CN114588471A - Intelligent sleep assisting system, sleep state classification method and storage medium - Google Patents

Intelligent sleep assisting system, sleep state classification method and storage medium Download PDF

Info

Publication number
CN114588471A
CN114588471A CN202210311325.6A CN202210311325A CN114588471A CN 114588471 A CN114588471 A CN 114588471A CN 202210311325 A CN202210311325 A CN 202210311325A CN 114588471 A CN114588471 A CN 114588471A
Authority
CN
China
Prior art keywords
sleep
data
intelligent
temperature
humidity
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.)
Pending
Application number
CN202210311325.6A
Other languages
Chinese (zh)
Inventor
陈言璞
陈龙
黄茜
钟学洋
王海晖
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.)
Wuhan Institute of Technology
Original Assignee
Wuhan Institute of Technology
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 Wuhan Institute of Technology filed Critical Wuhan Institute of Technology
Priority to CN202210311325.6A priority Critical patent/CN114588471A/en
Publication of CN114588471A publication Critical patent/CN114588471A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • 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
    • 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
    • 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
    • A61B5/48—Other medical applications
    • A61B5/4803—Speech analysis specially adapted for diagnostic purposes
    • 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
    • A61B5/4812—Detecting sleep stages or cycles
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
    • A61F5/00—Orthopaedic methods or devices for non-surgical treatment of bones or joints; Nursing devices; Anti-rape devices
    • A61F5/56—Devices for preventing snoring
    • 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
    • A61M2021/0022—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 tactile sense, e.g. vibrations
    • 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
    • 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
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Physics & Mathematics (AREA)
  • Veterinary Medicine (AREA)
  • Public Health (AREA)
  • General Health & Medical Sciences (AREA)
  • Animal Behavior & Ethology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Pathology (AREA)
  • Biophysics (AREA)
  • Artificial Intelligence (AREA)
  • Physiology (AREA)
  • Cardiology (AREA)
  • Anesthesiology (AREA)
  • Pain & Pain Management (AREA)
  • Psychology (AREA)
  • Hematology (AREA)
  • Otolaryngology (AREA)
  • Pulmonology (AREA)
  • Nursing (AREA)
  • Orthopedic Medicine & Surgery (AREA)
  • Vascular Medicine (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Acoustics & Sound (AREA)
  • Evolutionary Computation (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Psychiatry (AREA)
  • Signal Processing (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

The invention relates to an intelligent sleep auxiliary system, a sleep state classification method and a storage medium, wherein the system comprises: the sleep assisting device, the cloud server and the mobile terminal are in communication connection; the sleep assisting device is used for collecting sleep data and controlling the adjustment of the device corresponding to the sleep data based on the sleep data; the cloud server is used for monitoring the sleep data and inputting the sleep data into a trained support vector machine model to obtain a sleep classification result; the mobile terminal is used for receiving and displaying the sleep classification result. The invention can monitor the sleep quality and intervene the sleep, thereby improving the sleep quality of the user.

Description

Intelligent sleep assisting system, sleep state classification method and storage medium
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an intelligent sleep auxiliary system and a sleep state identification method which are combined with biology and computer science.
Background
With the improvement of consumption level and life quality in a new era, more and more people play entertainment by depending on electronic intelligent equipment in leisure time, and due to the increase of the entertainment time, the sleep time is reduced, and the importance of sleep in the growth process is ignored. The harm of sleep disorder to young people is not only physical, but also serious, and can endanger the mind, causing psychological diseases.
As early as 1937, the american scholars Loomis et al first proposed a sleep depth determination based on brain waves. In 1968, the judgment criteria of sleep stages were described in detail by Rechtschschschchaffen and Kales who used in the Polysomnography (PSG) system and are the internationally accepted standard for diagnosing sleep apnea hypopnea syndrome. However, PSG can only be used as a monitoring system, and cannot help patients with sleep disorder to effectively solve insomnia symptoms, and the PSG is expensive in price; the sleep health field is rapidly developed in the years in China, and a large number of sleep auxiliary systems, such as a small sleep mode which is typical of software and a millet bracelet which is typical of hardware, emerge from the market at present. The minor sleep is a white noise small program designed for the sleep disorder patient, which helps the user fall asleep by playing the built-in white noise audio, but does not give effective sleep advice to the user. The millet bracelet describes deep sleep time through brain wave scanning and eye movement observation, but the millet bracelet is used as a sleep monitoring system and cannot interfere in sleep of a user.
