Design and Implementation of a Modularized Polysomnography System

Chang, Da-Wei; Liu, You-De; Young, Chung-Ping; Chen, Jing-Jhong; Chen, Ying-Huang; Chen, Chun-Yu; Hsu, Yu-Wei; Shaw, Fu-Zen; Liang, Sheng-Fu

doi:10.1109/tim.2012.2182853

Cited by 22 publications

(12 citation statements)

References 28 publications

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“…Therefore, sleep care systems are being studied to prevent sleep disorders and to manage sleep from home. Sleep care systems are being developed in the form of a variety of sleep care devices and mobile sleep care applications [6,7]. For example, there are wearable devices that can measure sleep disorders such as snoring and tossing and turning, etc.…”

Section: Introductionmentioning

confidence: 99%

Sleep Information Gathering Protocol Using CoAP for Sleep Care

Choi

Kang

Lee

2017

Entropy

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There has been a growing interest in sleep management recently, and sleep care services using mobile or wearable devices are under development. However, devices with one sensor have limitations in analyzing various sleep states. If Internet of Things (IoT) technology, which collects information from multiple sensors and analyzes them in an integrated manner, can be used then various sleep states can be more accurately measured. Therefore, in this paper, we propose a Smart Model for Sleep Care to provide a service to measure and analyze the sleep state using various sensors. In this model, we designed and implemented a Sleep Information Gathering Protocol to transmit the information measured between physical sensors and sleep sensors. Experiments were conducted to compare the throughput and the consumed power of this new protocol with those of the protocols used in the existing service-we achieved the throughput of about two times and 20% reduction in power consumption, which has confirmed the effectiveness of the proposed protocol. We judge that this protocol is meaningful as it can be applied to a Smart Model for Sleep Care that incorporates IoT technology and allows expanded sleep care if used together with services for treating sleep disorders.

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Section: Introductionmentioning

confidence: 99%

Sleep Information Gathering Protocol Using CoAP for Sleep Care

Choi

Kang

Lee

2017

Entropy

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“…The high correlation coefficients validated the accuracy of our EOG recording system. For more details of the comparison experiment and results, please see [26]. Our eye mask system has met the verification standard on 16 subjects in continuous overnight recording.…”

Section: B Verification Of the Eog Signal That Is Acquired From The mentioning

confidence: 99%

Development of an EOG-Based Automatic Sleep-Monitoring Eye Mask

Liang

Kuo

Lee

et al. 2015

IEEE Trans. Instrum. Meas.

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Health care researchers have recently developed several home-based sleep monitoring systems and mobile applications that support healthy sleep by monitoring a user's sleep environment, activities, or sleep quality. This study describes the design and evaluation of an electrooculogram (EOG)-based system for an automatic sleep monitoring. Compared with polysomnogram or electroencephalogram recordings, EOG has the advantage of easy placement and can be operated by the users themselves. We also design an intelligent eye mask that is user friendly for measuring sleep stage and quality. Two user experiments were carried out to demonstrate that the proposed system produces valid measurements of sleep stage and sleep quality and has good usability and reliability while not disturbing sleep significantly. These findings suggest that our system can also be applied to long-term sleep monitoring or sleep environment control to improve the user's sleep quality and make sleep more comfortable.

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“…If you use a sleep care system, you can reduce inconveniences and time spent visiting the hospital and you can easily check your sleep state. Thanks to these advantages, many sleep care applications for smartphones are being developed [3] [4].…”

Section: Introductionmentioning

confidence: 99%