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Preventing Undesired Face-Touches With Wearable Devices and Haptic Feedback

The alarming morbidity of COVID-19 has drawn the attention to the social role of hygiene rules, with a particular focus on the importance of limiting face-touch occurrences. To deal with this aspect, we present No Face-Touch, a system able to estimate hand proximity to face and notify the user whene...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IEEE 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545332/
https://www.ncbi.nlm.nih.gov/pubmed/34812343
http://dx.doi.org/10.1109/ACCESS.2020.3012309
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description The alarming morbidity of COVID-19 has drawn the attention to the social role of hygiene rules, with a particular focus on the importance of limiting face-touch occurrences. To deal with this aspect, we present No Face-Touch, a system able to estimate hand proximity to face and notify the user whenever a face-touch movement is detected. In its complete setup, the system consists of an application running on the smartwatch and a wearable accessory. Its ease of implementation allows this solution to be ready-to-use and large-scale deployable. We developed two gesture detection approaches compatible with sensors embedded in recent smartwatches, i.e. inertial and magnetic sensors. After preliminary tests to tune target gesture parameters, we tested the two approaches and compared their accuracy. The final phase of this project consisted in exploiting the most robust approach in a daily living scenario during a 6-days campaign. Experimental results revealed the effectiveness of the proposed system, demonstrating its impact in reducing the number of face-touches and their duration.
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spelling pubmed-85453322021-11-18 Preventing Undesired Face-Touches With Wearable Devices and Haptic Feedback IEEE Access Robotics and Automation The alarming morbidity of COVID-19 has drawn the attention to the social role of hygiene rules, with a particular focus on the importance of limiting face-touch occurrences. To deal with this aspect, we present No Face-Touch, a system able to estimate hand proximity to face and notify the user whenever a face-touch movement is detected. In its complete setup, the system consists of an application running on the smartwatch and a wearable accessory. Its ease of implementation allows this solution to be ready-to-use and large-scale deployable. We developed two gesture detection approaches compatible with sensors embedded in recent smartwatches, i.e. inertial and magnetic sensors. After preliminary tests to tune target gesture parameters, we tested the two approaches and compared their accuracy. The final phase of this project consisted in exploiting the most robust approach in a daily living scenario during a 6-days campaign. Experimental results revealed the effectiveness of the proposed system, demonstrating its impact in reducing the number of face-touches and their duration. IEEE 2020-07-27 /pmc/articles/PMC8545332/ /pubmed/34812343 http://dx.doi.org/10.1109/ACCESS.2020.3012309 Text en This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
spellingShingle Robotics and Automation
Preventing Undesired Face-Touches With Wearable Devices and Haptic Feedback
title Preventing Undesired Face-Touches With Wearable Devices and Haptic Feedback
title_full Preventing Undesired Face-Touches With Wearable Devices and Haptic Feedback
title_fullStr Preventing Undesired Face-Touches With Wearable Devices and Haptic Feedback
title_full_unstemmed Preventing Undesired Face-Touches With Wearable Devices and Haptic Feedback
title_short Preventing Undesired Face-Touches With Wearable Devices and Haptic Feedback
title_sort preventing undesired face-touches with wearable devices and haptic feedback
topic Robotics and Automation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545332/
https://www.ncbi.nlm.nih.gov/pubmed/34812343
http://dx.doi.org/10.1109/ACCESS.2020.3012309
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