650 results about "Sleep quality" patented technology

The invention relates to the technical field of physiological signal processing and sleep monitoring, in particular to a sleep staging method and a sleep staging system for collecting multiple physiological signals, and the sleep staging method and the sleep staging system for collecting the multiple physiological signals synchronously collect auditory meatus photoelectric volume pulse waves, temperature and head micro-motion signals through an in-ear sensor array. According to the method, the signal quality index is calculated, time domain, frequency domain and nonlinear features are extracted, a dynamic weighted fusion mechanism is adopted, feature weights are adjusted according to the signal quality index, a hierarchical depth time sequence learning model is input for sleep staging, and the sleep staging accuracy is improved to 89% or above and is improved by 15-20% compared with a single brain wave method. A sleep state evaluation report and a personalized feedback intervention strategy generated by the system are beneficial for improving sleep quality, a dynamic weighted fusion mechanism enhances system robustness, adapts to different signal qualities and ensures stable performance, and the invention provides an efficient and accurate new method for the field of sleep monitoring.

The invention relates to the technical field of sleep stage classification, and particularly provides a sleep quality monitoring method fusing multi-scale features. The method comprises the following steps: preprocessing input signals, and inputting the input signals into a multi-mode sleep signal analysis network after ensuring that the signal amplitudes are consistent; capturing features of a plurality of time scales through a multi-granularity feature learning module, and carrying out feature fusion; integrating spatial information by using a spatial-temporal feature enhancement module, and mapping the three-dimensional features into a two-dimensional time sequence feature sequence; on the basis of a time context module of Mama, long-distance time dependence is modeled with linear complexity, features are averagely aggregated along the time dimension through a classification module, a classification result is output through a full connection layer and an activation function Softmax, and the method improves the accuracy of sleep stage classification while ensuring the high efficiency of sleep stage classification.

There is provided a computer-implemented method for determining sleep misperception of a subject during a sleep session. The method comprises receiving sleep condition information. The sleep condition information comprises at least one of SDB information and insomnia information. The SDB information is representative of a sleep disordered breathing (SDB) condition of the subject based on a number of SDB events of the subject per unit of time. The computer-implemented method comprises receiving sleep quality information representative of a quality of sleep of the sleep session experienced by the subject. The computer-implemented method comprises determining a degree of sleep misperception based on the sleep condition information and the sleep quality information. The sleep misperception is representative of a difference between a subjective total sleep time of the sleep session experienced by the subject and an objective total sleep time of the subject in the sleep session.

The invention discloses a compound composition for improving sleep disorders, which is characterized by comprising the following components: an inhibitory neurotransmitter component, melatonin and a nano-lipid carrier, the nano-lipid carrier comprises phospholipid and cholesterol, the weight ratio of phospholipid to cholesterol is (1-6): 1, the weight ratio of phospholipid to cholesterol is (1-6): 1, and the weight ratio of melatonin to cholesterol is (1-6): 1. The inhibitory neurotransmitter component is wrapped in the nano-lipid carrier to form lipid nanoparticles, and the weight ratio of the inhibitory neurotransmitter component to the nano-lipid carrier is 1: (1-15). The compound composition can be prepared into a compound oral mucosa preparation, can be rapidly disintegrated when encountering saliva in the oral cavity, is good in patient compliance and small in side effect, all the components play a synergistic effect from different mechanisms through multiple target points, and the compound oral mucosa preparation can improve the sleep quality, prolong the sleep time and shorten the sleep latency; and patients with sleep disorders are helped to improve insomnia from the pathologic root.