Therefore, how to design a sleep assisting system which can monitor the sleep quality and give sleep intervention is an urgent problem to be solved.
Disclosure of Invention
In view of the above, there is a need to provide an intelligent sleep assisting system and a sleep state identification method, which can monitor the sleep quality and provide sleep intervention function during the sleep process.
In order to achieve the above object, in a first aspect, the present invention provides an intelligent sleep assistance system, comprising: the sleep assisting device, the cloud server and the mobile terminal are in communication connection;
the sleep auxiliary equipment is used for acquiring sleep data and controlling equipment corresponding to the sleep data to adjust based on the sleep data;
the cloud server is used for monitoring the sleep data and inputting the sleep data into a trained support vector machine model to obtain a sleep classification result;
the mobile terminal is used for receiving and displaying the sleep classification result.
Optionally, the sleep data includes user voice data; the sleep aid comprises a controller, a sound sensor and an air bag;
the sound sensor is used for collecting user voice data in a sleep environment;
the controller is used for controlling the air bag to increase or decrease the inflating quantity when the user voice data comprises voice data with preset frequency.
Optionally, the sleep data includes external voice data; the sleep assisting device comprises a microphone, a controller and a loudspeaker;
the microphone is used for collecting external voice data in a sleep environment;
the controller is used for controlling the loudspeaker to play white noise audio when the decibel of the external voice data is larger than a preset decibel.
Optionally, the sleep data includes temperature and humidity data; the sleep auxiliary equipment comprises a temperature and humidity sensor, a controller and a temperature and humidity regulator;
the temperature and humidity sensor is used for collecting temperature and humidity data in a sleep environment;
the controller is used for controlling the temperature and humidity regulator to regulate the temperature and humidity in the sleeping environment when the temperature and humidity data are not in a preset temperature and humidity range.
Optionally, the sleep data comprises BCG signals; the sleep assisting device comprises a piezoelectric film sensor, wherein the piezoelectric film sensor is used for collecting BCG signals of a user;
the trained support vector machine model comprises an optimal support vector machine model trained using samples in an MIT-BIH database; the cloud server is specifically configured to:
separating and extracting a heartbeat interval sequence from the BCG signal;
extracting time domain features of the heartbeat interval sequence, and extracting frequency domain features of the heartbeat interval sequence by adopting a time-varying autoregressive model to form a first feature matrix;
performing dimensionality reduction on the first feature matrix by adopting a principal component analysis method to obtain a second feature matrix;
and inputting the second feature matrix into the optimal support vector machine model, and outputting sleep classification results of the rapid eye movement sleep period, the shallow sleep period and the deep sleep period of the user.
Optionally, the mobile terminal is further configured to set a sleep parameter, where the sleep parameter includes sleep start time;
the sleep assisting device comprises a vibration module, and the vibration module is used for vibrating during the sleep starting time.
Optionally, the sleep assisting apparatus further includes: an anion generator for releasing anions.
Optionally, the sleep assisting apparatus further includes: a pulse heart rate sensor for detecting a heart rate of a user.
In a second aspect, the present invention further provides a sleep state classification method, including:
acquiring sleep data through sleep auxiliary equipment, and controlling equipment corresponding to the sleep data to adjust based on the sleep data;
monitoring the sleep data through a cloud server, and inputting the sleep data into a trained support vector machine model to obtain a sleep state classification result;
and receiving and displaying the sleep state classification result through the mobile terminal.
In a third aspect, the present invention also provides a computer storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements the functions in the intelligent sleep assistance system as described.
