CN114587281B - Intelligent pillow control method and system with sleep aiding function and readable storage medium - Google Patents

Intelligent pillow control method and system with sleep aiding function and readable storage medium Download PDF

Info

Publication number
CN114587281B
CN114587281B CN202210257770.9A CN202210257770A CN114587281B CN 114587281 B CN114587281 B CN 114587281B CN 202210257770 A CN202210257770 A CN 202210257770A CN 114587281 B CN114587281 B CN 114587281B
Authority
CN
China
Prior art keywords
sleep
data
user
information
characteristic
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202210257770.9A
Other languages
Chinese (zh)
Other versions
CN114587281A (en
Inventor
李军
付存谓
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang Xiangneng Sleep Technology Stock Co ltd
Original Assignee
Zhejiang Xiangneng Sleep Technology Stock Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang Xiangneng Sleep Technology Stock Co ltd filed Critical Zhejiang Xiangneng Sleep Technology Stock Co ltd
Priority to CN202210257770.9A priority Critical patent/CN114587281B/en
Publication of CN114587281A publication Critical patent/CN114587281A/en
Application granted granted Critical
Publication of CN114587281B publication Critical patent/CN114587281B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4806—Sleep evaluation
    • A61B5/4815—Sleep quality
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
    • A61B5/0816—Measuring devices for examining respiratory frequency
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A61B5/372—Analysis of electroencephalograms
    • A61B5/374—Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
    • A61B5/6892—Mats
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • A61M21/02—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis for inducing sleep or relaxation, e.g. by direct nerve stimulation, hypnosis, analgesia
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • A61M2021/0005—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
    • A61M2021/0027—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus by the hearing sense
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • A61M2021/0005—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
    • A61M2021/0066—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus with heating or cooling
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • A61M2021/0005—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
    • A61M2021/0077—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus with application of chemical or pharmacological stimulus
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Veterinary Medicine (AREA)
  • Pathology (AREA)
  • Biophysics (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Cardiology (AREA)
  • Physiology (AREA)
  • Databases & Information Systems (AREA)
  • Psychology (AREA)
  • Pulmonology (AREA)
  • Anesthesiology (AREA)
  • Theoretical Computer Science (AREA)
  • Psychiatry (AREA)
  • Acoustics & Sound (AREA)
  • Hematology (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Pain & Pain Management (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

The embodiment of the application provides an intelligent pillow control method and system with a sleep aiding function and a readable storage medium. The method comprises the following steps: acquiring sleep characteristic data information of a user, acquiring sleep individual data according to the sleep characteristic data information and environmental information, acquiring a sleep response characteristic data set of the user in a sleep information database according to the sleep individual data of the user, performing intelligent pillow regulation and control according to the sleep response characteristic data set, monitoring sleep dynamic information data of the user, performing threshold comparison according to the sleep dynamic information data monitored and acquired by the user in a preset time period to acquire an early warning level identification, and performing intelligent pillow corresponding regulation and control according to the early warning level identification; therefore, the sleep response data are acquired according to the sleep data information of the user and combined with the environment information to carry out intelligent pillow regulation and control, the sleep dynamic information of the user is monitored to carry out early warning, intelligent acquisition and regulation and control according to the sleep state parameters of the user are realized, individuation and intelligence of the intelligent pillow are improved, and user experience is improved.

