251 results about "Sleep period" patented technology

The invention relates to a sleep apnea monitoring method and device, electronic monitoring equipment and a storage medium. The method comprises the following steps: acquiring PPG signal data of a user in a sleep period, performing segmentation processing on the PPG signal data, performing quality scoring on each PPG signal fragment data obtained by the segmentation processing, screening out target PPG signal fragment data of which the quality score is lower than a quality score threshold value, and sending the target PPG signal fragment data to the user; the quality score threshold value dynamically changes based on statistical characteristics of quality scores in different time periods, blood oxygen detection is conducted on the target PPG signal segment data to obtain blood oxygen index data, effective respiratory wave detection is conducted based on the target PPG signal segment data to obtain respiratory index data, and the effective respiratory wave detection is conducted based on the blood oxygen index data and the respiratory index data to obtain the target PPG signal segment data. Whether a sleep apnea event or a hypopnea event is present during sleep of the user is identified. By adopting the method, more accurate sleep apnea monitoring can be realized.

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 relates to an intelligent hypnosis method and system based on a brain-computer interface and a storage medium, and belongs to the technical field of human-computer interaction and artificial intelligence. The method comprises the following steps: acquiring an EEG signal of a user in real time through EEG acquisition equipment, and extracting a brain wave segment power value as state input through preprocessing; a deep reinforcement learning model (such as DRQN) selects music type actions (such as classical music and white noise) based on an epsilon-greedy strategy; calculating a reward value (maximizing delta wave increment and inhibiting beta wave) according to the electroencephalogram state change after playing, and optimizing model parameters by adopting Q-Learning; and dynamically adjusting the strategy through iterative interaction until the user reaches a preset sleep target. The system comprises an electroencephalogram acquisition module, a preprocessing module, a reinforcement learning module and a music control module, and realizes closed-loop regulation and control. The method has the advantages of high personalization, high hypnosis efficiency (induction to sleep in 1-7 minutes), flexible adaptation to different users and self-evolution optimization capability, and effectively improves the sleep induction effect.

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 relates to an equipment low-power-consumption control method and system based on wireless sensing. The method comprises the following steps: carrying out energy consumption modeling on a radio frequency transmitting circuit of a wireless sensing node to obtain a power control factor set for describing an energy consumption behavior of a power amplifier in the radio frequency transmitting circuit; performing bias intelligent control on the power amplifier according to the power control factor set to obtain a self-adaptive bias voltage configuration set under various input signal power conditions; and performing polling protocol synchronization processing on a wireless communication module of the wireless sensing node according to the self-adaptive bias voltage configuration set to obtain a low-power-consumption communication scheduling instruction set based on a time quasi-synchronization mechanism and a dynamic dormancy strategy, the method is used for controlling the transmitting time slot, the dormancy time period and the back-off waiting time length of the wireless sensing node in the multi-node networking communication. By adopting the method, a structured low-power-consumption control strategy of the wireless sensing node under the condition of dynamic input signal power can be realized.

The invention relates to a train dormancy awakening method and system based on TACS fusion control, and the method comprises the following steps: before a train is dormant, an AOM stores the position information of the train; in the train dormancy process, the speed measurement positioning board card keeps power supply, the speed measurement positioning module continuously collects speed pulse signals, train position information is calculated, and the train position information obtained through calculation is sent to the AOM; before the train is awakened, the AOM compares the position information obtained from the speed measurement positioning module in real time with the position information stored before dormancy, and whether the train is allowed to be awakened or not is judged based on the comparison result. According to the method, power supply is kept for the speed measurement positioning module during the train sleep period, real-time monitoring of the train position during the sleep period is achieved, meanwhile, through position comparison before wakeup, the wakeup efficiency of the train is improved, and wrong wakeup operation caused by abnormal movement of the train is prevented.

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.

A server delay controller includes: a packet harvesting unit that refers to a packet held in a ring buffer when a packet arrives and executes harvesting to delete an entry of a corresponding queue from the ring buffer, a sleep management unit that puts the thread to sleep in a case in which a packet does not arrive for a predetermined period, and cancels the sleep of the thread through a hardware interrupt at the time of packet arrival, and an idle state recovery control unit that periodically wakes up the thread during sleep or wakes up the thread immediately before the packet arrival in accordance with a packet arrival timing.

