30 results about "Sleep pattern" patented technology

A system and method for generating patient care instructions based on real-time sensor and medical data. The method includes receiving time-stamped sensor data from a sensor network comprising motion, occupancy, and environmental sensors, and receiving medical data associated with a patient, including medical conditions, treatment history, medication data, and biometric data. The sensor data is enriched with room-specific information, and activity pattern data is generated in real time using a pattern recognition model. The activity pattern data includes mobility, sleep patterns, medication adherence, statistical measures, temporal patterns, and correlations with medical data. Anomalies indicating potential health risks are detected by comparing current activity patterns with baseline data. A prediction model, trained on historical patient data, assesses the patient's health and generates care instructions accordingly. The care instructions are securely delivered to patient devices, caregiver applications, or automated medication dispensing systems, enabling timely interventions and continuous patient monitoring.

A system includes a processor that collects data representing activity levels, sleep patterns, and food intake from an information collection device attached to a dog, transmits the collected data to an analysis server, wherein the analysis server inputs the collected data into a generative artificial intelligence model and analyzes the data, transmits analysis results to a terminal and notifies a user, receives user input regarding questions or symptoms of the dog and generates advice using the generative artificial intelligence model, transmits the generated advice to the terminal for display to the user, and provides online consultation reservation with a veterinarian.

The present invention relates to a system and a method for allowing a user to connect to a controller much faster and more conveniently by performing initial connection between system components through BLE / Wi-Fi chipsets provided in a sensor unit and the controller. A smart mattress networking system according to an embodiment of the present invention comprises: a controller for adjusting a hardness of a smart mattress under control of a monitoring server, wherein the controller establishes a state ready for connection to a user terminal through Bluetooth communication using an internally provided BLE / Wi-Fi chipset, and performs initial connection to the user terminal by inputting an SSID / PW delivered from the user terminal; a user terminal having a monitoring application installed therein to record and report a sleep pattern through wireless communication with the monitoring server, wherein the user terminal identifies Wi-Fi information of a current space and delivers an SSID / PW to the controller through Bluetooth communication; a sensor unit for sensing (measuring) pressure (body pressure) during a sleep of a user located on the smart mattress and transmitting the sensed pressure to the monitoring server through the controller; and the monitoring server for analyzing a sleep posture on the basis of a sensing value of the sensor unit, determining a hardness suitable for the sleep posture, and transmitting the determined hardness to the controller.

The invention is applied to the field of sleep management, and discloses a sleep state recognition regulation and control method and system.The method comprises the steps that piezoelectric signal data captured by piezoelectric sensing equipment and optical pulse signal data captured by wearable sensing equipment in the sleep process of a target user are obtained; body movement artifact removal processing is conducted on the piezoelectric signal data and the optical pulse signal data, and first piezoelectric signal data and first optical pulse signal data are obtained; performing fusion processing on the first piezoelectric signal data and the first optical pulse signal data to obtain a target fusion feature; determining a sleep type of the target user based on the target fusion feature, performing sleep state recognition on the target fusion feature based on the sleep type, and generating a sleep core index corresponding to a recognition result; and according to the sleep type and the sleep core index, generating and executing a sleep regulation strategy of the target user. According to the method, the sleep quality of the user is improved.

A system is provided.SOLUTION: The system includes an electric stimulation means for relaxing the muscles around the eyes, a camera means for monitoring the state of the pupils, a sensor means for analyzing the sleep pattern of the user, a notification means for notifying the timing of the eye lotion, and a server means for managing data obtained from the respective means.SELECTED DRAWING: Figure 1

This invention provides a radar-based sleep staging method, terminal, and storage medium. The method includes: acquiring human echo signals detected by radar over a preset monitoring area in real time, and calculating a sleep staging index corresponding to each calculation cycle during the sleep period based on the human echo signals; calculating a sleep staging threshold corresponding to the current calculation cycle based on the standard deviation of the sleep staging indices corresponding to multiple calculation cycles near the current calculation cycle; and determining the sleep staging result for the current calculation cycle based on the sleep staging index and the corresponding sleep staging threshold. This method can adaptively set the sleep staging threshold based on the user's own sleep patterns, thereby improving the accuracy of sleep staging calculations.