The invention belongs to the technical field of sleep quality analysis, and particularly relates to a sleep quality analysis system and method based on a medical bed sensor, so as to solve the technical problem that an existing method excessively depends on duration statistics and neglects sleep continuity and periodic rhythmicity. The analysis method comprises the following steps: S1, acquiring sign signal data acquired by a sensor on a medical bed in a sleep cycle, and dividing the sign signal data into a plurality of continuous time slices; s2, extracting physiological indexes of respiratory rate, heart rate and body movement amplitude in each time slice, and calculating variation depth of the corresponding time slice; s3, generating a variation depth baseline; calculating an unsteady state disturbance factor according to the occurrence frequency and the duration of the micro-awakening disturbance fragment; and S4, generating a sleep quality comprehensive score. According to the analysis method, the comprehensiveness and objectivity of the evaluation result are improved, and the sleep health condition is reflected more truly.

The invention discloses a sleep quality improving system based on big data analysis, and relates to the technical field of big data. According to the system, a multi-dimensional sleep state monitoring matrix is constructed, effective intervals of monitoring points are optimized in combination with dynamic adjustment factors and a deep learning algorithm, and redundant data interference is eliminated; generating a sleep intervention regulation factor based on the environmental influence function and the physiological rhythm constraint factor, and training the sleep intervention function through a genetic algorithm to dynamically adjust the intervention intensity; and generating an intervention instruction by utilizing the reinforcement learning model and combining the real-time physiological data of the user, the environmental parameters and the sleep stage prediction result, and controlling the starting sequence and parameter adjustment of the monitoring points until preset ideal sleep state parameters are met. According to the method, the problems of insufficient monitoring precision, poor environment adaptability, intervention lag and the like in a traditional method are solved, the accuracy and the real-time performance of sleep intervention are improved, and the method is suitable for the fields of smart home, medical health and the like.

The invention provides a sleep assisting system based on photoacoustic magnetic vibration wave resonance, and relates to the technical field of sleep assisting. The system comprises an acquisition unit, a processing unit, a stimulation unit and an evaluation feedback unit. Determining a sleep stage of the user, analyzing phases of multi-scale electroencephalogram rhythm components such as slow waves and spindle waves in a cross-scale manner, and extrapolating and predicting a phase value of a target electroencephalogram rhythm at a future moment in combination with a recent phase trajectory; taking the predicted phase as a target state, mapping a rising / falling slope of a slow wave form into an intensity change parameter of photoacoustic and magnetic vibration stimulation by constructing a mapping channel, and selecting an optimal stimulation combination for output through a decision model based on the intensity change parameter; calculating a phase locking effect index, and adjusting a phase prediction model parameter by using an optimization algorithm according to the index so as to optimize subsequent stimulation; and linkage regulation and control of an external environment are supported, and centralized monitoring of sleep states of multiple users can be realized. According to the invention, self-adaptive guidance of sleep brain rhythms is realized, and the sleep quality is effectively improved.

The invention belongs to the technical field of bedding, and discloses a mattress supporting performance self-adaptive adjusting method based on pressure comfort and a mattress, the method is applied to a mattress provided with a pressure detection assembly and an air pressure adjusting assembly, and the method comprises the following steps: obtaining pressure index data and sleep quality data of each partition of a body; calculating a pressure comfort comprehensive value of each partition of the body based on each pressure index data of each partition of the body; based on the intermediary factors influencing the sleep quality, constructing a correlation model of the pressure comfort comprehensive value of each partition of the body and the sleep quality; real-time data of pressure indexes of all the partitions of the body are obtained, the real-time sleep quality is calculated through the correlation model, and based on the real-time sleep quality and a preset sleep quality threshold value, the air pressure of the mattress areas corresponding to all the partitions of the body is independently adjusted at the same time. The overall comfort is defined by calculating the comprehensive value of the pressure comfort of each partition of the body, the overall dynamic balance adjustment of the supporting performance of the mattress is realized by utilizing a correlation model, and the overall supporting performance unbalance caused by local adjustment is avoided.