Description

Intelligent pillow control method and system with sleep aiding function and readable storage medium
Technical Field
The application relates to the technical field of intelligent household articles and intelligent control, in particular to an intelligent pillow control method and system with a sleep-aiding function and a readable storage medium.
Background
Along with the acceleration of the life rhythm of residents, particularly the increase of the pressure of new middle-aged products, the sleep quality of the residents in the city is not good, the insomnia condition under the superposition of multiple factors is more and more common, the physical health of the residents is greatly influenced, and how to effectively improve the sleep quality has important value for improving the physical and psychological health of the residents and the life satisfaction degree.
The pillow is necessary for sleeping, the quality or performance of the pillow directly determines the sleeping quality of people, the current pillow only focuses on the touch feeling of a user, the eyesight is limited on improving the filler and the supporting function, the pillow does not have the function of personalized adjustment according to the difference of different users or the different sleeping states and physical conditions of each user, and the intelligent pillow capable of being intelligently adjusted according to the sleeping conditions and physical conditions of the users is not provided, so that a personalized and intelligent pillow product is designed to be in the future direction, the pillow does not have the design at present, and the market also lacks the intelligent product to meet the increasingly-increasing living demands of residents.
Accordingly, a related technical solution is needed to address the above-mentioned problems.
Disclosure of Invention
The embodiment of the application aims to provide an intelligent pillow control method and system with a sleep-aiding function and a readable storage medium, which can realize personalized and intelligent regulation and control of a pillow and improve user experience.
The embodiment of the application also provides an intelligent pillow control method with the sleep aiding function, which comprises the following steps:
acquiring sleep characteristic data information of a user, and acquiring sleep personality data according to the sleep characteristic data information and environment information;
acquiring a sleep response characteristic data set of the user from a user sleep information database according to the sleep personality data of the user;
performing intelligent pillow regulation and control according to the sleep response characteristic data set and monitoring sleep dynamic information data of the user;
performing threshold comparison according to sleep dynamic information data obtained by monitoring the user in a preset time period to obtain an early warning level mark;
and carrying out intelligent pillow corresponding regulation and control according to the early warning level identification.
Optionally, in the method for controlling an intelligent pillow with sleep aiding function according to the embodiment of the present application, the obtaining sleep characteristic data information of the user and obtaining sleep personality data according to the sleep characteristic data information and environmental information includes:
The sleep characteristic data information of the user is obtained and comprises physical characteristic information, sleep posture data, sleep health index and cervical vertebra health data;
acquiring environment information of sleeping of a user, wherein the environment information comprises season information, time information and room temperature data;
the physical characteristic information comprises user weight, age and gender information;
the sleep health index and the cervical vertebra health data are obtained through a medical platform;
and acquiring sleep personality data in a sleep quality detection model according to the sleep characteristic data information of the user and the environment information.
Optionally, in the method for controlling an intelligent pillow with sleep aiding function according to the embodiment of the present application, the acquiring sleep personality data in the sleep quality detection model according to the sleep feature data information of the user and the environmental information includes:
establishing a sleep quality detection model;
inputting physical characteristic information, sleep posture data, cervical vertebra health data, time information and room temperature data of the user into the sleep quality detection model to obtain sleep personality data;
the sleep personality data includes steady state electroencephalogram spectrum, steady state body temperature, cervical elevation, and steady state heart rate.
Optionally, in the method for controlling an intelligent pillow with sleep aiding function according to the embodiment of the present application, the acquiring, according to the sleep personality data of the user, the sleep response feature data set of the user in the sleep information database of the user includes:
obtaining a deep sleep steady-state coefficient according to the sleep personality data and the physical characteristic information of the user and the environmental information;
inquiring a plurality of historical sleep characteristic samples meeting threshold comparison requirements in a user sleep information database according to the user deep sleep steady-state coefficient;
and inquiring the sleep response characteristic data set of the user conforming to the similarity according to the plurality of historical sleep characteristic samples.
Optionally, in the method for controlling an intelligent pillow with sleep aiding function according to the embodiment of the present application, the querying, according to the plurality of historical sleep feature samples, a sleep response feature data set of the user meeting similarity includes:
acquiring a sample data set of a plurality of historical sleep characteristic samples;
the sample data set comprises body weight, steady state electroencephalogram spectrum, steady state body temperature, steady state heart rate, and room temperature data;
performing similarity comparison between the body weight, the steady-state electroencephalogram frequency spectrum, the steady-state body temperature, the steady-state heart rate and the room temperature data of the user and the sample data sets of the plurality of historical sleep characteristic samples to obtain a target sleep characteristic sample meeting the similarity requirement;
And taking the plurality of sleep response data of the target sleep characteristic sample as a sleep response characteristic data set of the user.
Optionally, in the method for controlling an intelligent pillow with sleep aiding function according to the embodiment of the present application, the performing intelligent pillow adjustment and control according to the sleep response feature data set and monitoring sleep dynamic information data of the user includes:
the sleep response characteristic data set comprises cervical vertebra correction data, audio excitation data, oxygen data, temperature regulation data and brain wave excitation data;
according to the data of the sleep response characteristic data set, the intelligent pillow is correspondingly regulated and controlled in posture, audio frequency, oxygen, temperature and brain wave current;
monitoring sleep dynamic information data of the user stimulated by the intelligent pillow within a preset time period after regulation and control;
the sleep dynamic information data comprises brain wave dynamic data, body temperature dynamic data, respiratory spectrum dynamic data and heart rate fluctuation data.
Optionally, in the method for controlling an intelligent pillow with sleep aiding function according to the embodiment of the present application, the performing threshold comparison according to sleep dynamic information data obtained by monitoring the user in a preset time period to obtain the early warning level identifier includes:
Acquiring a sleep steady state threshold set of a user, wherein the sleep steady state threshold set comprises an electroencephalogram steady state threshold, a body temperature steady state threshold, a respiratory spectrum steady state threshold and a heart rate steady state threshold;
comparing the sleep dynamic information data of the user with four thresholds of the sleep steady state threshold set correspondingly;
if all four data of the sleep dynamic information data are larger than the corresponding threshold value of the sleep steady state threshold value set, marking the sleep dynamic information data as a first-level early warning mark;
if the brain wave dynamic data, the body temperature dynamic data and the heart rate fluctuation data are respectively larger than the corresponding threshold values, marking as a secondary early warning mark;
if the brain wave dynamic data and the respiratory spectrum dynamic data are respectively larger than the corresponding threshold values, marking as a three-level early warning mark;
and if the body temperature dynamic data and the respiratory spectrum dynamic data are respectively larger than the corresponding threshold values, marking as a four-level early warning mark.
In a second aspect, an embodiment of the present application provides an intelligent pillow control system with a sleep-aiding function, where the system includes: the intelligent pillow control system comprises a memory and a processor, wherein the memory comprises a program of an intelligent pillow control method with a sleep aiding function, and the program of the intelligent pillow control method with the sleep aiding function realizes the following steps when being executed by the processor:
Acquiring sleep characteristic data information of a user, and acquiring sleep personality data according to the sleep characteristic data information and environment information;
acquiring a sleep response characteristic data set of the user from a user sleep information database according to the sleep personality data of the user;
performing intelligent pillow regulation and control according to the sleep response characteristic data set and monitoring sleep dynamic information data of the user;
