Wristalert: A Face Touching Alert Through Inertial Sensors and Long Short-Term Memory Neural Network
A wearable face-touching prevention device intended for diminishing the contagion risk from viruses and other pathogens has been developed, named wristalert. The purpose is to identify and emit an alert when face-touching behaviors are detected. The wristalert draws awareness to subconscious hand mo...
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Veröffentlicht in: | IEEE sensors journal 2023-11, Vol.23 (22), p.27960-27966 |
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creator | Porta-Garcia, Miguel Angel Villa-Medina, Juan Francisco Gutierrez, Joaquin Fuentes-Villegas, Alberto Daniel Porta-Gandara, Miguel Angel |
description | A wearable face-touching prevention device intended for diminishing the contagion risk from viruses and other pathogens has been developed, named wristalert. The purpose is to identify and emit an alert when face-touching behaviors are detected. The wristalert draws awareness to subconscious hand movements toward the face, particularly when a person is exposed to high-risk places where a contaminated surface could be reached, and self-inoculation may occur. It is based upon a trained neuronal network using inertial sensors and implemented into a microcontroller to drive a sound alert when wrist-hand movements may reach the face. The electronic components are embedded in a 3-D-printed case attached to a strap, forming the alerting device. The results show that the wristalert is highly reliable since an 89% prediction accuracy is obtained, providing a feasible system to avoid face touching. This wearable device is replicable, inexpensive, and has low power consumption. |
doi_str_mv | 10.1109/JSEN.2023.3322080 |
format | Article |
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The purpose is to identify and emit an alert when face-touching behaviors are detected. The wristalert draws awareness to subconscious hand movements toward the face, particularly when a person is exposed to high-risk places where a contaminated surface could be reached, and self-inoculation may occur. It is based upon a trained neuronal network using inertial sensors and implemented into a microcontroller to drive a sound alert when wrist-hand movements may reach the face. The electronic components are embedded in a 3-D-printed case attached to a strap, forming the alerting device. The results show that the wristalert is highly reliable since an 89% prediction accuracy is obtained, providing a feasible system to avoid face touching. This wearable device is replicable, inexpensive, and has low power consumption.</description><identifier>ISSN: 1530-437X</identifier><identifier>EISSN: 1558-1748</identifier><identifier>DOI: 10.1109/JSEN.2023.3322080</identifier><identifier>CODEN: ISJEAZ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Electronic components ; Face recognition ; Faces ; Fomite transmission ; Hand (anatomy) ; Inertial sensing devices ; Inertial sensors ; infection prevention ; Logic gates ; machine learning (ML) embedded application ; Microcontrollers ; Neural networks ; pathogen spread ; Power consumption ; Sensors ; Three dimensional printing ; wearable alert ; Wearable technology ; Wrist</subject><ispartof>IEEE sensors journal, 2023-11, Vol.23 (22), p.27960-27966</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c246t-34a7ce2a06a89f54343ba1eb0e82a24c8bdd80a9c7b93193eacc444bda1e8b123</cites><orcidid>0009-0003-7430-0823 ; 0000-0002-1647-2649 ; 0000-0002-2298-9898 ; 0000-0002-4045-9102</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10278103$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10278103$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Porta-Garcia, Miguel Angel</creatorcontrib><creatorcontrib>Villa-Medina, Juan Francisco</creatorcontrib><creatorcontrib>Gutierrez, Joaquin</creatorcontrib><creatorcontrib>Fuentes-Villegas, Alberto Daniel</creatorcontrib><creatorcontrib>Porta-Gandara, Miguel Angel</creatorcontrib><title>Wristalert: A Face Touching Alert Through Inertial Sensors and Long Short-Term Memory Neural Network</title><title>IEEE sensors journal</title><addtitle>JSEN</addtitle><description>A