The invention provides a multi-mode adaptive wave simulation control system and method for a deep sleep physiotherapy cabin. Belongs to the technical field of fluid mechanics and health intervention. The method comprises the steps that multi-modal physiological parameter collection is conducted on a user on a deep sleep physiotherapy cabin, a real-time physiological data set is generated, the current sleep stage of the user is deduced through a time-frequency analysis and machine learning model on the basis of the data set, a sleep stage label is generated, a pre-trained wave mode generator is dynamically called according to the sleep stage label, and the deep sleep physiotherapy cabin is obtained. An initial set of wave parameters matching the current sleep stage is generated. By sensing the physiological state of the user in a non-contact mode, deducing the sleep stage and dynamically generating and adjusting the wave modes such as sleep guiding and deep sleep maintaining, water fluctuation accurately adapts to the physiological requirements of the user in different sleep stages, a traditional static wave mode is abandoned, highly-personalized sleep adjusting experience is provided for the user, and the sleep quality is effectively improved.

The utility model relates to the field of medical instruments, in particular to an auxiliary sleep device with a sound wave hypnosis function, which comprises a base, a support block, a seat, a backrest, a headrest, an electric push rod and the like, the upper side of the middle of the base is connected with the support block, the upper side of the support block is connected with the seat, the left part of the seat is rotatably connected with the backrest, and the upper side of the backrest is connected with the headrest. The left part of the backrest is rotationally connected with an electric push rod. The window shade is put down by pushing the connecting frame to move and then reversely pulling the pull bead chain, and then sound waves are sent out by the ultrasonic sleep aiding device for hypnosis to assist sleep, so that the sound waves can be used for hypnosis of a user to assist sleep, relax the brain and accelerate falling asleep, and meanwhile, the window shade can be used for shading. A user is in a dark environment, light stimulation is avoided, the sleep quality is improved, and use is convenient.

The invention relates to the technical field of sleep quality evaluation, in particular to a sleep monitoring optimization system based on artificial intelligence. The system comprises the steps of collecting sleep monitoring data of a user at different collection moments, extracting dominant frequency components in snore audio data through spectrum envelope analysis, extracting audio primitives based on the dominant frequency components, inputting the audio primitives into a snore classification model, outputting a snore category corresponding to the snore audio data of the user, and outputting the snore category corresponding to the snore audio data of the user. Carrying out Bayesian inversion analysis on the brain wave data to obtain a posterior sample of random field model parameters, executing reliability analysis based on the posterior sample to calculate a posterior failure probability, obtaining a first sleep quality index of the user based on the posterior failure probability, obtaining a second sleep quality index of the user based on vital sign data analysis, and sending the second sleep quality index to the user; and obtaining a user sleep quality evaluation result based on the snore type, the user first sleep quality index and the user second sleep quality index. The accuracy and efficiency of user sleep quality evaluation can be improved.

A breathable and comfortable inflatable mattress includes a top layer, a surrounding band and a bottom layer, which together define a cavity of the inflatable mattress. The top layer includes a breathable layer and a ticking layer, the ticking layer and the surrounding band are connected by welding or bonding. The breathable layer is arranged on the ticking layer, and the breathable layer is connected to the surrounding band via a sealing layer. The inflatable mattress according to the present invention is replaced the traditional flock / PVC or PVC material with comfortable fabric for the top layer, which can greatly improve comfort and breathability, avoid noise generated by friction between the user's body and PVC, and improve user' s sleep quality, thus meeting needs of users widely.

The invention relates to the technical field of deep sleep management, in particular to a deep sleep staging management method and system based on electroencephalogram feedback. Comprising the steps that electroencephalogram feedback of a target user is collected, an actual deep sleep waveform is extracted and judged with an expected spectral domain of an ideal state transfer stage, and an unreached stage is locked; in an unreached stage, constructing a signal mode prediction model, and determining an optimal guide window stage by combining with intervention entry point migration analysis; performing wavelet basis decomposition to obtain an excellent wave band and a clutter band of the optimal guide window period; when the signal-to-noise ratio is high, crosstalk coupling analysis is executed, and white noise is generated by using the rhythm coding library for guide management; when the signal-to-noise ratio is low, light environment and temperature response regulation is planned, and deep sleep is managed in combination with a color coding chain and a signal excitation result. According to the method and the system, guide management of different decisions can be executed in the stage of entering the deep sleep of the target user, and the deep sleep quality, stability and continuity are improved.

