7 results about "Sleep interval" patented technology

Methods, systems, and devices for measuring compressive toughness are described. A system may obtain heart rate variability (HRV) data from a user via a wearable device over a plurality of time intervals, wherein each time interval includes a waking interval at which the user wakes and a sleeping interval at which the user falls asleep. The system may determine a stress index and a recovery index associated with a waking interval of the respective time interval and a sleep recovery index associated with a sleeping interval of the respective time interval. The system may then determine a compressive toughness metric for the user based on a weighted sum of the pressure index, the recovery index, and the sleep recovery index for multiple time intervals, where the compressive toughness metric indicates a relative ability of the user to handle and / or recover from pressure.

The invention relates to the technical field of Internet of Things communication and metering instruments, and particularly discloses an intelligent water meter data monitoring system based on NB-IoT, which is characterized in that an inherent system frame number in a downlink signal of a base station is used as a high-precision network timestamp, and the high-precision network timestamp is associated with a local clock value to form a reference; periodically collecting the time pairs and storing the time pairs into a queue; calculating the drift rate of the local clock relative to the network time by analyzing the ratio relationship of a plurality of time pairs in the queue; when the drift rate continuously exceeds the limit, triggering calibration, and carrying out dynamic compensation calculation on a preset sleep interval according to the drift rate to obtain a corrected actual sleep interval and executing the corrected actual sleep interval; downlink signals in the communication process are multiplexed to serve as a free time source, continuous monitoring and dynamic adjustment are achieved, and long-term reliable synchronization of the intelligent water meter and the network in the whole life cycle is guaranteed on the premise that hardware cost is not increased and power consumption is not remarkably affected.

The application relates to the technical field of Internet of Things communication and metering instrument, and particularly discloses an intelligent water meter data monitoring system based on NB-IoT, which utilizes inherent system frame numbers in base station downlink signals as high-precision network time stamps, associates the time stamps with local clock values to form a reference, periodically collects the time pairs and stores the time pairs in a queue, analyzes the ratio relationship of multiple time pairs in the queue, calculates the drift rate of the local clock relative to the network time, triggers calibration when the drift rate continuously exceeds the limit, dynamically compensates the preset sleep interval according to the drift rate, obtains a corrected actual sleep interval, and executes the actual sleep interval, utilizes the downlink signals in the multiplexing communication process as a free time source, realizes continuous monitoring and dynamic adjustment, and ensures long-term and reliable synchronization between the intelligent water meter and the network in the whole life cycle without increasing hardware cost and without significantly affecting power consumption.

Detecting rapid eye movement (REM) sleep and associated abnormalities can be significant for identifying various neurological disorders. The present disclosure relates to detection of time intervals during which a subject is in REM sleep by leveraging encephalography (EEG) data from selective spectral frequencies. The techniques, as disclosed herein, may use one or more EEG electrodes, more specifically, a single-channel EEG signal offering a simple and a cost effective solution. The disclosed technique may preprocess this EEG data, extract features and / or derived features for one or more time intervals from selective spectral bands e.g., Delta and Gamma. These extracted features may be normalized and clustered to further determine REM, non-REM, and awake time intervals. By leveraging one or more non-EEG sensors to detect presence of muscle tones for the identified REM sleep intervals and by performing sleep pattern analysis, potential REM intervals may be validated for detection of REM behavior disorder.

The application relates to an air conditioner control method and device, an air conditioner, a storage medium and a computer program product. When the air conditioner enters a sleep mode, an initial human body temperature and a real-time human body temperature can be acquired, and the current human body sleep interval is analyzed in combination with the initial human body temperature and the real-time human body temperature. Finally, the air conditioner is controlled to operate according to the analyzed human body sleep interval. In the sleep mode, the initial human body temperature and the real-time human body temperature are combined in real time, the operation control of the air conditioner is realized, the operation of the air conditioner changes according to the change of the real-time human body temperature, and the temperature regulation intelligence of the air conditioner in the sleep mode is greatly improved.

This application discloses a model creation method, apparatus, device, and storage medium. The method includes: obtaining the real-time running phase of a real-time model creation task; determining a real-time sleep interval time matching the real-time running phase based on the real-time running phase; during the real-time running phase, pausing the real-time model creation task once every real-time sleep interval time; after each pause of the real-time model creation task, querying the real-time non-model creation tasks in the task list; if a real-time non-model creation task exists, obtaining the real-time sleep time matching the real-time non-model creation task; wherein, the real-time non-model creation task is executed based on the real-time sleep time; and after waiting for the real-time sleep time, the real-time model creation task continues. The technical solution of this application achieves both a good user interaction experience on the editing page and the ability to complete batch model creation tasks in the shortest possible time.

A wearable physiological monitoring device is configured to determine a wearer's sleep intention. In particular, the device evaluates activity that might be objectively associated with awaking from sleep in order to distinguish between a wearer's intention to end sleep and transitory stirring or other intermittent activity occurring in the context of a longer sleep interval. By evaluating sleep intention more accurately in this manner, the device can advantageously request sleep analysis from a remote server in those instances where a user intends to end a period of sleep (so that this data can be available to the user more quickly), while avoiding unnecessary or redundant server-side processing of sleep data in those instances where a user intends to continue sleeping.