The beneficial effects of adopting the above embodiment are: according to the invention, the sleep auxiliary equipment is used for acquiring sleep data, equipment corresponding to the sleep data is controlled to adjust based on the sleep data, and the sleep quality of a user is improved by intervening the sleep process of the user; then, the sleep data are input into the trained support vector machine model through the cloud server to obtain a sleep state classification result, and the result is checked at the mobile terminal, so that the user can clearly know the sleep state of the user through accurate sleep monitoring, and the pertinence of the user is improved according to the sleep state of the user; and finally, the cooperative cooperation of all the functional modules is completed by adopting a sleep auxiliary device, a cloud server and a cloud architecture mode of the mobile terminal, so that the transmission integration of the information is more efficient than that of the traditional mode.
Drawings
FIG. 1 is an overall architecture diagram of an embodiment of an intelligent sleep assistance system provided by the present invention;
FIG. 2 is a hardware block diagram of an embodiment of an intelligent sleep aid provided in the present invention;
fig. 3 is a schematic structural diagram of a cloud server according to an embodiment of the present invention;
fig. 4 is a communication flow chart of an embodiment of a mobile terminal and a cloud server provided in the present invention;
FIG. 5 is a flowchart of an algorithm of an embodiment of the support vector machine provided by the present invention;
fig. 6 is a flowchart of a sleep state classification method according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form a part hereof, and which together with the embodiments of the invention serve to explain the principles of the invention and not to limit its scope.
In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise. Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The invention provides an intelligent sleep assisting system, a sleep state classifying method and a storage medium, which are respectively explained below.
Referring to fig. 1, fig. 1 is an overall architecture diagram of an embodiment of an intelligent sleep assistance system provided in the present invention. One embodiment of the present invention discloses an intelligent sleep aid system, comprising: the sleep assisting apparatus 10, the cloud server 20 and the mobile terminal 30 are in communication connection; the sleep assisting device 10 is used for acquiring sleep data and controlling devices corresponding to the sleep data to adjust based on the sleep data; the cloud server 20 is configured to monitor sleep data, and input the sleep data into the trained support vector machine model to obtain a sleep classification result; the mobile terminal 30 is used for receiving and displaying the sleep classification result.
As shown in fig. 1, the present invention adopts a cloud architecture mode to complete the cooperative cooperation of each functional module, wherein Socket (Socket) is used for data communication to realize the communication between the sleep assisting apparatus 10 and the cloud server 20, and the mobile terminal 30 interacts with the cloud server 20 mainly through HTTP protocol.
It should be noted that the hardware architecture of the sleep assisting apparatus 10 is designed with STM32 as the core, and has functions of collecting, processing, displaying and transmitting multiple data,
referring to fig. 2, fig. 2 is a hardware structure diagram of an embodiment of an intelligent sleep assisting apparatus provided in the present invention. The system mainly comprises a power module 101, a sensor module 102 (including various sensors), a signal conditioning (module) 103 and a micro control unit 104, wherein the micro control unit 104 is a system with minimum SOC, and specifically comprises an I/O (module) 1041, a serial port unit 1042, a wireless module 1043, a key module 1044, a clock module 1045, a display module 1046, a storage module 1047 and a debugging unit 1048.
The STM32 minimum system mainly comprises a power supply circuit, a program downloading and debugging circuit, a crystal oscillator circuit, a reset circuit and the like, wherein the crystal oscillator circuit comprises a passive crystal oscillator of 8MHz, a corresponding matching capacitor and a corresponding resistor, a plurality of clock sources are contained in the crystal oscillator circuit to serve as a system clock, the clock sources can be selected through software, and meanwhile, STM32 supports software downloading and debugging in JTAG and SWD modes. A plurality of modules can be expanded in a minimum system, and the embedded requirement of easy clipping is met. There are many kinds of signals at the signal acquisition end, and the distribution of pins and the design of circuits need to be made.
It can be understood that the sleep assisting device can collect sleep data of the user in a sleep environment through various sensors included in the sleep assisting device, and then control the device corresponding to the sleep data by using the control module in the sleep assisting device based on the sleep data, so that the effect of adjusting the sleep data is achieved, and the sleep of the user is guaranteed by interfering the sleep process.
