone.0281778
_version_ 1784890430559617024
author Fathian, Ramin
Phan, Steven
Ho, Chester
Rouhani, Hossein
author_facet Fathian, Ramin
Phan, Steven
Ho, Chester
Rouhani, Hossein
author_sort Fathian, Ramin
collection PubMed
description One of the main factors in controlling infectious diseases such as COVID-19 is to prevent touching preoral and prenasal regions. Face touching is a habitual behaviour that occurs frequently. Studies showed that people touch their faces 23 times per hour on average. A contaminated hand could transmit the infection to the body by a facial touch. Since controlling this spontaneous habit is not easy, this study aimed to develop and validate a technology to detect and monitor face touch using dynamic time warping (DTW) and KNN (k-nearest neighbours) based on a wrist-mounted inertial measurement unit (IMU) in a controlled environment and natural environment trials. For this purpose, eleven volunteers were recruited and their hand motions were recorded in controlled and natural environment trials using a wrist-mounted IMU. Then the sensitivity, precision, and accuracy of our developed technology in detecting the face touch were evaluated. It was observed that the sensitivity, precision, and accuracy of the DTW-KNN classifier were 91%, 97%, and 85% in controlled environment trials and 79%, 92%, and 79% in natural environment trials (daily life). In conclusion, a wrist-mounted IMU, widely available in smartwatches, could detect the face touch with high sensitivity, precision, and accuracy and can be used as an ambulatory system to detect and monitor face touching as a high-risk habit in daily life.
format Online
Article
Text
id pubmed-9937467
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-99374672023-02-18 Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours Fathian, Ramin Phan, Steven Ho, Chester Rouhani, Hossein PLoS One Research Article One of the main factors in controlling infectious diseases such as COVID-19 is to prevent touching preoral and prenasal regions. Face touching is a habitual behaviour that occurs frequently. Studies showed that people touch their faces 23 times per hour on average. A contaminated hand could transmit the infection to the body by a facial touch. Since controlling this spontaneous habit is not easy, this study aimed to develop and validate a technology to detect and monitor face touch using dynamic time warping (DTW) and KNN (k-nearest neighbours) based on a wrist-mounted inertial measurement unit (IMU) in a controlled environment and natural environment trials. For this purpose, eleven volunteers were recruited and their hand motions were recorded in controlled and natural environment trials using a wrist-mounted IMU. Then the sensitivity, precision, and accuracy of our developed technology in detecting the face touch were evaluated. It was observed that the sensitivity, precision, and accuracy of the DTW-KNN classifier were 91%, 97%, and 85% in controlled environment trials and 79%, 92%, and 79% in natural environment trials (daily life). In conclusion, a wrist-mounted IMU, widely available in smartwatches, could detect the face touch with high sensitivity, precision, and accuracy and can be used as an ambulatory system to detect and monitor face touching as a high-risk habit in daily life. Public Library of Science 2023-02-17 /pmc/articles/PMC9937467/ /pubmed/36800355 http://dx.doi.org/10.1371/journal.pone.0281778 Text en © 2023 Fathian et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Fathian, Ramin
Phan, Steven
Ho, Chester
Rouhani, Hossein
Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
title Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
title_full Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
title_fullStr Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
title_full_unstemmed Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
title_short Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
title_sort face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9937467/
https://www.ncbi.nlm.nih.gov/pubmed/36800355
http://dx.doi.org/10.1371/journal.pone.0281778
work_keys_str_mv AT fathianramin facetouchmonitoringusinganinstrumentedwristbandusingdynamictimewarpingandknearestneighbours
AT phansteven facetouchmonitoringusinganinstrumentedwristbandusingdynamictimewarpingandknearestneighbours
AT hochester facetouchmonitoringusinganinstrumentedwristbandusingdynamictimewarpingandknearestneighbours
AT rouhanihossein facetouchmonitoringusinganinstrumentedwristbandusingdynamictimewarpingandknearestneighbours