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Use of Mobile Phones as Intelligent Sensors for Sound Input Analysis and Sleep State Detection
Sleep is not just a passive process, but rather a highly dynamic process that is terminated by waking up. Throughout the night a specific number of sleep stages that are repeatedly changing in various periods of time take place. These specific time intervals and specific sleep stages are very import...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231421/ https://www.ncbi.nlm.nih.gov/pubmed/22163941 http://dx.doi.org/10.3390/s110606037 |
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author | Krejcar, Ondrej Jirka, Jakub Janckulik, Dalibor |
author_facet | Krejcar, Ondrej Jirka, Jakub Janckulik, Dalibor |
author_sort | Krejcar, Ondrej |
collection | PubMed |
description | Sleep is not just a passive process, but rather a highly dynamic process that is terminated by waking up. Throughout the night a specific number of sleep stages that are repeatedly changing in various periods of time take place. These specific time intervals and specific sleep stages are very important for the wake up event. It is far more difficult to wake up during the deep NREM (2–4) stage of sleep because the rest of the body is still sleeping. On the other hand if we wake up during the mild (REM, NREM1) sleep stage it is a much more pleasant experience for us and for our bodies. This problem led the authors to undertake this study and develop a Windows Mobile-based device application called wakeNsmile. The wakeNsmile application records and monitors the sleep stages for specific amounts of time before a desired alarm time set by users. It uses a built-in microphone and determines the optimal time to wake the user up. Hence, if the user sets an alarm in wakeNsmile to 7:00 and wakeNsmile detects that a more appropriate time to wake up (REM stage) is at 6:50, the alarm will start at 6:50. The current availability and low price of mobile devices is yet another reason to use and develop such an application that will hopefully help someone to wakeNsmile in the morning. So far, the wakeNsmile application has been tested on four individuals introduced in the final section. |
format | Online Article Text |
id | pubmed-3231421 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-32314212011-12-07 Use of Mobile Phones as Intelligent Sensors for Sound Input Analysis and Sleep State Detection Krejcar, Ondrej Jirka, Jakub Janckulik, Dalibor Sensors (Basel) Article Sleep is not just a passive process, but rather a highly dynamic process that is terminated by waking up. Throughout the night a specific number of sleep stages that are repeatedly changing in various periods of time take place. These specific time intervals and specific sleep stages are very important for the wake up event. It is far more difficult to wake up during the deep NREM (2–4) stage of sleep because the rest of the body is still sleeping. On the other hand if we wake up during the mild (REM, NREM1) sleep stage it is a much more pleasant experience for us and for our bodies. This problem led the authors to undertake this study and develop a Windows Mobile-based device application called wakeNsmile. The wakeNsmile application records and monitors the sleep stages for specific amounts of time before a desired alarm time set by users. It uses a built-in microphone and determines the optimal time to wake the user up. Hence, if the user sets an alarm in wakeNsmile to 7:00 and wakeNsmile detects that a more appropriate time to wake up (REM stage) is at 6:50, the alarm will start at 6:50. The current availability and low price of mobile devices is yet another reason to use and develop such an application that will hopefully help someone to wakeNsmile in the morning. So far, the wakeNsmile application has been tested on four individuals introduced in the final section. Molecular Diversity Preservation International (MDPI) 2011-06-03 /pmc/articles/PMC3231421/ /pubmed/22163941 http://dx.doi.org/10.3390/s110606037 Text en © 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Krejcar, Ondrej Jirka, Jakub Janckulik, Dalibor Use of Mobile Phones as Intelligent Sensors for Sound Input Analysis and Sleep State Detection |
title | Use of Mobile Phones as Intelligent Sensors for Sound Input Analysis and Sleep State Detection |
title_full | Use of Mobile Phones as Intelligent Sensors for Sound Input Analysis and Sleep State Detection |
title_fullStr | Use of Mobile Phones as Intelligent Sensors for Sound Input Analysis and Sleep State Detection |
title_full_unstemmed | Use of Mobile Phones as Intelligent Sensors for Sound Input Analysis and Sleep State Detection |
title_short | Use of Mobile Phones as Intelligent Sensors for Sound Input Analysis and Sleep State Detection |
title_sort | use of mobile phones as intelligent sensors for sound input analysis and sleep state detection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231421/ https://www.ncbi.nlm.nih.gov/pubmed/22163941 http://dx.doi.org/10.3390/s110606037 |
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