Multiparameter Sleep Monitoring Using a Depth Camera - Biomedical Engineering Systems and Technologies - page 299

over the body frequently, and the participant was almost in static condition in experi-
ment II. That's the reason that the measurement accuracy of breathing is lower in expe-
riment I than in experiment II. One possible solution method is to suspend the breathing
measurement while the user is moving.

6 Conclusions

In this study, we proposed a depth image sequence analysis technique to monitor
user's sleep position, body movement, and breathing rate on the bed without any
physical contact. A depth image-based processing method is proposed to monitor the
sleeping conditions. The results of experimental I showed that the proposed method is
promising to detect the head and torso with various sleeping postures and body
shapes. The results of experimental II showed that the system can accurately monitor
the sleeping conditions. Therefore, we confirm that the system could provide relevant
sleep information and sleep report to the user. Furthermore, the sleep parameters
which we detected can provide to the sleep center to diagnose the sleep problems.
This study is important for providing a non-contact technology to measure the sleep
conditions and assist users in better understanding of his sleep quality. In the future,
we expect to detect more sleeping conditions and solve some measurement limita-
tions, such as the problems of overlapping. Besides, we will develop a multimedia
feedback sleep-assisted system which can detect the breathing status and provide
appropriate sleeping guidance in real time to help users shorten the time to fall asleep.
In addition, a web-based browser will be developed to provide the personalized sleep-
ing information to the user.

Acknowledgements. This work was supported in part by the National Science Coun-
cil, Taiwan, under grants NSC 98-2221-E-002-128-MY3. And many thanks to
HealthConn Corp. (http://hcc.healthconn.com/), who provided many assistances of
the knowledge.

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