The cloud server 20 in the present invention adopts a hierarchical and structured design concept in software. Please refer to fig. 3, in which the software is decomposed into a plurality of functional modules, and fig. 3 is a schematic structural diagram of a cloud server according to an embodiment of the present invention. The cloud server 20 includes a data communication module 201, a data storage module 202, and a data processing module 203.
In the data communication module 201, data interaction between the cloud server and the sleep aid is realized by continuously monitoring sleep data from the sleep aid, specifically, sleep data sent to the cloud server by the piezoelectric film sensor after noise elimination by using a Socket program. And then, the data are simply processed and then stored in a database, so that the communication between the mobile terminal and the cloud server is facilitated.
In the data storage module 202, a cloud database is used to store the identity information of the user and some sleep parameters of the user: such as sleep duration, etc.
In the data processing module 203, the cloud server is configured to monitor sleep data, and input the sleep data into the trained support vector machine model to obtain a sleep classification result.
The mobile terminal 30 is used for receiving and displaying the sleep classification result. Referring to fig. 4, fig. 4 is a communication flow chart of an embodiment of a mobile terminal and a cloud server provided in the present invention.
Step S401: the mobile terminal sends a data request to a cloud server through an HTTP (hyper text transport protocol);
step S402: the cloud server encapsulates the data requested by the mobile terminal into a JSON format, and then responds to the mobile terminal through an HTTP (hyper text transport protocol);
step S403: and the mobile terminal analyzes the received JSON format data and then displays the data on a webpage.
In addition, the mobile terminal 30 may also complete setting of sleep parameters and obtaining of monitored sleep parameters of the user.
According to the invention, the sleep auxiliary equipment is used for acquiring sleep data, equipment corresponding to the sleep data is controlled to adjust based on the sleep data, and the sleep quality of a user is improved by intervening the sleep process of the user; then, the cloud server inputs the sleep data into the trained support vector machine model to obtain a sleep state classification result, and the result is checked at the mobile terminal, so that the user can clearly know the sleep state of the user through accurate sleep monitoring, and the targeted improvement can be made on the sleep state of the user; and finally, the cooperative cooperation of all the functional modules is completed by adopting a sleep auxiliary device, a cloud server and a cloud architecture mode of the mobile terminal, so that the transmission integration of the information is more efficient than that of the traditional mode.
In one embodiment of the invention, the sleep data includes user voice data; the sleep assisting device comprises a controller, a sound sensor and an air bag;
the sound sensor is used for collecting user voice data in a sleep environment;
the controller is used for controlling the air bag to increase or decrease the inflation quantity when the user voice data comprises the voice data with the preset frequency.
It is understood that, after the user goes to sleep, if voice data of a specific frequency, such as snoring, is detected by the sound sensor, the sleep aid can slowly adjust the height of the sleeper's pillow, changing the neck position. Wherein, the sleep auxiliary device can be embedded in the pillow, and the sleep auxiliary device can also be used as the pillow of the sleeper. Specifically, the stress and the bending degree of the neck of the human body are reduced by controlling the inflation quantity in the air bags, namely, quantitative inflation and deflation operations are performed on the single air bag close to the neck of the human body in the pillow, so that the bending of the neck is stretched, the stress of the neck is reduced, the muscles of the throat are relaxed, a breathing passage is opened, the snoring is stopped finally, and the sleeping of a user is ensured by intervening the sleeping process.
In one embodiment of the invention, the sleep data includes external voice data; the sleep auxiliary equipment comprises a microphone, a controller and a loudspeaker;
the microphone is used for acquiring external voice data in a sleep environment;
the controller is used for controlling the loudspeaker to play white noise audio when the decibel of the external voice data is larger than the preset decibel.
The sleep auxiliary equipment is provided with an ISD1820 loudspeaker module for playing white noise. When the noise of the external voice data detected by a microphone in the sleep assisting device is more than 50 decibels, a data request is made to the server, and white noise audio stored in the server in advance is played to offset the external noise, so that the sleep assisting device assists a user to sleep.