The invention discloses an intelligent sleep monitoring and air conditioner linkage control method and system based on a radar and a photosensitive device, a terminal product and a storage medium. The method comprises the steps that a voltage value is obtained and converted into an illumination value; when the illumination value is larger than a preset illumination threshold value, the air conditioner is in a bright state, whether a person exists in a target detection area or not is detected through a millimeter-wave radar module, if yes, whether the human body is in a micro-motion state or a static state or not is monitored and maintained for a first preset time or longer, and if yes, the air conditioner is controlled to start a sleep mode; and when the illuminance value is not larger than the preset illuminance threshold value, the air conditioner is in a dark state, whether a person exists in the target detection area is detected, if yes, whether the human body is in a micro-motion state or a static state is monitored and maintained for a second preset time or longer, and if yes, the air conditioner is controlled to start a sleep mode. By controlling the different operation modes of the air conditioner in a linkage mode, the purposes of intelligently adjusting the air conditioner and saving energy are achieved, and meanwhile the sleep quality of a user is improved.

The invention discloses a sleep quality evaluation method and system and a storage medium, and the method comprises the steps: inputting electrocardiosignal segmentation data into a trained sleep staging and breath detection multi-task model, and outputting a preliminary sleep staging result and an apnea detection result; based on the acceleration segmented data, extracting posture features of each corresponding time period, inputting the posture features into a decision tree posture classifier to obtain sleeping posture categories of each time period, and correcting a preliminary sleep staging result and an apnea detection result based on a preset posture and heart rate combined correction rule; and finally, calculating the corrected sleep staging result and the apnea result based on a preset sleep scoring rule to obtain a sleep quality evaluation result. Therefore, accurate quantitative evaluation of sleep staging and sleep quality is realized, and a reliable basis is provided for accurate intervention and monitoring of subsequent sleep health.

The invention discloses a sleep apnea monitoring system based on non-contact intervention, and belongs to the technical field of medical health monitoring. The method solves the problems that in the prior art, a PSG method is tedious in operation and high in cost, household contact equipment brings discomfort to a user, and natural sleep is affected, physiological signals are collected through a non-contact biological radar sensor, an initial threshold value, an auxiliary threshold value and an environment factor are synthesized to calculate an optimal threshold value, and the optimal threshold value is obtained. The detection accuracy of the apnea and hypopnea events is improved; in combination with the apnea hypopnea index, the event duration factor, the blood oxygen decreasing factor and the event type factor, severity scores are calculated, and the patients are divided into mild patients, moderate patients and severe patients; according to the severity, the grade and the snore type of the real-time event, the optimal intervention measure is selected from the intervention strategy library, personalized intervention is achieved, interference to sleep of the patient is reduced, and the sleep quality and the life quality are improved.

The invention discloses a sleep state self-adaptive layered regulation and control method and platform based on an environment regulation window, and relates to the technical field of self-adaptive control, and the method comprises the steps: carrying out the sleep state analysis according to a physiological data sequence, obtaining a real-time sleep stage, carrying out the scheduling task distribution, and generating a function unit scheduling sequence; performing data acquisition priority management and control on the wearable device to obtain real-time sleep associated data; generating a sleep environment adjustment strategy by taking the real-time sleep stage as an environment adjustment constraint; after updating the sleep environment of the user, activating an environment adjusting window; and operating a hierarchical scheduling architecture by taking an environment adjustment window as a time constraint, and circularly performing adaptive control updating. The technical problem that in the prior art, due to the fact that the sleep environment is difficult to adjust accurately in real time according to the sleep state of the user, the sleep quality of the user is low is solved, and the technical effects that the sleep state of the user is accurately judged, the sleep environment is dynamically and adaptively adjusted, and the sleep quality is improved are achieved.