performing threshold comparison according to sleep dynamic information data obtained by monitoring the user in a preset time period to obtain an early warning level mark;
and carrying out intelligent pillow corresponding regulation and control according to the early warning level identification.
Optionally, in the intelligent pillow control system with sleep aiding function according to the embodiment of the present application, the obtaining sleep characteristic data information of the user and obtaining sleep personality data according to the sleep characteristic data information and environmental information includes:
the sleep characteristic data information of the user is obtained and comprises physical characteristic information, sleep posture data, sleep health index and cervical vertebra health data;
acquiring environment information of sleeping of a user, wherein the environment information comprises season information, time information and room temperature data;
the physical characteristic information comprises user weight, age and gender information;
The sleep health index and the cervical vertebra health data are obtained through a medical platform;
and acquiring sleep personality data in a sleep quality detection model according to the sleep characteristic data information of the user and the environment information.
In a third aspect, an embodiment of the present application further provides a computer readable storage medium, where the computer readable storage medium includes an intelligent pillow control method program with a sleep aiding function, where when the intelligent pillow control method program with a sleep aiding function is executed by a processor, the steps of the intelligent pillow control method with a sleep aiding function as described in any one of the foregoing are implemented.
As can be seen from the above, according to the intelligent pillow control method, system and readable storage medium with sleep aiding function provided by the embodiments of the present application, sleep characteristic data is obtained by obtaining sleep characteristic data information of a user, sleep personality data is obtained according to the sleep characteristic data information and environmental information, a sleep response characteristic data set of the user is obtained in a sleep information database of the user according to the sleep personality data of the user, intelligent pillow regulation and control are performed according to the sleep response characteristic data set, sleep dynamic information data of the user are monitored, threshold comparison is performed according to the sleep dynamic information data obtained by the user in a preset time period, an early warning level identifier is obtained, and intelligent pillow corresponding regulation and control is performed according to the early warning level identifier; therefore, the sleep response data are acquired according to the sleep data information of the user and combined with the environment information to carry out intelligent pillow regulation and control, the sleep dynamic information of the user is monitored to carry out early warning, intelligent acquisition and regulation and control according to the sleep state parameters of the user are realized, individuation and intelligence of the intelligent pillow are improved, and user experience is improved.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of an intelligent pillow control method with sleep aiding function according to an embodiment of the present application;
FIG. 2 is a flowchart of an intelligent pillow control method with sleep aiding function according to an embodiment of the present application;
FIG. 3 is a flowchart of a method for controlling an intelligent pillow with sleep aiding function according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an intelligent pillow control system with sleep-aiding function according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, fig. 1 is a flowchart of an intelligent pillow control with sleep aiding function according to some embodiments of the present application. The intelligent pillow control method with the sleep-aiding function is used in terminal equipment, such as mobile phones, computers and the like. The intelligent pillow control method with the sleep aiding function comprises the following steps:
s101, acquiring sleep characteristic data information of a user, and acquiring sleep individual data according to the sleep characteristic data information and environment information;
s102, acquiring a sleep response characteristic data set of the user from a sleep information database of the user according to the sleep personality data of the user;
s103, intelligent pillow regulation and control are carried out according to the sleep response characteristic data set, and sleep dynamic information data of the user are monitored;
s104, comparing thresholds according to sleep dynamic information data obtained by monitoring the user in a preset time period to obtain an early warning level mark;
and S105, performing intelligent pillow corresponding regulation and control according to the early warning level identification.
It should be noted that, in order to adapt to the regulation and control requirement of the user on the intelligent pillow, the sleep characteristic data information of the user is obtained, the acquired environmental information is combined to obtain the sleep personality data, the sleep response characteristic data set is found according to the sleep personality data and the target sleep characteristic sample conforming to the similarity is queried in the sleep information database of the user, the intelligent pillow is regulated and controlled and the sleep dynamic information data of the user is monitored, the early warning level identification is obtained according to the comparison between the sleep dynamic information data and the sleep steady state threshold value set of the user in the preset time period, and then the next regulation and control are carried out according to the identification.
Referring to fig. 2, fig. 2 is a flowchart of an intelligent pillow control with sleep aiding function according to some embodiments of the present application. According to the embodiment of the application, the sleep characteristic data information of the user is obtained, and the sleep personality data is obtained according to the sleep characteristic data information and the environment information, specifically:
s201, acquiring sleep characteristic data information of a user, wherein the sleep characteristic data information comprises body characteristic information, sleep posture data, sleep health index and cervical vertebra health data;
s202, acquiring environment information of sleeping of a user, wherein the environment information comprises season information, time information and room temperature data;
s203, the physical characteristic information includes user weight, age and sex information;
s204, the sleep health index and the cervical vertebra health data are obtained through a medical platform;
s205, acquiring sleep personality data in a sleep quality detection model according to the sleep characteristic data information of the user and the environment information.
It should be noted that, to accurately determine the sleep condition of the user in the preset period, sleep personality data of the user is obtained through the sleep quality detection model according to the obtained physical feature information, sleep posture data, cervical vertebra health data and environment information of the user, and a data base is established for obtaining sleep response data of the user in the next step, wherein the sleep health index and the cervical vertebra health data of the user are obtained through the third-party medical platform.
Referring to fig. 3, fig. 3 is a flowchart of an intelligent pillow control with sleep aiding function according to some embodiments of the present application. According to the embodiment of the application, the sleep personality data is obtained in the sleep quality detection model according to the sleep characteristic data information of the user and the environmental information, specifically:
s301, establishing a sleep quality detection model;
s302, inputting physical characteristic information, sleep posture data, cervical vertebra health data, time information and room temperature data of the user into the sleep quality detection model to obtain sleep personality data;
s303, the sleep personality data comprises a steady state electroencephalogram frequency spectrum, a steady state body temperature, a cervical vertebra elevation angle and a steady state heart rate.
It should be noted that, to accurately obtain the sleep personality data of the user, the sleep personality data is obtained by inputting physical feature information, sleep posture data, cervical vertebra health data, time information and room temperature data of the user into a sleep quality detection model, where the sleep quality detection model is obtained by training physical feature information, sleep posture data, cervical vertebra health data, time information, room temperature data and sleep personality data of a large number of historical periods of the user, and the training sample set is obtained by preprocessing physical feature information, sleep posture data, cervical vertebra health data, time information, room temperature data and sleep personality data recorded by the historical user, and is input into an initialized sleep quality detection model to train to obtain the accuracy of the output result, and if the accuracy is greater than a preset accuracy threshold, the sleep quality detection model is obtained.
According to the embodiment of the invention, the sleep response characteristic data set of the user is obtained from the sleep information database according to the sleep personality data of the user, specifically:
obtaining a deep sleep steady-state coefficient according to the sleep personality data and the physical characteristic information of the user and the environmental information;
inquiring a plurality of historical sleep characteristic samples meeting threshold comparison requirements in a user sleep information database according to the user deep sleep steady-state coefficient;
