期刊论文详细信息
Sensors
Use of Mobile Phones as Intelligent Sensors for Sound Input Analysis and Sleep State Detection
Ondrej Krejcar1  Jakub Jirka2 
[1] Department of Information Technologies, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, Hradec Kralove 50003, Czech Republic;Department of Measurement and Control, Faculty of Electrical Engineering and Computer Science, VSB Technical University of Ostrava, 17. Listopadu 15, Ostrava Poruba 70833, Czech Republic; E-Mails:
关键词: sleep stages detection;    hypnogram;    Windows Mobile;    FFT analysis;   
DOI  :  10.3390/s110606037
来源: mdpi
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【 摘 要 】

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.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.

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