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
Hauptverfasser: Porta-Garcia, Miguel Angel, Villa-Medina, Juan Francisco, Gutierrez, Joaquin, Fuentes-Villegas, Alberto Daniel, Porta-Gandara, Miguel Angel
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container_end_page 27966
container_issue 22
container_start_page 27960
container_title IEEE sensors journal
container_volume 23
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
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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. 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source IEEE Electronic Library (IEL)
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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