and inquiring the sleep response characteristic data set of the user conforming to the similarity according to the plurality of historical sleep characteristic samples.
It should be noted that, in order to obtain sleep adjustment data adapted to a sleep state of a user, an adapted sleep response feature data set of the user is obtained, the sleep response feature data set is obtained according to a historical sleep feature sample meeting a user similarity requirement in a user sleep information database, a deep sleep steady state coefficient is obtained through calculation according to sleep individual data, physical feature information and environmental information of the user, then a plurality of historical sleep feature samples meeting a threshold comparison requirement with the deep sleep steady state coefficient of the user in the user sleep information database are queried according to the deep sleep steady state coefficient of the user, the deep sleep steady state coefficient of the selected plurality of historical sleep feature samples meets the threshold comparison requirement of the user, and then the sleep response feature data set of the user is obtained by similarity screening according to the plurality of historical sleep feature samples;
The calculation formula of the deep sleep steady-state coefficient is as follows:
t is a deep sleep steady-state coefficient, p is body temperature, f is brain electrical spectrum, r is heart rate, n is the number of time nodes in a preset time period,for the ith time node of n time nodes, p o Is steady state body temperature, f o Is steady state brain electrical spectrum, r o Is a steady state heart rate, I e For the acquired sleep activity characteristic values of the user, delta is a sleep characteristic coefficient, sigma and +.>The characteristic index is that A is the age of the user, B is the weight of the user, and θ is the acquired sleep health index of the user.
According to an embodiment of the present invention, the querying the sleep response feature data set of the user according to the plurality of historical sleep feature samples, which accords with the similarity, specifically includes:
acquiring a sample data set of a plurality of historical sleep characteristic samples;
the sample data set comprises body weight, steady state electroencephalogram spectrum, steady state body temperature, steady state heart rate, and room temperature data;
performing similarity comparison between the body weight, the steady-state electroencephalogram frequency spectrum, the steady-state body temperature, the steady-state heart rate and the room temperature data of the user and the sample data sets of the plurality of historical sleep characteristic samples to obtain a target sleep characteristic sample meeting the similarity requirement;
and taking the plurality of sleep response data of the target sleep characteristic sample as a sleep response characteristic data set of the user.
It should be noted that, according to the comparison of the sample data set of the plurality of historical sleep characteristic samples queried in the user sleep information database and the corresponding data of the user including the weight, the steady state electroencephalogram frequency spectrum, the steady state body temperature, the steady state heart rate and the room temperature data, the historical sleep characteristic sample with the largest similarity is screened out as the target sleep characteristic sample, the plurality of sleep response data of the target sleep characteristic sample are taken as the sleep response characteristic data set of the user, the sleep response characteristic data set is a set of a plurality of sleep response data which are stimulated and regulated for optimizing the sleep state of the user or the sample and aim at the sleep data of the user or the sample, the sleep response characteristic data set exists in each sample of the user sleep information database, the sleep response characteristic data set is regulated by taking the intelligent pillow as the main body, so as to realize the optimization of the sleep state of the user or the sample, and the similarity comparison in this case adopts the Euclidean distance or cosine similarity comparison.
According to the embodiment of the invention, the intelligent pillow regulation and control are performed according to the sleep response characteristic data set, and the sleep dynamic information data of the user are monitored, specifically:
The sleep response characteristic data set comprises cervical vertebra correction data, audio excitation data, oxygen data, temperature regulation data and brain wave excitation data;
according to the data of the sleep response characteristic data set, the intelligent pillow is correspondingly regulated and controlled in posture, audio frequency, oxygen, temperature and brain wave current;
monitoring sleep dynamic information data of the user stimulated by the intelligent pillow within a preset time period after regulation and control;
the sleep dynamic information data comprises brain wave dynamic data, body temperature dynamic data, respiratory spectrum dynamic data and heart rate fluctuation data.
The sleep response characteristic data set is a set of adjustment and excitation data for improving the sleep state of the user, and comprises cervical vertebra correction data, audio excitation data, oxygen data, temperature regulation data and brain wave excitation data, the adjustment of the cervical vertebra elevation angle of the user, the excitation of brain wave current, oxygen release, audio playing and temperature adjustment are realized through the data input intelligent pillow, the sleep state of the user is adjusted through the function of the intelligent pillow, the aim is to adjust the body temperature, heart rate, respiration and brain wave frequency spectrum of the user to the target state, and the sleep dynamic information data of the monitored user after the excitation and the regulation of the user comprise brain wave dynamic data, body temperature dynamic data, respiration frequency spectrum dynamic data and heart rate fluctuation data.
According to the embodiment of the invention, the early warning level mark is obtained by comparing the threshold value according to the sleep dynamic information data monitored and obtained by the user in the preset time period, specifically:
acquiring a sleep steady state threshold set of a user, wherein the sleep steady state threshold set comprises an electroencephalogram steady state threshold, a body temperature steady state threshold, a respiratory spectrum steady state threshold and a heart rate steady state threshold;
comparing the sleep dynamic information data of the user with four thresholds of the sleep steady state threshold set correspondingly;
if all four data of the sleep dynamic information data are larger than the corresponding threshold value of the sleep steady state threshold value set, marking the sleep dynamic information data as a first-level early warning mark;
if the brain wave dynamic data, the body temperature dynamic data and the heart rate fluctuation data are respectively larger than the corresponding threshold values, marking as a secondary early warning mark;
if the brain wave dynamic data and the respiratory spectrum dynamic data are respectively larger than the corresponding threshold values, marking as a three-level early warning mark;
and if the body temperature dynamic data and the respiratory spectrum dynamic data are respectively larger than the corresponding threshold values, marking as a four-level early warning mark.
After the excitation and regulation of the intelligent pillow to the user are completed, the user sleep dynamic information data monitored in a preset time period is compared with a preset sleep steady state threshold set by corresponding data threshold values, four data of the user sleep dynamic information data are compared with the corresponding threshold values, and identification classification of early warning levels is performed according to the threshold value comparison result, so that the regulation effect of the intelligent pillow to the user is checked.
According to an embodiment of the present invention, further comprising:
performing intelligent pillow corresponding regulation and control according to the early warning level identification;
if the early warning level mark of the monitored user is a primary early warning mark, regulating and controlling the gesture, the audio frequency, the oxygen, the temperature and the brain wave current of the intelligent pillow;
if the early warning level mark of the monitored user is a secondary early warning mark, regulating and controlling oxygen, temperature and brain wave current of the intelligent pillow;
if the early warning level mark of the monitored user is a three-level early warning mark, regulating and controlling the gesture, the audio frequency and the brain wave current of the intelligent pillow;
and if the early warning level mark of the monitored user is a four-level early warning mark, regulating and controlling the audio frequency, the oxygen and the temperature of the intelligent pillow.
After the user sleep state is checked, the intelligent pillow is readjusted according to the obtained early warning mark level to further optimize the user sleep state.
According to an embodiment of the present invention, further comprising:
tracking and monitoring the sleep dynamic information data of the user after the intelligent pillow is regulated;
when the brain wave dynamic data of the user reach the preset steady-state electric wave data, the breathing frequency spectrum data, the body temperature data and the heart rate data corresponding to the next time node are read;
Acquiring sleep steady-state characteristic parameters according to the respiratory spectrum data, the body temperature data and the heart rate data;
and judging the sleep state of the user according to the sleep steady-state characteristic parameters by carrying out preset values.