wearable face-touching prevention device intended for diminishing the contagion risk from viruses and other pathogens has been developed, named wristalert. The purpose is to identify and emit an alert when face-touching behaviors are detected. The wristalert draws awareness to subconscious hand movements toward the face, particularly when a person is exposed to high-risk places where a contaminated surface could be reached, and self-inoculation may occur. It is based upon a trained neuronal network using inertial sensors and implemented into a microcontroller to drive a sound alert when wrist-hand movements may reach the face. The electronic components are embedded in a 3-D-printed case attached to a strap, forming the alerting device. The results show that the wristalert is highly reliable since an 89% prediction accuracy is obtained, providing a feasible system to avoid face touching. This wearable device is replicable, inexpensive, and has low power consumption.</description><subject>Electronic components</subject><subject>Face recognition</subject><subject>Faces</subject><subject>Fomite transmission</subject><subject>Hand (anatomy)</subject><subject>Inertial sensing devices</subject><subject>Inertial sensors</subject><subject>infection prevention</subject><subject>Logic gates</subject><subject>machine learning (ML) embedded application</subject><subject>Microcontrollers</subject><subject>Neural networks</subject><subject>pathogen spread</subject><subject>Power consumption</subject><subject>Sensors</subject><subject>Three dimensional printing</subject><subject>wearable alert</subject><subject>Wearable technology</subject><subject>Wrist</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkMtOwkAUhidGExF9ABMXk7guzq3M1B0hgBjEBTW6m0ynB1qEDs60Mby9bWDh6lzy_eckH0L3lAwoJcnT62qyHDDC-IBzxogiF6hH41hFVAp12fWcRILLr2t0E8KWEJrIWPZQ_unLUJsd-PoZj_DUWMCpa2xRVhs86tY4LbxrNgWeV-1Umh1eQRWcD9hUOV64llsVztdRCn6P32Dv_BEvofEtuYT61_nvW3S1NrsAd-faRx_TSTp-iRbvs_l4tIgsE8M64sJIC8yQoVHJOhZc8MxQyAgoZpiwKstzRUxiZZZwmnAw1gohsryFVEYZ76PH092Ddz8NhFpvXeOr9qVmKiGUDLmkLUVPlPUuBA9rffDl3vijpkR3MnUnU3cy9Vlmm3k4ZUoA-MczqSjh_A84lHDa</recordid><startdate>20231115</startdate><enddate>20231115</enddate><creator>Porta-Garcia, Miguel Angel</creator><creator>Villa-Medina, Juan Francisco</creator><creator>Gutierrez, Joaquin</creator><creator>Fuentes-Villegas, Alberto Daniel</creator><creator>Porta-Gandara, Miguel Angel</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The purpose is to identify and emit an alert when face-touching behaviors are detected. The wristalert draws awareness to subconscious hand movements toward the face, particularly when a person is exposed to high-risk places where a contaminated surface could be reached, and self-inoculation may occur. It is based upon a trained neuronal network using inertial sensors and implemented into a microcontroller to drive a sound alert when wrist-hand movements may reach the face. The electronic components are embedded in a 3-D-printed case attached to a strap, forming the alerting device. The results show that the wristalert is highly reliable since an 89% prediction accuracy is obtained, providing a feasible system to avoid face touching. This wearable device is replicable, inexpensive, and has low power consumption.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSEN.2023.3322080</doi><tpages>7</tpages><orcidid>https://orcid.org/0009-0003-7430-0823</orcidid><orcidid>https://orcid.org/0000-0002-1647-2649</orcidid><orcidid>https://orcid.org/0000-0002-2298-9898</orcidid><orcidid>https://orcid.org/0000-0002-4045-9102</orcidid></addata></record> |
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subjects | Electronic components Face recognition Faces Fomite transmission Hand (anatomy) Inertial sensing devices Inertial sensors infection prevention Logic gates machine learning (ML) embedded application Microcontrollers Neural networks pathogen spread Power consumption Sensors Three dimensional printing wearable alert Wearable technology Wrist |
title | Wristalert: A Face Touching Alert Through Inertial Sensors and Long Short-Term Memory Neural Network |
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