The invention discloses a plant lactobacillus and application thereof in preparation of gamma-aminobutyric acid and improvement of sleep, and relates to the technical field of biology. According to the present invention, the plant lactobacillus XBMU-SN-23 has been preserved in the China General Microbiological Culture Collection Center (CGMCC) on December 19, 2025, and the preservation number is CGMCC No.37118. The present invention further provides applications of the plant lactobacillus XBMU-SN-23 in gamma-aminobutyric acid preparation and sleep improvement. A metabolite of the strain XBMU-SN-23 has a sleep aiding function, and can regulate and control a neurotransmitter system to improve sleep quality by up-regulating GABA, 5-HT, IL-1 and MT, down-regulating Glu and DA and regulating protein quantity expression of a 5-HT1A receptor, a GABAAR alpha 1 receptor and a GABAAR gamma 2 receptor. Therefore, the plant lactobacillus XBMU-SN-23 has a wide application prospect in the product for preventing or treating insomnia.

The invention discloses a sleep intervention robot based on five-dimensional space-time cooperation (time, space, physiology, environment and behavior) and multi-scene self-adaption. Through a four-dimensional core module (physical / chemical / biological / information) and a five-dimensional cooperation mechanism (Qtotal = summa t.x dt), and in combination with a 77GHz FMCW radar and an ultrasonic solid-state particle technology, full-scene efficient sub-health conditioning is realized. The core innovation is as follows: an efficient herbal absorption system improves the herbal absorption efficiency by 37.8%; accurate biological signal monitoring is achieved, and 95.8% sleep state recognition accuracy is achieved; the differential radar design is adopted, and the speed resolution reaches 0.1 m / s. Through fusion of traditional Chinese medicine herbs and physical modules, an intervention strategy is dynamically adjusted, and the sleep quality is remarkably improved (the PSQI score is reduced by 14.1 scores). The system is suitable for medical, household, aviation and other scenes.

Through the multi-sensor fusion design of the microphone, the millimeter wave radar sensor and the piezoelectric film sensor, compared with an existing single or double-sensor sleep monitoring technology, the monitoring precision, the function dimension, the environmental adaptability and the like are remarkably improved. According to the method, a weighted voting decision fusion mechanism and an improved random forest model are adopted, and after a microphone acoustic monitoring dimension is newly added, the apnea detection sensitivity is improved; acoustic characteristics such as snore, breath sound rhythm, cough and dream can be accurately captured; health risk assessment dimensions are richer, preliminary screening of diseases such as sleep apnea syndrome and periodic limb dyskinesia can be realized, snore indexes and breathing stability are newly increased, and a multi-dimensional sleep quality report is provided for a user; in the whole process, an electrode plate or a wrist strap does not need to be worn, the three sensors all adopt non-intrusive design, no foreign body sensation exists after the piezoelectric film is embedded into the mattress, the problem of wearing discomfort of traditional monitoring is solved, and the user compliance is improved.

Exemplary systems, methods, and devices are disclosed which provide at-home, portable, wireless sleep sensors and wearable electronics with embedded machine learning. Such devices have applications in assessing sleep quality and detecting sleep apnea with multiple patients. Unlike the conventional system at a sleep center using numerous bulky sensors, the soft all-integrated wearable platform offers natural sleep in a familiar setting. The face-mounted patches that detect brain, eye, and muscle signals show comparable performance in sleep monitoring with polysomnography in a clinical study. Furthermore, deep learning is embedded in an exemplary device, offering automated high-precision sleep scoring, which demonstrates the wearable system's portability and point-of-care usability. The at-home wearable patches help to support portable sleep monitoring and home healthcare.

A proposal system (1) comprises an acquisition unit (220) that acquires body information relating to the body of a user and action schedule information relating to an action schedule of the user after bathing, a determination unit (230) that determines bathing information for improving the quality of sleep of the user in accordance with the acquired body information and action schedule information, and an output unit (240) that outputs the determined bathing information to the user.