The method includes the steps that a sleep preset value is set for accurately judging the sleep state of a user, the preset value is a reference value for enabling the sleep of the user to reach a target stable state, the sleep steady state characteristic parameter of the user is compared with the preset value, if the sleep steady state characteristic parameter is larger than or equal to the preset value, the user reaches the target sleep stable state, the sleep dynamic information data of the user are monitored according to the detection, when the brain wave of the user reaches a stable alpha wave band, the breathing frequency spectrum data, the body temperature data and the heart rate data of a next time node are read, the sleep steady state characteristic parameter of the user is calculated according to the breathing frequency spectrum data, the body temperature data and the heart rate data, and the sleep state of the user is judged according to a comparison result of the sleep steady state characteristic parameter and the preset value;
the calculation formula of the sleep steady-state characteristic parameter is as follows:
U＝εK+φP+γR/H s ；
ε、φ、gamma is characteristic coefficient, K breath frequency spectrum data, P is body temperature data, R is heart rate data, H s For the sleep dynamic threshold (dynamic value readable according to the sleep state of the user), U is a sleep steady-state characteristic parameter.
As shown in fig. 4, the present invention further discloses an intelligent pillow control system with sleep aiding function, which includes a memory 201 and a processor 202, wherein the memory 201 includes an intelligent pillow control method program with sleep aiding function, and when the intelligent pillow control method program with sleep aiding function is executed by the processor 202, the following steps are implemented:
acquiring sleep characteristic data information of a user, and acquiring sleep personality data according to the sleep characteristic data information and environment information;
acquiring a sleep response characteristic data set of the user from a user sleep information database according to the sleep personality data of the user;
performing intelligent pillow regulation and control according to the sleep response characteristic data set and monitoring sleep dynamic information data of the user;
performing threshold comparison according to sleep dynamic information data obtained by monitoring the user in a preset time period to obtain an early warning level mark;
and carrying out intelligent pillow corresponding regulation and control according to the early warning level identification.
It should be noted that, in order to adapt to the regulation and control requirement of the user on the intelligent pillow, the sleep characteristic data information of the user is obtained, the acquired environmental information is combined to obtain the sleep personality data, the sleep response characteristic data set is found according to the sleep personality data and the target sleep characteristic sample conforming to the similarity is queried in the sleep information database of the user, the intelligent pillow is regulated and controlled and the sleep dynamic information data of the user is monitored, the early warning level identification is obtained according to the comparison between the sleep dynamic information data and the sleep steady state threshold value set of the user in the preset time period, and then the next regulation and control are carried out according to the identification.
According to the embodiment of the invention, the sleep characteristic data information of the user is obtained, and the sleep personality data is obtained according to the sleep characteristic data information and the environment information, specifically:
the sleep characteristic data information of the user is obtained and comprises physical characteristic information, sleep posture data, sleep health index and cervical vertebra health data;
acquiring environment information of sleeping of a user, wherein the environment information comprises season information, time information and room temperature data;
the physical characteristic information comprises user weight, age and gender information;
the sleep health index and the cervical vertebra health data are obtained through a medical platform;
and acquiring sleep personality data in a sleep quality detection model according to the sleep characteristic data information of the user and the environment information.
It should be noted that, to accurately determine the sleep condition of the user in the preset period, sleep personality data of the user is obtained through the sleep quality detection model according to the obtained physical feature information, sleep posture data, cervical vertebra health data and environment information of the user, and a data base is established for obtaining sleep response data of the user in the next step, wherein the sleep health index and the cervical vertebra health data of the user are obtained through the third-party medical platform.
According to the embodiment of the invention, the sleep personality data is obtained in the sleep quality detection model according to the sleep characteristic data information of the user and the environmental information, specifically:
establishing a sleep quality detection model;
inputting physical characteristic information, sleep posture data, cervical vertebra health data, time information and room temperature data of the user into the sleep quality detection model to obtain sleep personality data;
the sleep personality data includes steady state electroencephalogram spectrum, steady state body temperature, cervical elevation, and steady state heart rate.
It should be noted that, to accurately obtain the sleep personality data of the user, the sleep personality data is obtained by inputting physical feature information, sleep posture data, cervical vertebra health data, time information and room temperature data of the user into a sleep quality detection model, where the sleep quality detection model is obtained by training physical feature information, sleep posture data, cervical vertebra health data, time information, room temperature data and sleep personality data of a large number of historical periods of the user, and the training sample set is obtained by preprocessing physical feature information, sleep posture data, cervical vertebra health data, time information, room temperature data and sleep personality data recorded by the historical user, and is input into an initialized sleep quality detection model to train to obtain the accuracy of the output result, and if the accuracy is greater than a preset accuracy threshold, the sleep quality detection model is obtained.
According to the embodiment of the invention, the sleep response characteristic data set of the user is obtained from the sleep information database according to the sleep personality data of the user, specifically:
obtaining a deep sleep steady-state coefficient according to the sleep personality data and the physical characteristic information of the user and the environmental information;
inquiring a plurality of historical sleep characteristic samples meeting threshold comparison requirements in a user sleep information database according to the user deep sleep steady-state coefficient;
and inquiring the sleep response characteristic data set of the user conforming to the similarity according to the plurality of historical sleep characteristic samples.
It should be noted that, in order to obtain sleep adjustment data adapted to a sleep state of a user, an adapted sleep response feature data set of the user is obtained, the sleep response feature data set is obtained according to a historical sleep feature sample meeting a user similarity requirement in a user sleep information database, a deep sleep steady state coefficient is obtained through calculation according to sleep individual data, physical feature information and environmental information of the user, then a plurality of historical sleep feature samples meeting a threshold comparison requirement with the deep sleep steady state coefficient of the user in the user sleep information database are queried according to the deep sleep steady state coefficient of the user, the deep sleep steady state coefficient of the selected plurality of historical sleep feature samples meets the threshold comparison requirement of the user, and then the sleep response feature data set of the user is obtained by similarity screening according to the plurality of historical sleep feature samples;
The calculation formula of the deep sleep steady-state coefficient is as follows:
t is a deep sleep steady-state coefficient, p is body temperature, f is brain electrical spectrum, r is heart rate, n is the number of time nodes in a preset time period,for the ith time node of n time nodes, p o Is steady state body temperature, f o Is steady state brain electrical spectrum, r o Is a steady state heart rate, I e For the acquired sleep activity characteristic values of the user, delta is a sleep characteristic coefficient, sigma and +.>The characteristic index is that A is the age of the user, B is the weight of the user, and θ is the acquired sleep health index of the user.
According to an embodiment of the present invention, the querying the sleep response feature data set of the user according to the plurality of historical sleep feature samples, which accords with the similarity, specifically includes:
acquiring a sample data set of a plurality of historical sleep characteristic samples;
the sample data set comprises body weight, steady state electroencephalogram spectrum, steady state body temperature, steady state heart rate, and room temperature data;
performing similarity comparison between the body weight, the steady-state electroencephalogram frequency spectrum, the steady-state body temperature, the steady-state heart rate and the room temperature data of the user and the sample data sets of the plurality of historical sleep characteristic samples to obtain a target sleep characteristic sample meeting the similarity requirement;
and taking the plurality of sleep response data of the target sleep characteristic sample as a sleep response characteristic data set of the user.
