Sleep (system call)

About: Sleep (system call) is a research topic. Over the lifetime, 2633 publications have been published within this topic receiving 27806 citations. The topic is also known as: Sleep() & sleep().

Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles

Abstract: Background: Sleep is a critical aspect of people’s well-being and as such assessing sleep is an important indicator of a person’s health. Traditional methods of sleep assessment are either time- and resource-intensive or suffer from self-reporting biases. Recently, researchers have started to use mobile phones to passively assess sleep in individuals’ daily lives. However, this work remains in its early stages, having only examined relatively small and homogeneous populations in carefully controlled contexts. Thus, it remains an open question as to how well mobile device-based sleep monitoring generalizes to larger populations in typical use cases. Objective: The aim of this study was to assess the ability of machine learning algorithms to detect the sleep start and end times for the main sleep period in a 24-h cycle using mobile devices in a diverse sample. Methods: We collected mobile phone sensor data as well as daily self-reported sleep start and end times from 208 individuals (171 females; 37 males), diverse in age (18−66 years; mean 39.3), education, and employment status, across the United States over 6 weeks. Sensor data consisted of geographic location, motion, light, sound, and in-phone activities. No specific instructions were given to the participants regarding phone placement. We used random forest classifiers to develop both personalized and global predictors of sleep state from the phone sensor data. Results: Using all available sensor features, the average accuracy of classifying whether a 10-min segment was reported as sleep was 88.8%. This is somewhat better than using the time of day alone, which gives an average accuracy of 86.9%. The accuracy of the model considerably varied across the participants, ranging from 65.1% to 97.3%. We found that low accuracy in some participants was due to two main factors: missing sensor data and misreports. After correcting for these, the average accuracy increased to 91.8%, corresponding to an average median absolute deviation (MAD) of 38 min for sleep start time detection and 36 min for sleep end time. These numbers are close to the range reported by previous research in more controlled situations. Conclusions: We find that mobile phones provide adequate sleep monitoring in typical use cases, and that our methods generalize well to a broader population than has previously been studied. However, we also observe several types of data artifacts when collecting data in uncontrolled settings. Some of these can be resolved through corrections, but others likely impose a ceiling on the accuracy of sleep prediction for certain subjects. Future research will need to focus more on the understanding of people’s behavior in their natural settings in order to develop sleep monitoring tools that work reliably in all cases for all people. [J Med Internet Res 2017;19(4):e118]

Apparatus and method for remotely powering-down a wireless transceiver

Abstract: A portable computer or a similar electronic device having a wireless data communication device such as a Bluetooth transceiver is provided with a power down procedure activated by a remote control device. For example, a single key remote control device emits a radio frequency signal bearing a power down control signal that is transmitted to the portable computer. The control signal is received by a receiver separate from the wireless communication device and initiates a power down process that first causes the portable computer to wake up from a sleep state, if the computer is in a sleep or similar state. The communication device or the computer then invokes a driver that either directly initiates a power down sequence or that invokes another program that initiates a power down sequence. A log file is written during power down that indicates the state of the computer at the time that the power down control signal was received.

System and method for administering light therapy

Abstract: A sleep mask is configured to provide light therapy to a subject. The sleep mask may provide a comfortable delivery mechanism for the light therapy, and may deliver the light therapy to the subject while the subject is asleep, in the process of going to sleep, and/or waking from sleep. In one embodiment, the sleep mask includes one or more of a shield, a strap, a first lighting module, and/or a second lighting module.

Controlling power for a sleeping state of a computer to prevent overloading of the stand-by power rails by selectively asserting a control signal

Abstract: A computer receives a sleep signal that instructs the computer to enter a sleeping state in which stand-by power from a power source is needed. The computer generates a control signal that initiates delivery of stand-by power from the power source in connection with the computer's entering the sleeping state. The control signal is asserted in at least one situation in which the sleep signal is asserted, and the control signal is not asserted in at least one other situation.