177 results about "Sleep period" patented technology

The invention discloses a sleep state real-time monitoring method and system, and belongs to the technical field of sleep monitoring, and the method specifically comprises the steps: collecting a heart rate variability signal, an electroencephalogram signal and body movement data of a user in real time through a non-invasive sleep pad integrating a piezoelectric sensor, a flexible dry electrode and a pressure sensor; based on the physiological data, whether the user reaches an autonomous sleep state or not is judged through a first algorithm model; if not, starting an active intervention program for playing the adjustable music, and dynamically adjusting the music volume, the playing speed or the track in combination with the physiological data feedback until the user enters an autonomous sleep state; after the user falls asleep, physiological data are continuously collected, and a sober period, a light sleep period, a deep sleep period and a rapid eye movement period are divided through a second algorithm model; if the staging result is a waking period, the autonomous sleep state judgment is executed again; according to the invention, non-intrusive monitoring and personalized intervention are combined, and the monitoring comfort and accuracy are improved.

The invention discloses a sleep real-time staging modeling method, a sleep real-time encoding and decoding method and a sleep real-time staging modeling system. EEG, EOG and EMG signals of a subject are collected, statistics, frequency domain and frequency domain characteristics and other characteristics are extracted after preprocessing, sleep stages marked by experts serve as real labels, a model is trained in a supervised learning mode, and real-time classification of the sleep stages is achieved. Furthermore, high-precision encoding and decoding of sleep content are realized by applying stimulation prompt during sleep, collecting and preprocessing whole-brain EEG signals, distinguishing NREM and REM stages, training encoding and decoding models respectively, and aligning nerve characterization during waking and sleep by utilizing comparative learning.

The invention discloses a method for detecting sleep apnea and related events based on a brain-computer interface. The method comprises the following steps: collecting physiological signals during sleep; performing signal preprocessing operation on the physiological signal to obtain a preprocessed physiological signal; performing automatic sleep staging on electroencephalogram signals in the preprocessed physiological signals by adopting a deep learning model to obtain a sleep staging result; extracting features corresponding to the sleep staging results to obtain sleep feature data; positioning an apnea related event through the sleep feature data to obtain an event positioning result; calculating the event positioning result and the preprocessed physiological signal by adopting a statistical method to obtain event statistical data; calculating an apnea hypopnea index according to the sleep staging result, the event statistical data and the total sleep duration; and generating a sleep monitoring report according to the sleep staging result, the event statistical data and the apnea hypopnea index.

The invention discloses a child mouth breathing monitoring method, device and equipment and a medium, and the method comprises the steps that a non-contact sensor group is used for synchronously collecting multi-mode physiological data of a target child in the sleep period, and the multi-mode physiological data at least comprises a face thermal imaging video stream, a thoracic and abdominal micro-motion signal and an environment audio signal; the multi-modal physiological data is processed, multi-modal features related to respiration are extracted respectively, and the multi-modal features comprise thermodynamic change features of mouth and nose areas extracted based on a face thermal imaging video stream, respiratory effort waveforms extracted based on thoracic and abdominal micro-motion signals, and the respiratory effort waveforms extracted based on the thoracic and abdominal micro-motion signals; extracting a sound source spatial position and a spectrum feature of breathing sound based on the environment audio signal; inputting the multi-modal features into a pre-trained mouth breathing recognition model, and outputting a judgment result of the functional mouth breathing event of the target child within a specific time period; and generating a mouth breathing monitoring report of the target child based on the judgment result.

The invention discloses a Doppler frequency offset estimation method and electronic equipment, and relates to the technical field of communication, and the method comprises the step that the electronic equipment communicates with a low-orbit satellite in a discontinuous reception (DRX) mode. Wherein in a discontinuous reception (DRX) mode, the electronic equipment enters a wake-up period when the wake-up moment arrives, the electronic equipment communicates with a low-orbit satellite in the wake-up period, the electronic equipment enters a sleep period when the sleep moment arrives, and the electronic equipment stops communicating with the low-orbit satellite in the sleep period. When the wake-up moment arrives, the electronic device obtains at least one historical Doppler frequency offset value; and the electronic equipment determines a Doppler frequency offset value corresponding to the wake-up moment based on the historical Doppler frequency offset value. In the scheme, the Doppler frequency offset value at the wake-up moment is estimated through the historical Doppler frequency offset value, and the electronic equipment can calculate the Doppler frequency offset value at the current wake-up moment, so that frequency offset compensation can be carried out in time at the current wake-up moment, and the performance of frequency offset compensation is optimized.