It should be noted that, according to the comparison of the sample data set of the plurality of historical sleep characteristic samples queried in the user sleep information database and the corresponding data of the user including the weight, the steady state electroencephalogram frequency spectrum, the steady state body temperature, the steady state heart rate and the room temperature data, the historical sleep characteristic sample with the largest similarity is screened out as the target sleep characteristic sample, the plurality of sleep response data of the target sleep characteristic sample are taken as the sleep response characteristic data set of the user, the sleep response characteristic data set is a set of a plurality of sleep response data which are stimulated and regulated for optimizing the sleep state of the user or the sample and aim at the sleep data of the user or the sample, the sleep response characteristic data set exists in each sample of the user sleep information database, the sleep response characteristic data set is regulated by taking the intelligent pillow as the main body, so as to realize the optimization of the sleep state of the user or the sample, and the similarity comparison in this case adopts the Euclidean distance or cosine similarity comparison.
According to the embodiment of the invention, the intelligent pillow regulation and control are performed according to the sleep response characteristic data set, and the sleep dynamic information data of the user are monitored, specifically:
The sleep response characteristic data set comprises cervical vertebra correction data, audio excitation data, oxygen data, temperature regulation data and brain wave excitation data;
according to the data of the sleep response characteristic data set, the intelligent pillow is correspondingly regulated and controlled in posture, audio frequency, oxygen, temperature and brain wave current;
monitoring sleep dynamic information data of the user stimulated by the intelligent pillow within a preset time period after regulation and control;
the sleep dynamic information data comprises brain wave dynamic data, body temperature dynamic data, respiratory spectrum dynamic data and heart rate fluctuation data.
The sleep response characteristic data set is a set of adjustment and excitation data for improving the sleep state of the user, and comprises cervical vertebra correction data, audio excitation data, oxygen data, temperature regulation data and brain wave excitation data, the adjustment of the cervical vertebra elevation angle of the user, the excitation of brain wave current, oxygen release, audio playing and temperature adjustment are realized through the data input intelligent pillow, the sleep state of the user is adjusted through the function of the intelligent pillow, the aim is to adjust the body temperature, heart rate, respiration and brain wave frequency spectrum of the user to the target state, and the sleep dynamic information data of the monitored user after the excitation and the regulation of the user comprise brain wave dynamic data, body temperature dynamic data, respiration frequency spectrum dynamic data and heart rate fluctuation data.
According to the embodiment of the invention, the early warning level mark is obtained by comparing the threshold value according to the sleep dynamic information data monitored and obtained by the user in the preset time period, specifically:
acquiring a sleep steady state threshold set of a user, wherein the sleep steady state threshold set comprises an electroencephalogram steady state threshold, a body temperature steady state threshold, a respiratory spectrum steady state threshold and a heart rate steady state threshold;
comparing the sleep dynamic information data of the user with four thresholds of the sleep steady state threshold set correspondingly;
if all four data of the sleep dynamic information data are larger than the corresponding threshold value of the sleep steady state threshold value set, marking the sleep dynamic information data as a first-level early warning mark;
if the brain wave dynamic data, the body temperature dynamic data and the heart rate fluctuation data are respectively larger than the corresponding threshold values, marking as a secondary early warning mark;
if the brain wave dynamic data and the respiratory spectrum dynamic data are respectively larger than the corresponding threshold values, marking as a three-level early warning mark;
and if the body temperature dynamic data and the respiratory spectrum dynamic data are respectively larger than the corresponding threshold values, marking as a four-level early warning mark.
After the excitation and regulation of the intelligent pillow to the user are completed, the user sleep dynamic information data monitored in a preset time period is compared with a preset sleep steady state threshold set by corresponding data threshold values, four data of the user sleep dynamic information data are compared with the corresponding threshold values, and identification classification of early warning levels is performed according to the threshold value comparison result, so that the regulation effect of the intelligent pillow to the user is checked.
According to an embodiment of the present invention, further comprising:
performing intelligent pillow corresponding regulation and control according to the early warning level identification;
if the early warning level mark of the monitored user is a primary early warning mark, regulating and controlling the gesture, the audio frequency, the oxygen, the temperature and the brain wave current of the intelligent pillow;
if the early warning level mark of the monitored user is a secondary early warning mark, regulating and controlling oxygen, temperature and brain wave current of the intelligent pillow;
if the early warning level mark of the monitored user is a three-level early warning mark, regulating and controlling the gesture, the audio frequency and the brain wave current of the intelligent pillow;
and if the early warning level mark of the monitored user is a four-level early warning mark, regulating and controlling the audio frequency, the oxygen and the temperature of the intelligent pillow.
After the user sleep state is checked, the intelligent pillow is readjusted according to the obtained early warning mark level to further optimize the user sleep state.
According to an embodiment of the present invention, further comprising:
tracking and monitoring the sleep dynamic information data of the user after the intelligent pillow is regulated;
when the brain wave dynamic data of the user reach the preset steady-state electric wave data, the breathing frequency spectrum data, the body temperature data and the heart rate data corresponding to the next time node are read;
Acquiring sleep steady-state characteristic parameters according to the respiratory spectrum data, the body temperature data and the heart rate data;
and judging the sleep state of the user according to the sleep steady-state characteristic parameters by carrying out preset values.
The method includes the steps that a sleep preset value is set for accurately judging the sleep state of a user, the preset value is a reference value for enabling the sleep of the user to reach a target stable state, the sleep steady state characteristic parameter of the user is compared with the preset value, if the sleep steady state characteristic parameter is larger than or equal to the preset value, the user reaches the target sleep stable state, the sleep dynamic information data of the user are monitored according to the detection, when the brain wave of the user reaches a stable alpha wave band, the breathing frequency spectrum data, the body temperature data and the heart rate data of a next time node are read, the sleep steady state characteristic parameter of the user is calculated according to the breathing frequency spectrum data, the body temperature data and the heart rate data, and the sleep state of the user is judged according to a comparison result of the sleep steady state characteristic parameter and the preset value;
the calculation formula of the sleep steady-state characteristic parameter is as follows:
U＝εK+φP+γR/H s ；
epsilon, phi and gamma are characteristic coefficients, K breath frequency spectrum data, P is body temperature data, R is heart rate data and H s For the sleep dynamic threshold (dynamic value readable according to the sleep state of the user), U is a sleep steady-state characteristic parameter.
A third aspect of the present invention provides a readable storage medium, including an intelligent pillow control method program with a sleep aiding function, where the intelligent pillow control method program with a sleep aiding function, when executed by a processor, implements the steps of the intelligent pillow control method with a sleep aiding function as described in any one of the above.
The invention discloses an intelligent pillow control method, a system and a readable storage medium with a sleep aiding function, which are characterized in that sleep characteristic data information of a user is obtained, sleep personality data is obtained according to the sleep characteristic data information and environmental information, a sleep response characteristic data set of the user is obtained in a sleep information database according to the sleep personality data of the user, intelligent pillow regulation and control are carried out according to the sleep response characteristic data set, sleep dynamic information data of the user are monitored, threshold comparison is carried out according to the sleep dynamic information data obtained by the user in a preset time period, an early warning level identification is obtained, and intelligent pillow corresponding regulation and control are carried out according to the early warning level identification; therefore, the sleep response data are acquired according to the sleep data information of the user and combined with the environment information to carry out intelligent pillow regulation and control, the sleep dynamic information of the user is monitored to carry out early warning, intelligent acquisition and regulation and control according to the sleep state parameters of the user are realized, individuation and intelligence of the intelligent pillow are improved, and user experience is improved.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.