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 disclosure herein relates to devices, systems and methods for detecting disturbances that may occur during the sleep of a subject. In particular, in some embodiments, the devices, systems, and methods described herein comprise a sensing unit and a processing unit for processing data relating to disturbances that may occur during the sleep of a subject, in which the sensing unit may include a gyroscope adapted to measure movements of the mandible of a subject.

The invention provides a method and equipment for constructing lung function characteristics during sleep. The method is applied to lung function data processing. The method comprises the following steps: collecting a breathing velocity waveform of a target object; determining an inspiration stage and an expiration stage in each respiratory cycle based on the respiratory velocity waveform; the duration of each stage is determined based on the inspiration stage and the expiration stage, and the duration of the inspiration sub-stage and the duration of the expiration sub-stage are obtained; basic features, a stability measurement feature group and a comprehensive feature group are calculated based on the inspiration sub-stage duration and the expiration sub-stage duration; according to the method, the breathing speed waveform is acquired without burden, and the comprehensive lung function evaluation feature group suitable for the radar breathing waveform is constructed.

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 relates to the technical field of infant sleep monitoring, in particular to an infant sleep state monitoring method and system based on sound analysis, and the method comprises the following steps: based on an intelligent infant bed, collecting sound signals sent by an infant in real time through a microphone sensor on the inner side of the bed, recognizing sound in a deep sleep period, sound in a light sleep period and sound in a rapid eye movement period, and transmitting the sound signals to the intelligent infant bed; and acquiring a sleep cycle sound category. According to the invention, the sound signals are collected in real time and are accurately classified according to the frequency range, so that the states of deep sleep, light sleep and rapid eye movement periods of the baby can be more accurately identified, and through careful comparison with reference modes in the audio database of the baby crib, the matching precision of data is improved, and the accuracy of the baby crib is improved. And the utilization efficiency of the sound data is optimized, so that the response capability of the whole monitoring system is improved, the monitoring sensitivity is dynamically adjusted, the sampling frequency is adjusted according to real-time data, the potential of misinformation is reduced, and the practicability of the monitoring system is improved.

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.

The present invention discloses a method for detecting leaks in combustible refrigerant indoor units and a multi-split air conditioning system employing this method. The method comprises: presetting an initial sleep period for the indoor unit's refrigerant sensor based on design and commissioning parameters; modifying the initial sleep period based on the indoor unit's cumulative operating time and fault frequency; and dynamically adjusting the indoor unit's refrigerant sensor's sleep period based on the indoor unit's operating status, enabling the indoor unit's refrigerant sensor to perform intermittent leak detection. For large multi-split air conditioning systems, this method reduces the operating time of the refrigerant sensor, contributing to energy savings and improved economic efficiency.

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.

A snoring and sleep apnea preventer to prevent snoring and sleep apnea from occurring during a user's sleep comprises a sensor part mounted on a body part of the user and collecting sensing information to determine snoring and sleep apnea symptoms occurring in the user; an operating part mounted in the user's mouth to move the user's mandible in response to the sensing information; and a control part for controlling the operating part based on the sensing information sensed via the sensor part, and controlling the operating part in stages to control snoring and sleep apnea symptoms occurring in the user.

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 disclosure relates to the technical field of brain wave signal processing, and more specifically, to a sleep staging method, apparatus, device, and computer-readable storage medium. The sleep staging method includes: determining the power spectral density of the brain wave signal of each sleep frame during sleep; performing dimensionality reduction processing on the power spectral density to obtain a reduced dimensionality data set; determining multiple characteristic signals of the brain wave signal of the sleep frame based on the power spectral density; for each sleep frame, performing kernel density estimation on the reduced dimensionality data set with weights determined according to each characteristic signal to obtain a probability density corresponding to the characteristic signal; and determining that the sleep frame belongs to the sleep stage corresponding to the characteristic signal when the probability density meets the preset condition corresponding to the characteristic signal, wherein different characteristic signals correspond to different sleep stages.

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 purpose of the present invention is to discover an eye drop capable of effectively lowering intraocular pressure even at night, especially during night sleep, in patients with glaucoma or ocular hypertension.　The present invention is an eye drop for lowering intraocular pressure during night sleep in patients suffering from glaucoma or ocular hypertension, the eye drop containing sepetaprost at a concentration of 0.002% (w / v) as an active ingredient.

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.