In one embodiment of the invention, the sleep data includes temperature and humidity data; the sleep assisting device comprises a temperature and humidity sensor; the sleep auxiliary equipment comprises a temperature and humidity sensor, a controller and a temperature and humidity regulator;
the temperature and humidity sensor is used for collecting temperature and humidity data in a sleep environment;
the controller is used for controlling the temperature and humidity regulator to regulate the temperature and humidity in the sleep environment by the sleep auxiliary equipment when the temperature and humidity data are not in the preset temperature and humidity range.
It can be understood that human beings are very sensitive to the temperature and humidity environment of sleep, and are the most ideal sleep conditions when the indoor temperature is 20 ℃ -23 ℃, if the temperature is lower than the threshold value, the people can not sleep easily due to cold, and if the temperature exceeds 23 ℃, the people can not sleep easily due to the worries caused by heat. The sleep auxiliary equipment is provided with a DHT11 temperature and humidity sensor for monitoring the temperature and humidity conditions of the sleep environment. When the current temperature is not within the set temperature range, the sleep auxiliary equipment can control a temperature and humidity regulator, such as a fan, an air conditioner and the like, to regulate and control the temperature and the humidity in the sleep environment.
In addition, the temperature and humidity sensor can convert the acquired analog signals into corresponding digital signals to be recorded in a cloud database, and the intelligent sleep auxiliary system can acquire temperature and humidity signals of the current environment through the database to be interconnected with the intelligent household equipment, so that the temperature and humidity can be intelligently adjusted.
In one embodiment of the present invention, the sleep assistance apparatus further comprises: the negative ion generator is used for releasing negative ions.
It can be understood that the anion generator can release anions to purify the air in the sleeping environment, so that the good air quality in the sleeping environment can be maintained.
In one embodiment of the present invention, the sleep assistance apparatus further comprises: the pulse heart rate sensor is used for detecting the heartbeat frequency of the user.
The heartbeat frequency is detected through the pulse heart rate sensor, the data of the light sleep time and the deep sleep time are analyzed according to the time-frequency domain data of the frequency threshold value, the data are recorded and displayed on the mobile terminal, signal basis is provided for realizing other functions, and the user can conveniently check the data at the mobile terminal.
In an embodiment of the present invention, the mobile terminal is further configured to set a sleep parameter, where the sleep parameter includes a sleep on time; the sleep assisting device comprises a vibration module which is used for vibrating during sleep starting time.
It can be understood that, because the structures in the intelligent sleep system of the invention are in communication connection, the sleep parameters set in the mobile terminal can also control the sleep auxiliary equipment, for example, the sleep start time is set in the mobile terminal, which is equivalent to embedding an "alarm clock" in the sleep auxiliary equipment, according to the alarm clock time set at the mobile terminal, the sleep auxiliary equipment embedded in the pillow or the sleep auxiliary equipment of the pillow itself controls the slight vibration of the vibration module until the head leaves the pillow, so as to prevent the sleep from going to sleep again, and because of the design of vibration inside the pillow, the invention can not affect another person in the same bed, thereby ensuring the sleep quality.
The sleep auxiliary equipment is used for acquiring sleep data, controlling equipment corresponding to the sleep data to adjust based on the sleep data, and intervening the sleep process of the user to improve the sleep quality of the user.
In one embodiment of the present invention, the sleep data includes BCG signals, and the sleep aid includes a piezoelectric film sensor for collecting the BCG signals of the user; the trained support vector machine model comprises an optimal support vector machine model trained using samples in the MIT-BIH database.
Referring to fig. 5, fig. 5 is a flowchart illustrating an algorithm of an embodiment of a support vector machine according to the present invention. The support vector machine sleep staging algorithm takes a rapid eye movement sleep period, a shallow sleep period and a deep sleep period of a sleep stage as items to be classified.