A system is provided.SOLUTION: A system comprising: a terminal including a sensor that detects a motion of a baby, a crying voice, a room temperature, a humidity, and an intensity of illumination; a server that receives and stores data transmitted from the terminal; a unit that learns a sleep pattern of the baby using an artificial intelligence model installed in the server and proposes an optimal method of putting the baby to sleep and an optimal environment setting; SELECTED DRAWING: Figure 1

A system and method for generating patient care instructions based on real-time sensor and medical data. The method includes receiving time-stamped sensor data from a sensor network comprising motion, occupancy, and environmental sensors, and receiving medical data associated with a patient, including medical conditions, treatment history, medication data, and biometric data. The sensor data is enriched with room-specific information, and activity pattern data is generated in real time using a pattern recognition model. The activity pattern data includes mobility, sleep patterns, medication adherence, statistical measures, temporal patterns, and correlations with medical data. Anomalies indicating potential health risks are detected by comparing current activity patterns with baseline data. A prediction model, trained on historical patient data, assesses the patient's health and generates care instructions accordingly. The care instructions are securely delivered to patient devices, caregiver applications, or automated medication dispensing systems, enabling timely interventions and continuous patient monitoring.

1. Name of this design product: Children's Sleep Training Clock. 2. Purpose of this design: To correct children's sleep patterns. Establish a good daily routine. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

Detection of fast eye movement (REM) sleep and associated abnormalities is important for identifying various nervous system diseases. The present disclosure relates to the detection of time intervals during which a subject is in REM sleep by utilizing electroencephalogram (EEG) data from selective spectral frequencies. The techniques as disclosed herein may use one or more EEG electrodes, and more particularly, single channel EEG signals provide a simple and cost-effective solution. The disclosed techniques may pre-process the 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 waking time intervals. By using one or more non-EEG sensors to detect the presence of muscular tension of the identified REM sleep intervals, and by performing sleep pattern analysis, potential REM intervals can be verified to detect REM behavioral disorders.

The invention relates to a sleep state metric index calibration system and a management system thereof.The calibration system comprises a first sleep monitor, a second sleep monitor and / or a terminal, the first sleep monitor collects physiological feature data in a sleep state and determines a first sleep mode, sending the own sleep state measurement index and the first sleep mode to a second sleep monitor; the second sleep monitor and the first sleep monitor start monitoring at the same time, bio-electricity signal data related to time is collected to serve as second sleep feature data, and a second sleep mode is determined; the second sleep monitor generates update information of a sleep state measurement index of the first sleep monitor on the basis of a difference between the first sleep mode and the second sleep mode in the same sleep cycle by taking the second sleep mode as a reference; and the second sleep monitor transmits update information to the first sleep monitor through direct communication or indirect terminal transmission so as to complete calibration or correction of the sleep state measurement index of the first sleep monitor.

A mobile device for identifying a potential candidate includes a screen, a sensor, and a control system. The sensor configured to generate sensor data associated with use of the mobile device. The control system is configured to: extract location data from the sensor data, the location data including physical location of the mobile device at different time intervals; determine from the location data whether mobility of the mobile device is below a threshold; extract mobile device usage data from the sensor data; determine, from the mobile device usage data, a pattern of use of the mobile device to obtain a sleeping pattern of the potential candidate; and based at least in part on the mobility of the mobile device being below a threshold and the pattern of use of the mobile device, cause the screen to display an alert.

A system is provided.SOLUTION: A system comprising: means for collecting genetic information of an individual; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for integrating and analyzing the genetic information and the daily life data; means for generating a personalized health plan based on the analysis; and means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan.SELECTED DRAWING: Figure 1

Proposed is a health care monitoring and smart home convergence system based on a built-in ceiling IoT radar sensor. The health care monitoring and smart home convergence system includes the built-in ceiling IoT radar sensor, and a health analysis part. The built-in ceiling IoT radar sensor is installed into a ceiling of a bedroom, and configured to measure a user's heart rate or respiratory rate on the basis of time of flight (ToF) of a radar signal to generate biosignal data. The health analysis part is configured to analyze the user's sleep pattern on the basis of the biosignal data, and uses the sleep pattern to generate health prediction information on the user's health state.

Multi-mode neurological and cardiopulmonary monitoring systems may be designed for the especially challenging needs of very fragile patients, such as neonates and infants. Compact, lightweight, time-synchronized wireless sensors may be built into wearable modules. The modules' skin-friendly encapsulations and bio-integrated form factors reduce the risk of iatrogenic injury while permitting natural motion and comforting touch. The system's integrated sensors include electroencephalography, near-infrared spectroscopy, electrocardiography, seismocardiography, photoplethysmography, motion, and temperature. By combining and analyzing the sensors' time-synchronized readings, the system can calculate heart rate, respiratory rate, pulse oxygenation, temperature, perfusion index, tidal volume, pulse wave velocity, and pulse arrival time (a surrogate for blood pressure). Advanced algorithms can further evaluate sleep patterns and detect arrhythmias, strokes, hemorrhaging and pre-seizure events. Other design features facilitate low cost, ruggedness, and ease of use in both hospital and non-hospital settings.