the first information indicates a cell DTX state of a serving cell of the terminal device, and the C-DRX-related timer is configured to determine whether the terminal device enters a C-DRX active period (S901); and when the first information indicates that the DTX state of the serving cell is an inactive period state, performing a first operation, where the first operation indicates the terminal device to enter a C-DRX sleep period or is used to change the running state of the C-DRX-related timer (S902). The cell DTX state is taken into consideration for whether the terminal device enters the C-DRX sleep period, thereby avoiding an invalid monitoring of a PDCCH performed by the terminal device when the cell DTX state is the inactive period state.

The invention relates to an insomnia diagnosis and typing method based on multi-modal signal fusion, which comprises the following steps of: acquiring multi-source physiological signals of a testee during a rest period at night to construct a multi-modal information source during a sleep period; performing rhythm recognition and consistency judgment on the collected signals, calculating the rhythm change trend of each modal signal in a preset time window, and determining whether a signal fragment with physiological rhythm synchronization imbalance exists or not according to the rhythm collaboration among modals; performing inter-modal logic consistency analysis on the rhythm anomaly signal segments, identifying contradictory states of different modals in the same time window, and marking the contradictory states as modal conflict nodes; extracting an activation sequence of each modal signal according to a sequential relationship of the conflict nodes so as to determine a dominant modal of the insomnia behavior; analyzing a state transition behavior of the multi-mode signal through a sliding time window, identifying a nonlinear fracture section of a sleep state, and determining an insomnia occurrence time section and jump characteristics in combination with a mode activation sequence so as to realize insomnia diagnosis and typing judgment.

The invention provides a sound wave and low-frequency pulse collaborative sleep-aiding oxygen cabin control method, which comprises the following steps of: setting a basic period stage of an oxygen cabin on the basis of a superdaily rhythm of a human body sleep period, and determining a core physiological target of the basic period stage; respectively carrying out time sequence matching of low-frequency pulse, sound wave stimulation and oxygen supply pressurization; carrying out nerve conduction path matching and organ response space-time synchronization based on the corresponding organ nerve induction partitions; establishing a fuzzy control model, performing multi-parameter real-time detection, and dynamically adjusting modal parameters according to monitoring data of human body physiological indexes; setting a pulse intensity upper limit, a sound wave decibel upper limit, an oxygen concentration upper limit and a single pressurization duration, and executing oxygen cabin operation control according to the modal parameters. The method has the advantages in physiological adaptation, collaborative accuracy, individual adaptation and safety guarantee, fits the electroencephalogram and physiological law of natural sleep, and improves the sleep continuity.

The invention relates to a sleep apnea detection method and device, embedded equipment and a storage medium. The method comprises the steps of obtaining PPG signal data of a user during sleep, preprocessing the PPG signal data to obtain a plurality of PPG signal segments, extracting a one-dimensional time sequence feature vector used for reflecting the change condition of heart rate and blood flow for each PPG signal segment, converting the PPG signal segments into two-dimensional frequency spectrum images, and outputting the two-dimensional frequency spectrum images. Extracting a two-dimensional image feature vector used for reflecting spectrum structure characteristics based on the two-dimensional spectrum image, fusing the one-dimensional time sequence feature vector and the two-dimensional image feature vector to obtain a fused feature vector, and performing standardization and dimension reduction processing on the fused feature vector to obtain a target feature vector; and inputting the target feature vector into a trained classification model for classification to obtain a classification result of whether the PPG signal segment has the apnea event. By adopting the method, the accuracy of apnea detection during sleep can be improved.

The invention discloses a sleep staging method based on a piezoelectric sensing signal and related equipment, and the method comprises the steps: obtaining the piezoelectric sensing signal of a target object in a sleep period, and segmenting the piezoelectric sensing signal in the sleep period into a plurality of piezoelectric sensing signals according to a preset time length; performing signal amplitude alignment processing on the piezoelectric sensing signal of each segment to obtain an amplitude alignment signal of each segment; performing continuous wavelet transform on the amplitude alignment signal of each segment to generate a time-frequency graph corresponding to each segment; fusing the time-frequency graph of each segment with the time-frequency graph of the adjacent segment to obtain a context time-frequency graph; inputting the context time-frequency graph into a preset sleep staging model to obtain an initial sleep staging result of each segment; and correcting the initial sleep staging result of each segment to obtain a final sleep staging result of each segment. The method can effectively improve the accuracy of sleep staging, and can be widely applied to the technical field of sleep monitoring.