The invention belongs to the technical field of information, and discloses an intelligent sleep environment adjusting method based on artificial intelligence, and the method comprises the steps: synchronously collecting the heart rate variability, respiratory rate and body temperature data of a user, and carrying out the classification and recognition of a sleep state through a long-short-term memory network and a random forest algorithm, and obtaining a sleep state label; judging a deep sleep state according to the sleep state label and a corresponding body temperature data change trend, and further obtaining indoor environment parameters and calculating a deviation value with an ideal sleep environment; a reinforcement learning algorithm is adopted to construct a personalized environment adjustment strategy model, and when the environment parameter deviation exceeds a personalized threshold value, a multi-dimensional environment optimization control scheme is automatically generated. According to the invention, accurate identification of the sleep state of the user and intelligent adjustment of the environmental parameters are realized, the sleep quality is effectively improved, and a comfortable and healthy personalized sleep environment is created for the user.

The invention belongs to the technical field of nursing pillows, and discloses a pillow with a good shoulder and neck nursing effect, the pillow comprises a neck pillow, the middle part of the inner cavity of the neck pillow is movably sleeved with a high-resilience sponge, and the left side and the right side of the inner cavity of the neck pillow are movably sleeved with filling sponges. The neck pillow, the filling sponge and the pillows are arranged, when an operator uses the neck pillow, the neck pillow surrounds the neck, then the first buttons and the second buttons are clamped, and therefore the whole neck pillow is worn, when the operator lies flat, the back side of the head is located between the two pillows, and the back side of the head is located between the two pillows; the high-resilience sponge and the filling sponge can support the cervical vertebra so that the cervical vertebra can be protected, the whole neck pillow can rotate along with turning over of an operator when the operator lies on the side, the pillow can fill a gap between the head and a bed, compression on the shoulders and the neck is reduced, and the comfort of the operator is improved. And therefore, the problems of noble bags and shoulder inner buckles are relieved, the sleep quality is improved, and a human body has a better posture.

The intelligent office table comprises a table plate, a controller is fixedly installed on the upper surface of the table plate, a displayer is arranged on the upper surface of a base, a storage box is fixedly installed on the lower surface of the table plate, a storage groove is formed in the table plate, and a sliding plate is slidably installed in the storage groove; a storage groove is formed in the table board, a first pushing mechanism is fixedly mounted in the storage groove, a mounting cavity is formed in the surface of the table board, an L-shaped top plate is slidably mounted in the mounting cavity, a second pushing mechanism is fixedly mounted in the mounting cavity, and an inflatable throw pillow is fixedly mounted in the mounting cavity. Through the arrangement of the box body, the cleaning roller, the exhaust fan, the dust filtering net, the ventilation chamber, the hollowed-out plate and the like, when the display is stored, the display screen can be cleaned and dedusted, the definition of the display screen is influenced, the use effect of the display is improved, meanwhile, dust-free air after dedusting blows aromatherapy to a rest area, the air quality is improved, and meanwhile the use effect of the display is improved. The sleep quality is effectively improved.

The invention discloses a composition with a sleep improving function as well as a preparation method and application thereof, and the composition is prepared from the following raw materials in parts by weight: 50-100 parts of acanthopanax root, 30-50 parts of lotus seed, 50-100 parts of spina date seed, 30 parts of lily, 30 parts of longan, 30-50 parts of poria cocos, 30 parts of radix ophiopogonis, 10-30 parts of rehmannia, 10-30 parts of gastrodia elata, 2 parts of glutamic acid, 0.1 part of vitamin B, 0.1 part of vitamin B6 and 0.1 part of gamma-aminobutyric acid. The traditional single target spot limitation is broken through, a synergistic effect system of tonifying the spleen and soothing the nerves-neurotransmitter regulation and control-intestinal brain axis regulation is formed, a buffer solution of pH simulation biological fluid is adopted as a non-organic extraction medium in the process, the ultrasonic cavitation effect and the plasma activation effect are combined, the temperature is controlled in the whole process, and the preparation method is simple and easy to implement. The problems of vortex, uneven extraction, dead volume, solvent residue, active ingredient damage and the like in traditional extraction are fundamentally solved, the composition capable of effectively improving the sleep quality is obtained, and animal model and crowd experiments prove that the composition can effectively improve the sleep quality and achieve a good sleep aiding effect.