The present invention provides an information processing system, comprising: means for collecting activity amount, sleep pattern, and food intake data from an information collection means worn on a dog body; means for transmitting the collected data to a resolution server; the device is used for inputting the collected data into the generative artificial intelligence model by the analysis server and analyzing the data; the device is used for sending an analysis result to the terminal and informing a user; the device is used for receiving input about questions and dog symptoms from a user and generating suggestions through a generative artificial intelligence model; means for transmitting the generated suggestion to the terminal and displaying the suggestion to the user; a device for providing veterinary online consultation appointment functionality.

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.

This application relates to the field of smart home appliance technology, and discloses a method for regulating the sleep environment, applied to a sleep system, comprising: determining the user's sleep type based on the user's historical sleep time information; controlling the sleep system to enter or exit daytime sleep mode according to the user's sleep type and the current time, to regulate indoor temperature, and / or humidity, and / or air quality improvement measures, and / or sound settings; wherein the user's sleep type includes daytime sleepers or non-daytime sleepers. This method reduces the impact of external interference on the user's daytime sleep quality and improves the user's daytime sleep quality. This application also discloses a sleep environment regulation device and sleep system, and a computer-readable storage medium.

A system is provided.SOLUTION: The system includes a means for obtaining basic information of the child, a means for monitoring the child's health condition, a means for analyzing the monitored data and detecting abnormalities, a means for notifying abnormalities in real time, a means for recording the child's sleep pattern and generating an appropriate sleep schedule, a means for guiding the child's sleep based on the sleep schedule, a means for suggesting educational play based on the child's age and interests, and a means for detecting and reporting abnormal behavior in real time.SELECTED DRAWING: Figure 1

This invention relates to a sleep-aiding method and system based on heart rate variability biofeedback, belonging to the field of sleep health management technology. It solves the problem that existing sleep-aiding technologies, which rely on visual biofeedback and lack mechanisms for recognizing sleep trends and automatically exiting sleep patterns, are prone to overstimulation. The method includes: acquiring vital signs signals at multiple time steps and a sleep-aiding rhythm signal at the current time step; the vital signs signals include PPG sensor signals and IMU sensor signals; determining the signal quality index for each time step based on the PPG sensor signals from multiple time steps; calculating the body movement intensity at each time step based on the IMU sensor signals from multiple time steps; and adjusting the sleep-aiding rhythm signal based on the signal quality index and body movement intensity at the current time step or multiple time steps. This invention achieves full-process sleep management with light-free biofeedback, automatic sleep trend recognition, and nighttime awakening re-intervention, improving the effectiveness of sleep-aiding guidance.

The present invention relates to a motion mattress control system and, more specifically, to a motion mattress control system capable of analyzing a sleeping posture of a user using a body pressure sensor during sleep on a motion mattress having a plurality of strings divided into regions, and adjusting air pressure (hardness) of the divided (separated) strings according to the analysis result. The motion mattress control system according to an embodiment of the present invention comprises: a plurality of strings provided inside a motion frame having a structure bent in multiple stages to adjust an angle; a body pressure sensor provided on the upper portions of the strings for regularly sensing a plurality of pressures (body pressure) of a human body during sleep and outputting the sensed pressures to a controller; the controller for autonomously learning a sleep posture using the plurality of body pressures to find a sleep pattern and determining a hardness suitable for the sleep pattern and controlling an air pump; and a plurality of air pumps connected to the strings for injecting or discharging air into or from the strings by control of the controller so as to adjust the hardness.

1. Name of the product in this design: Graphical User Interface for Sleep Diary Questionnaire of Electronic Device. 2. Intended use of this design: for use in an electronic device. 3. The key design feature of this product is its graphical user interface. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: Used for conducting questionnaire surveys on users' sleep patterns. 7. Human-computer interaction methods of the graphical user interface: In designs 1 to 5, clicking the "Next Question" button at the bottom of the main view switches to the next questionnaire interface; in design 6, text content can be entered in the middle of the main view to record sleep status; in design 7, clicking the "Submit" button at the bottom of the main view submits the questionnaire; in design 8, clicking the "Next Question" button at the bottom of the main view switches to interface state diagram 1, clicking the "Next Question" button at the bottom of interface state diagram 1 switches to interface state diagram 2, clicking the "Next Question" button at the bottom of interface state diagram 2 switches to interface state diagram 3, clicking the "Next Question" button at the bottom of interface state diagram 3 switches to interface state diagram 4, clicking the "Next Question" button at the bottom of interface state diagram 4 switches to interface state diagram 5, text content can be entered in the middle of interface state diagram 5, switching to interface state diagram 6, and clicking the "Submit" button at the bottom of interface state diagram 6 submits the questionnaire.

A system and method for generating patient care instructions based on real-time sensor and medical data The method includes receiving time-stamped sensor data from a sensor network comprising motion, occupancy, and environmental sensors, and receiving medical data associated with a patient, including medical conditions, treatment history, medication data, and biometric data. The sensor data is enriched with room-specific information, and activity pattern data is generated in real time using a pattern recognition model. The activity pattern data includes mobility, sleep patterns, medication adherence, statistical measures, temporal patterns, and correlations with medical data. Anomalies indicating potential health risks are detected by comparing current activity patterns with baseline data. A prediction model, trained on historical patient data, assesses the patient's health and generates care instructions accordingly. The care instructions are securely delivered to patient devices, caregiver applications, or automated medication dispensing systems, enabling timely interventions and continuous patient monitoring.

The system according to this embodiment aims to generate sleep-inducing background music and noise optimized for each individual. [Solution] A system according to an embodiment includes a collection unit, an analysis unit, and a generation unit. The collection unit collects video data, audio data, and subjective assessment data from a user while they sleep. The analysis unit analyzes the data collected by the collection unit to analyze the user's sleep patterns and preferences. The generation unit generates background music and noise appropriate for the user based on the analysis results obtained by the analysis unit.

Disclosed herein are systems and methods for monitoring PAP treatment adherence. Systems and methods disclosed herein provide techniques to quantify PAP wear time in proportion to the time in bed or time asleep, and take into account individual factors affecting sleep patterns to provide feedback to patients and providers for motivating adherent use of the PAP device.

A patient's rapid eye movements (REM) can be evaluated via a virtual reality (VR) system, which can include a VR headset in electronic communication with a computing device. The patient can don the VR headset while she is sleeping. Optionally, the VR system can be used in a home setting, where the patient will likely be able to recreate her usual sleep patterns. Using varying combinations of sensors and cameras, the VR headset tracks the patient's eye movements while she sleeps to identify different sleep stages, including REM periods. Observing the patient's sleep patterns provides great insight into her health as well as opportunities to improve sleep.

An information processing method according to the present disclosure comprises the following performed by a computer: acquiring user data relating to a user's sleep; generating, on the basis of the acquired user data, classification data in which the type of the user's sleep is classified as a given type of sleep, and recommended action data relating to a recommended action which is an action recommended for improving the user's sleep; and presenting the generated classification data and recommended action data to the user.

This invention discloses an apparatus for conducting electroencephalography while allowing for secure and easy application to a human subject's forehead. The apparatus may be changed in size to fit each human subject without affecting the electronic components within the apparatus. Operation of the apparatus may be by a computer programming product in the nature of a software on a computer or an application on a mobile computer device. Signals collected from the apparatus may be used in a variety of applications, including brain computer interface, transport safety, neurofeedback, esports, virtual and augmented reality, as well as tracking sleep patterns.

The invention relates to a botanical sleep-aiding beverage and a preparation method thereof, and belongs to the technical field of food processing and functional food. The botanical sleep-aiding beverage consists of the following components in percentage by mass: 0.5 to 90 percent of spina date seeds, 0.001 to 80 percent of gastrodia elata, 0.01 to 80 percent of lily bulbs, 0.01 to 50 percent of Chinese wolfberry fruits, 0.001 to 50 percent of lucid ganoderma, 0.01 to 80 percent of poria cocos, 0.01 to 50 percent of longan, 0.01 to 50 percent of rhizoma polygonati, 0.001 to 50 percent of passion flower powder, 0.001 to 50 percent of North American cherry powder, 0.01 to 70 percent of roxburgh rose, 0.001 to 50 percent of walnut peptide, 0.01 to 60 percent of erythritol, 0.01 to 60 percent of xylitol, 0.0001 to 10 percent of stevioside, 0.001 to 3 percent of a preservative, 0.01 to 12 percent of a thickening stabilizer, 0.01 to 8 percent of an acidity regulator, 0.001 to 5 percent of an antioxidant and the balance of purified water. The botanical sleep-aiding beverage has the advantages that the sleep quality of a patient is obviously improved; therefore, the purposes of calming the mind, soothing the nerves, relaxing nerves, relieving anxiety, quickly inducing sleep, increasing the deep sleep proportion, improving the sleep structure, reducing night awakening, improving the sleep comfort level and avoiding the dim feeling in the next day are achieved, and the sleep state can be gradually regulated, the mental state can be improved and the physical recovery can be realized after long-term taking.