The invention provides a sleep nursing device capable of automatically adjusting temperature, which relates to the field of sleep nursing and comprises a shell, a surface shell and a flexible electric heating sheet, the inner side face of the machine shell is connected with a control mainboard through bolts, a through hole is formed in the position, close to the left end, of the upper side face of the machine shell, a wireless transceiver is installed in the through hole of the machine shell, a meter cover is bonded to the lower side face of the meter shell, an infrared temperature measuring sensor is installed in the through hole of the meter cover, and a miniature wireless transmitter is installed in the through hole of the meter shell. The left end and the right end of the flexible electric heating piece are each provided with an attaching pad in an adhesive mode. Through the arrangement of an infrared temperature measurement sensor, a micro wireless transmitter, a wireless transceiver and a flexible electric heating sheet, the temperature of the heating mattress can be automatically regulated and controlled according to the body temperature change rule in different sleep periods at night; the problem that the sleep quality of a patient is damaged due to uncomfortable sleep temperature of a human body caused by the fact that a traditional warm mattress in sleep nursing cannot automatically control and adjust the temperature according to the temperature change of the human body sleeping at night is solved.

A back sleeper pillow for supporting a head of a sleeper in a back sleeping position includes a pillow body having a frontside and a backside opposite the frontside. Each of the frontside and the backside is divided by a center plane. A primary head support surface is included on the frontside of the pillow body. At least one bumper adjacent to an edge of the primary head support surface and rising forward from the primary head support surface is included and configured to support the head of the sleeper in a neutral position during sleep. At least one shoulder horn extending down from the at least one bumper is included and configured to extend over a shoulder of the sleeper when the head of the sleeper is positioned on the primary head support surface.

Described herein is a method for providing personalised stimulation to a user during a sleep period comprising the steps of: receiving one or more signals indicative of the user's sleep activity during a sleep period, extracting one or more features of the one or more signals, determining a stimulation response including determining whether to vary one or more stimulation response parameters based on the extracted one or more features of the one or more signals, and delivering a stimulation response to the user based on the determined stimulation response including varying the stimulation response by varying one or more stimulation response parameters.

The present application relates to the field of artificial intelligence and intelligent sleep technology, and discloses a health state evaluation model generation method and system based on multi-point body surface temperature and vital sign data during sleep. The method continuously collects body surface temperature data of multiple body contact areas during the user's sleep process, and synchronously collects data such as heart rate, respiratory rate, body movement, environmental temperature and bed surface temperature, to construct a multi-dimensional sleep physiological data set. On this basis, the multi-dimensional sleep physiological data is preprocessed, feature extraction and model analysis are performed, and the health state evaluation result and personalized health insight information of the user during sleep are generated. The staged evaluation can also be carried out in combination with the change of sleep stage, and the model is continuously optimized based on the long-term temperature adjustment behavior of the user. By using the present application, the accuracy, continuity and individual adaptability of sleep health state evaluation can be improved, and more accurate sleep health analysis basis is provided for the user.

The present invention provides a package of a micronutrient supplement for promoting the digestive function of the intestinal tract of a body, the micronutrient supplement consisting of two types of unit dosage forms in one package for sale to a purchaser wherein the first type of unit dosage form contains VB6 and a compound thereof, and the second type of unit dosage form contains VB6 and a compound thereof. The first type of unit dosage form contains Zn and compounds thereof, the second type of unit dosage form contains Zn and compounds thereof or VD and compounds thereof, and the first type of unit dosage form does not contain Zn and VD, and the second type of unit dosage form does not contain VB6, the micronutrient supplement being provided in a manner of administration twice a day, the first type of unit dosage form is taken in an awakening period, and the second type of unit dosage form is taken in a sleep period. The packaging product can be matched with the biological clock rhythm of an organism, the absorption and utilization rate of micronutrients is increased, and then the intestinal digestion function is improved.