Claims (4)

1. An intelligent pillow control method with sleep aiding function is characterized by comprising the following steps:
acquiring sleep characteristic data information of a user, and acquiring sleep personality data according to the sleep characteristic data information and environment information;
acquiring a sleep response characteristic data set of the user from a user sleep information database according to the sleep personality data of the user;
performing intelligent pillow regulation and control according to the sleep response characteristic data set and monitoring sleep dynamic information data of the user;
performing threshold comparison according to sleep dynamic information data obtained by monitoring the user in a preset time period to obtain an early warning level mark;
performing intelligent pillow corresponding regulation and control according to the early warning level identification;
the step of obtaining sleep characteristic data information of the user and obtaining sleep personality data according to the sleep characteristic data information and the environment information comprises the following steps:
the sleep characteristic data information of the user is obtained and comprises physical characteristic information, sleep posture data, sleep health index and cervical vertebra health data;
acquiring environment information of sleeping of a user, wherein the environment information comprises season information, time information and room temperature data;
the physical characteristic information comprises user weight, age and gender information;
The sleep health index and the cervical vertebra health data are obtained through a medical platform;
acquiring sleep personality data in a sleep quality detection model according to the sleep characteristic data information of the user and the environment information;
the step of acquiring sleep personality data in a sleep quality detection model according to the sleep characteristic data information of the user and the environmental information comprises the following steps:
establishing a sleep quality detection model;
inputting physical characteristic information, sleep posture data, cervical vertebra health data, time information and room temperature data of the user into the sleep quality detection model to obtain sleep personality data;
the sleep personality data comprises a steady state electroencephalogram frequency spectrum, a steady state body temperature, a cervical vertebra elevation angle and a steady state heart rate;
the step of obtaining the sleep response characteristic data set of the user in a user sleep information database according to the sleep personality data of the user comprises the following steps:
obtaining a deep sleep steady-state coefficient according to the sleep personality data and the physical characteristic information of the user and the environmental information;
inquiring a plurality of historical sleep characteristic samples meeting threshold comparison requirements in a user sleep information database according to the user deep sleep steady-state coefficient;
Inquiring a sleep response characteristic data set of the user conforming to the similarity according to the plurality of historical sleep characteristic samples;
the querying the sleep response characteristic data set of the user conforming to the similarity according to the plurality of historical sleep characteristic samples comprises:
acquiring a sample data set of a plurality of historical sleep characteristic samples;
the sample data set comprises body weight, steady state electroencephalogram spectrum, steady state body temperature, steady state heart rate, and room temperature data;
performing similarity comparison between the body weight, the steady-state electroencephalogram frequency spectrum, the steady-state body temperature, the steady-state heart rate and the room temperature data of the user and the sample data sets of the plurality of historical sleep characteristic samples to obtain a target sleep characteristic sample meeting the similarity requirement;
taking a plurality of sleep response data of the target sleep characteristic sample as a sleep response characteristic data set of the user;
the intelligent pillow regulation and control and the monitoring of the sleep dynamic information data of the user are carried out according to the sleep response characteristic data set, and the intelligent pillow regulation and control method comprises the following steps:
the sleep response characteristic data set comprises cervical vertebra correction data, audio excitation data, oxygen data, temperature regulation data and brain wave excitation data;
according to the data of the sleep response characteristic data set, the intelligent pillow is correspondingly regulated and controlled in posture, audio frequency, oxygen, temperature and brain wave current;
Monitoring sleep dynamic information data of the user stimulated by the intelligent pillow within a preset time period after regulation and control;
the sleep dynamic information data comprises brain wave dynamic data, body temperature dynamic data, respiratory spectrum dynamic data and heart rate fluctuation data.
2. The intelligent pillow control method with sleep aiding function according to claim 1, wherein the step of obtaining the early warning level identifier by comparing threshold values according to sleep dynamic information data obtained by the user during a preset time period comprises the steps of:
acquiring a sleep steady state threshold set of a user, wherein the sleep steady state threshold set comprises an electroencephalogram steady state threshold, a body temperature steady state threshold, a respiratory spectrum steady state threshold and a heart rate steady state threshold;
comparing the sleep dynamic information data of the user with four thresholds of the sleep steady state threshold set correspondingly;
if all four data of the sleep dynamic information data are larger than the corresponding threshold value of the sleep steady state threshold value set, marking the sleep dynamic information data as a first-level early warning mark;
if the brain wave dynamic data, the body temperature dynamic data and the heart rate fluctuation data are respectively larger than the corresponding threshold values, marking as a secondary early warning mark;
If the brain wave dynamic data and the respiratory spectrum dynamic data are respectively larger than the corresponding threshold values, marking as a three-level early warning mark;
and if the body temperature dynamic data and the respiratory spectrum dynamic data are respectively larger than the corresponding threshold values, marking as a four-level early warning mark.
3. An intelligent pillow control system with sleep aiding function, which is characterized in that the system comprises: the intelligent pillow control system comprises a memory and a processor, wherein the memory comprises a program of an intelligent pillow control method with a sleep aiding function, and the program of the intelligent pillow control method with the sleep aiding function realizes the following steps when being executed by the processor:
acquiring sleep characteristic data information of a user, and acquiring sleep personality data according to the sleep characteristic data information and environment information;
acquiring a sleep response characteristic data set of the user from a user sleep information database according to the sleep personality data of the user;
performing intelligent pillow regulation and control according to the sleep response characteristic data set and monitoring sleep dynamic information data of the user;
performing threshold comparison according to sleep dynamic information data obtained by monitoring the user in a preset time period to obtain an early warning level mark;
Performing intelligent pillow corresponding regulation and control according to the early warning level identification;
the step of obtaining sleep characteristic data information of the user and obtaining sleep personality data according to the sleep characteristic data information and the environment information comprises the following steps:
the sleep characteristic data information of the user is obtained and comprises physical characteristic information, sleep posture data, sleep health index and cervical vertebra health data;
acquiring environment information of sleeping of a user, wherein the environment information comprises season information, time information and room temperature data;
the physical characteristic information comprises user weight, age and gender information;
the sleep health index and the cervical vertebra health data are obtained through a medical platform;
acquiring sleep personality data in a sleep quality detection model according to the sleep characteristic data information of the user and the environment information;
the step of acquiring sleep personality data in a sleep quality detection model according to the sleep characteristic data information of the user and the environmental information comprises the following steps:
establishing a sleep quality detection model;
inputting physical characteristic information, sleep posture data, cervical vertebra health data, time information and room temperature data of the user into the sleep quality detection model to obtain sleep personality data;
The sleep personality data comprises a steady state electroencephalogram frequency spectrum, a steady state body temperature, a cervical vertebra elevation angle and a steady state heart rate;
the step of obtaining the sleep response characteristic data set of the user in a user sleep information database according to the sleep personality data of the user comprises the following steps:
obtaining a deep sleep steady-state coefficient according to the sleep personality data and the physical characteristic information of the user and the environmental information;
inquiring a plurality of historical sleep characteristic samples meeting threshold comparison requirements in a user sleep information database according to the user deep sleep steady-state coefficient;
inquiring a sleep response characteristic data set of the user conforming to the similarity according to the plurality of historical sleep characteristic samples;
the querying the sleep response characteristic data set of the user conforming to the similarity according to the plurality of historical sleep characteristic samples comprises:
acquiring a sample data set of a plurality of historical sleep characteristic samples;
the sample data set comprises body weight, steady state electroencephalogram spectrum, steady state body temperature, steady state heart rate, and room temperature data;
performing similarity comparison between the body weight, the steady-state electroencephalogram frequency spectrum, the steady-state body temperature, the steady-state heart rate and the room temperature data of the user and the sample data sets of the plurality of historical sleep characteristic samples to obtain a target sleep characteristic sample meeting the similarity requirement;
Taking a plurality of sleep response data of the target sleep characteristic sample as a sleep response characteristic data set of the user;
the intelligent pillow regulation and control and the monitoring of the sleep dynamic information data of the user are carried out according to the sleep response characteristic data set, and the intelligent pillow regulation and control method comprises the following steps:
the sleep response characteristic data set comprises cervical vertebra correction data, audio excitation data, oxygen data, temperature regulation data and brain wave excitation data;
according to the data of the sleep response characteristic data set, the intelligent pillow is correspondingly regulated and controlled in posture, audio frequency, oxygen, temperature and brain wave current;
monitoring sleep dynamic information data of the user stimulated by the intelligent pillow within a preset time period after regulation and control;
the sleep dynamic information data comprises brain wave dynamic data, body temperature dynamic data, respiratory spectrum dynamic data and heart rate fluctuation data.
4. A computer readable storage medium, wherein the computer readable storage medium includes an intelligent pillow control method program with a sleep aiding function, and when the intelligent pillow control method program with a sleep aiding function is executed by a processor, the steps of the intelligent pillow control method with a sleep aiding function as claimed in any one of claims 1 to 2 are implemented.
CN202210257770.9A 2022-03-16 2022-03-16 Intelligent pillow control method and system with sleep aiding function and readable storage medium Active CN114587281B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210257770.9A CN114587281B (en) 2022-03-16 2022-03-16 Intelligent pillow control method and system with sleep aiding function and readable storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210257770.9A CN114587281B (en) 2022-03-16 2022-03-16 Intelligent pillow control method and system with sleep aiding function and readable storage medium