The invention discloses an intelligent sleep detection and intervention eyeshade system and method combined with a brain-computer interface, and belongs to the technical field of sleep detection and intervention. The intelligent sleep detection and intervention eyeshade system comprises a neural signal detection module, a core control module, a bone conduction module and a light stimulation module; the core control module is electrically connected with the neural signal detection module, the bone conduction module and the light stimulation module. Through the neural signal detection module, the system can perform electroencephalogram monitoring on a user and detect a corresponding neural signal of the user, real-time analysis is performed through the core control module based on a brain-computer interface technology to obtain an accurate sleep detection result, personalized sleep detection is provided for the user, and the sleep quality of the user can be improved according to the personalized sleep detection result. And real-time sleep intervention is realized, so that the sleep intervention effect on the user is improved.

The invention provides a loxoprofen sodium double-release capsule micro-tablet and a preparation method of the loxoprofen sodium double-release capsule micro-tablet. Through the synergistic effect of the quick-release micro-tablet and the sustained-release micro-tablet, the quick-release micro-tablet can realize quick release and absorption, and the sustained-release micro-tablet can maintain relatively stable blood concentration for a long time. The administration frequency is reduced, the coordination of the postprandial administration requirement and the dietary habit is ensured, and the occurrence of gastrointestinal tract adverse reactions is reduced. The preparation provided by the invention conforms to the dosage form design of the hour pharmacology, can quickly take effect through administration twice every day, can maintain the blood concentration in the high-incidence time period of night diseases, avoids the disadvantage of taking medicine after meal when the night diseases attack, guarantees the sleep quality, and improves the overall treatment effect. The micro tablet is small in size and easy to swallow, and the medication compliance of patients with dysphagia is obviously improved. Through dosage form design and improvement, unmet clinical requirements are expected to be met by virtue of obvious advantages of the traditional Chinese medicine composition.

The invention relates to the technical field of sleep aiding, in particular to an intelligent slow wave sleep aiding system based on adaptive adjustment, which comprises a health monitoring bracelet, a multi-mode sleep aiding pillow, a sleep aiding illumination system and a transcranial electrical stimulation system, the problems that a traditional sleep-aiding product is difficult to accurately adapt to the sleep state of a human body, the adjusting effect is poor and the like are solved, physiological and body movement data are collected by means of the health monitoring bracelet and optimized, states such as waking, light sleep and deep sleep can be automatically and accurately recognized in combination with sleep state judgment rules, the states are fed back to the main control unit of the pillow through wireless transmission, and the sleep-aiding function is achieved. Self-adaptive control of music and sound effects, adjustment of ambient light, transcranial electric intensity and the like based on the sleep state of the human body are achieved, scientific and personalized support is provided for sleep improvement, sleep quality improvement is assisted, and the method can be used for reference application in the fields of intelligent sleep product research and development, sleep health management and the like.

The invention discloses an intelligent pillow control method and device based on self-adaptive adjustment and a medium, belongs to the technical field of intelligent air bag pillows, and aims to solve the technical problems that the supporting effect of an existing intelligent pillow is difficult to adjust, sleep quality is difficult to really improve, neck pressure cannot be well relieved, and blood circulation cannot be well promoted. The method comprises the following steps: carrying out key pressure area distribution judgment on a head area and a neck area of a user, and determining an initial head pressure area and an initial neck pressure area; initial head air bag basic parameters and initial neck air bag basic parameters are determined; carrying out area correction processing on the initial head pressure area and the initial neck pressure area; and carrying out adaptive adjustment on the initial head airbag basic parameters and the initial neck airbag basic parameters, and carrying out data fusion on the compensation airbag parameters, the variable head airbag parameters and the variable neck airbag parameters to obtain a real-time pillow airbag control strategy.