The invention belongs to the cross technical field of biomedical engineering and signal processing, and discloses a fixed-length sleep staging sequence global correction method based on dynamic programming, which comprises the following steps of: defining an original sleep staging sequence which is divided by taking 30 seconds as a fixed time window and comprises a plurality of continuous fixed time windows, the target generates a corrected sequence, the number of fixed time windows of the corrected sequence is kept consistent with that of the original sequence, only the sleep state value corresponding to each fixed time window is corrected, and the fixed time windows are not added or deleted; a sleep state coding rule is set, and the waking state, the first light sleep stage, the second light sleep stage, the deep sleep stage and the rapid eye movement sleep stage correspond to unique digital codes respectively. Through a global cost accumulation mechanism, subsequent illegal transfer caused by local correction is avoided in advance, iteration is not needed, and the correction efficiency is remarkably improved.

The invention discloses a non-inductive monitoring and biological feedback communication method and system for child enuresis, relates to the field of enuresis monitoring and feedback control, and provides the following scheme that the method comprises the steps that impedance data, pressure image data, a sleep stage and an initial bladder personalized threshold value of the lower abdomen of a user are obtained in real time; and processing to generate a multi-modal feature vector, and inputting the multi-modal feature vector into a pre-training model to estimate the bladder filling degree. The dynamic threshold adjustment is based on a new threshold obtained by multiplying the maximum filling degree when no alarm is given in history by an attenuation coefficient, and the new threshold passes confidence verification and is discarded when being lower than a preset value, so that the threshold is ensured to fit a user. And when the bladder filling degree exceeds a threshold value, executing a strategy according to a sleep stage: starting biological feedback in a deep sleep stage, promoting to a light sleep stage or an REM stage to promote waking, and directly waking up by wrist vibration in a non-deep sleep stage. According to the method, the accuracy is improved by dynamically adjusting the threshold value and verifying the validity of data, and the influence on the sleep quality of children is reduced in combination with the sleep stage of the user.

The invention discloses a sleep monitoring and intelligent early warning system and method based on a multi-modal time sequence signal, and the system comprises a multi-modal sensor module which is used for collecting an original heterogeneous time sequence signal of a subject in a sleep period; the time sequence data preprocessing module is used for performing timestamp alignment, band-pass filtering noise reduction, baseline drift correction and sliding window segmentation on the original heterogeneous time sequence signals and extracting multi-modal feature vectors; the sleep feature recognition module is used for receiving the multi-modal feature vector, performing deep feature learning and outputting sleep staging probability distribution and a sleep apnea event detection mark; the large language model module is used for performing joint coding on an output result, a historical sleep file of the subject and a clinical diagnosis text to generate a structured sleep quality assessment report and health risk association analysis; and the multi-level intelligent early warning and decision support module is used for triggering early warning signals of different levels and generating personalized sleep intervention suggestions.

The invention discloses an apnea syndrome evaluation method based on a smart watch. According to the method, a photoelectric volume pulse wave signal and a three-axis acceleration signal in the sleep period of a user are collected through a built-in sensor of the smart watch, and filtering and window segmentation preprocessing is carried out on the signals. Extracting multi-dimensional features such as heart rate, heart rate variability, body movement index and respiratory rate from each analysis window, and constructing a feature vector sequence; and analyzing the feature vector by using a pre-trained machine learning classification model, outputting the apnea event probability and performing binary classification. And finally, quantitatively analyzing the event sequence, calculating an apnea hypopnea index and dividing risk levels. According to the method, the signal processing technology and the machine learning algorithm are combined, intelligent identification and risk assessment of the sleep apnea event are achieved, and an effective solution is provided for portable monitoring.

The application belongs to the field of monitoring, and particularly relates to an environment evaluation method based on monitoring data, a terminal device and a storage medium, wherein the method can determine the distribution of light of each wavelength in the zoo through wavelength detection data of each light source and the position of each light source in the zoo, and can determine the activity area heat map of animals through monitoring video, and through comparison of the distribution of light of each wavelength and the intersection of the activity area, in combination with the sleep period of animals and the influence wavelength range, the influence on the sleep rhythm of animals can be accurately estimated, that is, the light pollution of the living environment of animals can be accurately evaluated through quantitative data.

According to the model training method and the human body sleeping posture prediction method and device provided by the embodiment of the invention, the human body sleeping data of the target human body are collected through the radar, and the sleeping signal features of the target human body are extracted from the human body sleeping data of the target human body; and inputting the sleep signal features into a human body sleep posture prediction model to obtain a predicted sleep posture corresponding to the target human body. According to the technical scheme provided by the embodiment of the invention, the body movement of the target human body in the sleep period can be accurately tracked under multiple different positions and environment conditions, so that the sleep postures of the target human body can be accurately classified, and the method has a potential wide application prospect for improving sleep quality monitoring and health management.

Disclosed is a method and apparatus for analyzing sleep and health status using radar. In an aspect of the present disclosure, an apparatus for analyzing sleep and health status using radar according to at least one of the various embodiments of the present disclosure may include a memory; a radar sensor for sensing movement data during sleeping of a user; and a processor configured to analyze the sleep and health status by obtaining data sensed by the radar sensor, wherein the processor may be configured to convert the data sensed by the radar sensor into a frequency domain and obtain respiratory activity waveform and heartbeat waveform data.

The present invention discloses a head piece, such as a headband or helmet, that fits around the cranium and includes one or more contractile elements which contract in synchrony with inspiration during sleep. The head piece is connected to a breath sensor which signals the timing of inspiration and software which incorporates the generated timing signals from the breath sensor to control the timing and release of the contraction of the head piece to coordinate with the user's breath. The breath sensor may comprise a variety of mechanisms such as a flow valve in the tubing of a CPAP or other type of automated breathing machine, an anemometer such as a hot wire anemometer to directly detect airflow in front of the nose or mouth, acoustic sensors to record breathing sounds, or a radar detector that monitors chest or abdomen movements from above the bed. In the illustrated embodiments, the breath sensor is a chest band that signals inspiration by recording an increase in tension produced by expansion of the chest. Coupling expansion of the chest with compression of the cranium is advantageous, because these movements occur simultaneously and because the expansion of the chest occurs with much greater force than the compression of the cranium, therefore the natural expansion of the chest can power the compressive forces which are desirably applied to the cranium. The chest band and head piece can be coupled to provide such a self powered head pumping mechanism by an electrical connection or a tube that permits flow of a liquid or air between the two areas.

The invention relates to an electronic device (1) configured to perform wireless communications via a low-power communication interface (RI 145) when the electronic device (1) is operating in a deep sleep mode, and to an improved method for configuring said electronic device (1) during deep sleep. Figure to be published with the abstract: Fig. 1

A computer-implemented method and system includes accessing neurophysiological and neurovascular data recorded during sleep. A device worn on the subject's head during sleep can collect the neurovascular data by measuring transcranial impedance. The device can be in the form of a single band, multiple bands, or a head cap worn on the subject's head. Electrodes positioned along the inner surface of the wearable device contact the subject's head and measure the transcranial impedance. Transcranial impedance measurements are collected from multiple locations on the subject's head and across multiple frequencies to obtain a more complete assessment of glymphatic flow.

The invention provides a sleep quality evaluation method and device based on intelligent ring multi-mode sensing, the method is applied to an intelligent ring, and the method comprises the following steps: collecting multi-mode sleep data of a user in a sleep cycle; determining a multi-dimensional sleep score according to the multi-modal sleep data based on a preset sleep model; and determining a comprehensive sleep score according to the multi-dimensional sleep score. According to the method, the anti-interference performance and medical credibility of the sleep staging and scoring result are fundamentally improved, and the evaluation misaccuracy caused by misjudgment of a single signal is avoided, so that the evaluation depth and reliability close to professional medical analysis are realized on consumer equipment, and unprecedented accurate health insight is provided for users.

A method, apparatus and non-transitory computer-readable storage medium to notify a need for sleep care, the method comprising: acquiring video frame sequences of a person during sleep and identifying a target person; determining real-time moisture content level changes of the target person to determine whether the target person is in a sweating or urine-wet state; and notifying specialized caregivers to provide sleep care when it is determined that the target person is in a sweating or urine-wet state and has a higher moisture content level.

The present invention relates to systems and methods for analyzing data from motion activity monitoring technology. It is particularly, but not exclusively, concerned with a method for determining motion activity patterns during sleep.

System for eye tracking during sleep and in altered states of consciousness comprising an eye tracking device including a wearable eye mask comprising an eye mask casing with a form fit border configured for placing over a person's eyes, the eye mask casing and form fit border being opaque configured to prevent light from entering inside of the eye mask casing when worn in a form fit manner by the wearer, an electronic control and communications system and power source for transmission and reception of data with a computing system, a humidifier mounted on an inner side of the eye mask casing, eye tracking sensors mounted on an inner side of a front panel of the eye mask casing, and an infrared illumination source mounted on an inner side of the eye mask casing and configured to illuminate a position of the eyes of a person wearing the eye tracking device