Publications (2)

Publication Number Publication Date
CN114587281A CN114587281A (en) 2022-06-07
CN114587281B true CN114587281B (en) 2023-12-12

Family

ID=81818236

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210257770.9A Active CN114587281B (en) 2022-03-16 2022-03-16 Intelligent pillow control method and system with sleep aiding function and readable storage medium

Country Status (1)

Country Link
CN (1) CN114587281B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114917451A (en) * 2022-06-09 2022-08-19 北京清霆科技有限公司 Sleep aiding method and system based on real-time measurement signals
CN115577266B (en) * 2022-11-25 2023-05-16 深圳市警泰欣科技有限公司 Intelligent control method and system for action constraint device

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104873040A (en) * 2015-04-28 2015-09-02 北京乐动卓越科技有限公司 Sleep adjusting method and system and intelligent pillow
CN105559461A (en) * 2016-01-19 2016-05-11 杨坤 Modularized intelligent pillow system
CN109084432A (en) * 2018-08-20 2018-12-25 广东美的暖通设备有限公司 The regulation method and air conditioner of sleep environment
CN113171112A (en) * 2021-04-12 2021-07-27 杭州云睡吧健康管理有限公司 Pillow height adjusting system with database and method for establishing database
CN113332560A (en) * 2021-05-21 2021-09-03 苏州声动医疗科技有限公司 Pillow with elastic pillow body
CN113368365A (en) * 2021-05-21 2021-09-10 苏州声动医疗科技有限公司 Sound vibration regulation and control equipment and method for brain function monitoring, headrest and head-mounted equipment

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
HK1197625A2 (en) * 2014-10-06 2015-01-30 Ho David Sai Wah An automatic cervical vertebrae balancing device for sleeping

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104873040A (en) * 2015-04-28 2015-09-02 北京乐动卓越科技有限公司 Sleep adjusting method and system and intelligent pillow
CN105559461A (en) * 2016-01-19 2016-05-11 杨坤 Modularized intelligent pillow system
CN109084432A (en) * 2018-08-20 2018-12-25 广东美的暖通设备有限公司 The regulation method and air conditioner of sleep environment
CN113171112A (en) * 2021-04-12 2021-07-27 杭州云睡吧健康管理有限公司 Pillow height adjusting system with database and method for establishing database
CN113332560A (en) * 2021-05-21 2021-09-03 苏州声动医疗科技有限公司 Pillow with elastic pillow body
CN113368365A (en) * 2021-05-21 2021-09-10 苏州声动医疗科技有限公司 Sound vibration regulation and control equipment and method for brain function monitoring, headrest and head-mounted equipment

Also Published As

Publication number Publication date
CN114587281A (en) 2022-06-07

Similar Documents

Publication Publication Date Title
CN114587281B (en) Intelligent pillow control method and system with sleep aiding function and readable storage medium
KR102057463B1 (en) Device for controlling sleeping environment using reinforcement learning
CN116705337B (en) Health data acquisition and intelligent analysis method
CN111657890A (en) Sleep state monitoring method and device, intelligent mattress and medium
CN114065059B (en) Sleep posture recommendation control method and system based on big data and storage medium
CN104864558A (en) Air conditioner control method, device and terminal
CN105045898B (en) A kind of dynamically personalized song recommendations system and method based on brain wave earphone
KR102015097B1 (en) Apparatus and computer readable recorder medium stored program for recognizing emotion using biometric data
CN110706816A (en) Method and equipment for regulating sleep environment based on artificial intelligence
CN108375909A (en) A kind of parameters analysis method, device, equipment and computer readable storage medium
Tian et al. EEG-based emotion recognition of deaf subjects by integrated genetic firefly algorithm
Thatte et al. Optimal time-resource allocation for energy-efficient physical activity detection
CN115662631B (en) Nursing home management system based on AI intelligent discrimination
WO2021134250A1 (en) Emotion management method and device, and computer-readable storage medium
CN109242089B (en) Progressive supervised deep learning neural network training method, system, medium and device
JP2023089729A (en) Computer system and emotion estimation method
JP6213983B2 (en) Sleep stage estimation apparatus and method, and program
CN113854777A (en) Cloud-based multifunctional inflatable mattress and interaction method thereof
CN110313922A (en) A kind of pressure regulating method, pressure regulating system and terminal
KR101462748B1 (en) Method for clustering health-information
CN114711720B (en) Intelligent sleep-aiding mattress control method and system based on big data and readable storage medium
CN114664439A (en) Abnormality detection method, abnormality detection device, and storage medium
CN112735563A (en) Recommendation information generation method and device and processor
CN117017295A (en) Pressure analysis relieving method and device based on sleep monitoring and computer equipment
CN116189895A (en) Control method and device of health detection equipment, computer equipment and storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant