93 results about "Sleep patterns" patented technology

The invention discloses a self-adaptive music synthesis sleep aiding method and system based on physiological feedback. The method comprises the following steps: acquiring physiological data of a user; preprocessing the physiological data; evaluating the sleep state of the user based on the preprocessed physiological data; defining a music parameter space according to the sleep state; optimizing music parameters based on the sleep state and the music parameter space; generating and playing music according to the optimized music parameters; while music is played, physiological reactions of the user are continuously monitored, music parameters are adjusted in real time based on the physiological reactions, and feedback circulation is formed; analyzing a long-term sleep pattern of the user based on the data obtained in the feedback loop; according to the long-term sleep mode, updating a music parameter space and an optimization strategy; security monitoring is executed, and intervention is carried out when an abnormal condition is detected; according to the invention, a plurality of key indexes such as sleep time, deep sleep proportion, sleep quality and the like are obviously improved.

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.

To provide an information processing device capable of presenting a user an appropriate advice based on menstrual and sleep patterns.SOLUTION: An information processing device 10 includes: an acquisition unit that acquires information representing the status of a target user from one or multiple sensors; and a control unit that evaluates a menstrual cycle of a user by evaluating the sleep state of the target user by performing a first processing on the information and by performing a second processing different from the first processing on the information. The control unit controls to output a proposal for the target user on an external unit based on the evaluation of sleep status and the evaluation of menstrual rhythm.SELECTED DRAWING: Figure 1

Neurophysiologic assessment system includes an ingestion data hub for generating clean data from heart rhythm data, a neuroscience processing unit for generating primary metrics from the clean data, a contextual analysis unit for receiving and analyzing external contextual data, a behavior analysis unit for generating secondary metrics from the clean data, primary metrics, and external contextual data, and a workflow management unit for controlling the ingestion data hub, and neuroscience processing, contextual analysis, and behavior analysis units. Secondary metrics include at least one of emotional wellbeing, energy, mood, and peak immersion value for a given time frame. The external contextual data include at least one of location, proximity of related persons, time of day, day of a week, weather conditions, traffic conditions, measured activity levels, calendar events, biofeedback, survey results and information provided by the participant, tracked usage of software applications, engagement with social media, and sleep patterns.

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.

There is provided a sleep tracking system comprising a baby sleep tracking device and an adult sleep tracker device. The baby sleep tracking device is configured to track a baby's sleep patterns. The adult sleep tracker device is configured to track an adult's sleep patterns. The sleep tracking system is configured to generate a coordinated sleep schedule.

Smart gear, which includes electrically conductive fabric, is provided to monitor health parameters, conduct transactions, and generate power. For example, the smart gear may include one or more sensors coupled to the fabric and / or electrically conductive fibers woven into the fabric. The one or more sensors may monitor health parameters such as breathing patterns, sleep patterns, heart murmurs, and so forth. The smart gear may include one or more wireless regions that power electronic devices based on inductive charging.

A software-based system for mental health management and suicide prevention that utilizes biometric data from wearable devices. The system extracts and analyzes physiological metrics, such as heart rate, sleep patterns, and physical activity levels, to identify patterns, trends, or anomalies indicative of emerging mental health issues. Advanced algorithms process the collected data to detect potential mental health concerns before they escalate into crises, enabling proactive intervention and support.

Introduced are methods and systems for monitoring a person's sleeping patterns, and detecting episodes of sleeping disorders such as snoring and sleep apnea. In one embodiment, a sensor strip attached to the mattress monitors the user's breathing, and detects signature frequencies corresponding to snoring and sleep apnea. Once a sleeping disorder is detected, a notification can be sent to a device associated with the user, or the user's bed can be automatically adjusted to alleviate the sleeping disorder.

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 discloses a wearable wellness band that tracks health data and detects early signs of illness or sickness in humans. The invention is a wearable band equipped with various sensors, including those for heart rate, blood pressure, temperature, GSR, oxygen saturation, step count, EMG, altitude, air quality, UV exposure, calories burn, stress level, humidity, and sleep patterns. It utilizes advanced algorithms and data analytics techniques to process and analyze the collected data. By comparing the data against established health baselines and patterns, the band can identify deviations, anomalies, or early signs of illness. It provides timely notifications and recommendations to the user, promoting early intervention and proactive health management.

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 utility model discloses a human body gravity center transformation bed for sleeping, which comprises a bed head and a bed tail, support frames are respectively arranged at the positions of the bed head and the bed tail, a rotating shaft is arranged between the two support frames, a bed plate is arranged on the rotating shaft, the human body gravity center transformation bed further comprises a driving mechanism, and the driving mechanism drives the bed plate to reciprocate up and down on the horizontal plane around the shaft. The bed breaks through a traditional sleep mode which is changed from a static mode to a dynamic mode, so that the position of the gravity center of a human body is changed from a fixed mode to a whole-course continuous or intermittent movement mode in a heavy sleep process of a person, pressure and obstacles caused by the fixed position of the gravity center of the human body to internal circulation of the person are prevented, the person can quickly fall asleep, and the body of a long-term bedridden patient can be relieved; the problems of a traditional bed are well solved, the structure is simple, and the manufacturing cost is low.

The invention provides a light therapy system control method and device based on intelligent analysis and a storage medium, and the method comprises the steps: obtaining an MEQ scale test result of a user, and obtaining a sleep mode of the user; detecting basic data of a user; generating an initial illumination scheme based on basic data and the sleep mode; the initial illumination scheme at least comprises initial parameter setting of illumination intensity, starting time, color temperature, wavelength, stroboflash and treatment course of the illumination treatment system; in the illumination process of the user, brain wave data and heart rate data of the user are collected in real time; outputting corresponding correction data by using a preset analysis model; and correcting the initial illumination scheme based on the correction data to obtain a corrected illumination scheme for controlling the illumination treatment system. According to the invention, the defects that the traditional illumination treatment system cannot combine with the multi-dimensional information of the user and cannot automatically adjust the illumination scheme according to the real-time physiological state of the user are overcome.

The present invention provides a personalized sleep pattern providing system comprising: a data collection unit configured to collect sleep-arousal data including sleep pattern information about a user and work-arousal data including information about the degree of arousal during a period of arousal of the user; an analysis unit configured to estimate a homeostatic sleep pressure and a biological sleep threshold on the basis of the sleep-arousal state data and the work-arousal data and calculate a predicted degree of arousal on the basis of the homeostatic sleep pressure and the biological sleep threshold; and a sleep pattern providing unit configured to generate a personalized sleep pattern on the basis of the predicted degree of arousal, wherein the personalized sleep pattern includes adaptive biologically-segmented sleep including required main sleep and sleep immediately before work.

A bed includes components to control temperature of a sleep surface, for example based on time and historical usage patterns by a user. In some embodiments the temperature of the sleep surface is controlled based on information indicating a sleep state of the user. In some embodiments the temperature is dynamically adjusted so to achieve particular sleep states and / or sleep patterns for the user. In some embodiments the temperature and timing of temperature adjustments is iteratively adjusted over multiple sleep sessions so to achieve improvements in sleep states and / or sleep quality for the user.

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

To provide a system capable of improving sleep quality by proposing high-precision improvement methods and sleep aids and utilizing data such as sleep patterns.SOLUTION: The system includes: means of collecting data such as sleep patterns obtained from wearable devices; means of analyzing the collected data using AI and proposing individual improvement methods and sleep aids; and means of proposing the proposed improvement methods and sleep aids to a user.SELECTED DRAWING: Figure 1

An artificial intelligence (AI) based system for nutrient estimation, and meal planning comprises a server processor coupled with a database in network communication with a plurality of users connected over the said network. The database stores characteristics that represent physical conditions about the users (e.g. DNA test results, family health history, BMI along with meal patterns, hunger, sleep patterns, and food habits). The database coupled with the said server processor includes a diet plan dataset, and an ingredient nutritional information dataset. The server processor is operable to generate a meal profile for each of the users, wherein each meal profile comprises a plurality of individual characteristics representative of the user's physical condition. The system analyses the stored characteristics, and recommended nutritional intake levels to generate at least one meal plan.

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 method and apparatus to improve sleep aid efficacy are provided. The method comprises monitoring the sleeping patterns of a user utilizing a non-intrusive sleep monitoring device. The method further correlates the user's sleep quality and sleep quantity with use of the sleep aid. In one embodiment, the method adjusts the sleep aid based on the sleep statistics. The efficacy of sleep aids is increased by monitoring user's sleep patterns continuously.

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

The invention discloses an intelligent magnetic pulse sleep-aiding system with a self-adaptive adjustment function. The intelligent magnetic pulse sleep-aiding system comprises sleep physiological signal acquisition equipment, an intelligent processing terminal and multifunctional insomnia treatment equipment, the intelligent processing terminal comprises a data transceiving module, a data processing module, a model analysis module and an intervention adjustment module; the sleep physiological signal acquisition device is a portable wearable acquisition device. According to the intelligent magnetic pulse sleep aiding system with the self-adaptive adjustment function, personalized magnetic pulse treatment schemes and feedback can be provided by monitoring and adjusting the neural activity mode of the brain according to the real-time brain electrical activity condition of a user, the biological rhythm and the sleep mode of a patient can be adjusted, and therefore the sleep quality is improved, and the sleep aiding effect is improved. And therefore, the treatment requirements of the user can be met more accurately.

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.

To solve the problem in which a dream world is shared with other users in real time by providing means of analyzing the brain waves and sleep pattern of a user and extracting the contents of the dream as digital data in a system for sharing the dream.SOLUTION: A system for sharing a dream includes means of analyzing the brain waves and sleep pattern of a user, means of extracting the contents of a dream as digital data, and means of sharing the data of the dream with other users.SELECTED DRAWING: Figure 1

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.