Step S501: separating and extracting a heartbeat interval sequence from the BCG signal;
step S502: extracting time domain characteristics of the heart jump interval sequence, and extracting frequency domain characteristics of the heart jump interval sequence by adopting a time-varying autoregressive model to form a first characteristic matrix;
step S503: performing dimensionality reduction on the first feature matrix by adopting a principal component analysis method to obtain a second feature matrix;
step S504: and inputting the second characteristic matrix into the optimal support vector machine model, and outputting sleep classification results of the rapid eye movement sleep period, the shallow sleep period and the deep sleep period of the user.
It will be appreciated that during the training phase, the optimal support vector machine model is obtained by training using samples in the MIT-BIH database, which is a database provided by the national institute of technology, Massachusetts, Inc. for studying arrhythmias. Specifically, firstly, an electrocardio-RR sequence is extracted from an MIT-BIH database, then the electrocardio-RR sequence is subjected to time domain feature extraction and main component analysis dimensionality reduction, input into an initial support vector machine model for training, and parameter optimization is carried out by using a genetic algorithm, so that the model is converged, two models, namely a support vector machine model with six classifications in sleep stages and a support vector machine model with four classifications in sleep stages, are obtained, then the classification accuracy of the two support vector machines is obtained by respectively testing the two support vector machines, the support vector machine model with high accuracy is selected as an optimal support vector machine model, and model training is completed.
In the prediction stage, acquiring a BCG signal acquired from the piezoelectric film sensor, namely a ballistocardiogram signal, then carrying out noise reduction on the BCG signal and separating and extracting a heartbeat interval sequence from the noise-reduced BCG signal; extracting time domain characteristics of the heart jump interval sequence, and extracting frequency domain characteristics of the heart jump interval sequence by adopting a time-varying autoregressive model to form a first characteristic matrix; performing dimensionality reduction on the first feature matrix by adopting a principal component analysis method to obtain a second feature matrix; and inputting the second characteristic matrix into the trained optimal support vector machine model, and outputting sleep classification results of the rapid eye movement sleep period, the shallow sleep period and the deep sleep period of the user.
The invention provides an intelligent sleep auxiliary system based on a support vector machine, which aims to connect sensors, controllers, equipment, users, objects and the like together in a new way by using communication technologies such as a local network or the Internet and the like to form a network for people, objects and the like to realize informatization, remote management control and intellectualization, and is applied to the sleep auxiliary system to connect the users, hardware equipment and a webpage end through the Internet of things, so that data generated by the users in the sleep process can be quickly and efficiently transmitted to the hardware equipment through wifi, and the hardware equipment processes the data and displays an analysis result on a page, thereby being convenient and fast.
Compared with the prior art, the sleep assisting platform has a convenient and efficient design mode, the sleep assisting platform is not only applied to hospitals, but also can be moved into thousands of households, and patients with sleep disorder can experience the convenience brought to the hospitals; the accurate sleep monitoring can lead the user to clearly know the sleep condition of the user, make targeted improvement aiming at the sleep condition of the user, and help the user to solve a series of problems such as difficult sleep, snoring and the like through effective sleep assistance, so that the sleep quality of the user is ensured; and the cloud architecture mode is adopted to complete the cooperative cooperation of all the functional modules, so that the transmission and integration of the information are more efficient than the traditional mode.
Referring to fig. 6, fig. 6 is a flowchart illustrating a sleep state classification method according to an embodiment of the sleep state classification method provided by the present invention, including:
step S601: the sleep assisting device collects sleep data and controls adjustment of a device corresponding to the sleep data based on the sleep data;
step S602: the cloud server monitors sleep data, and inputs the sleep data into the trained support vector machine model to obtain a sleep state classification result;
step S603: and the mobile terminal receives and displays the sleep state classification result.
Here, it should be noted that: the sleep state classification method provided in the foregoing embodiments may implement the technical solutions described in the foregoing system embodiments, and details are not described here.
Based on the foregoing intelligent sleep assistance system, embodiments of the present invention also provide a computer-readable storage medium, where one or more programs are stored, and the one or more programs are executable by one or more processors to implement the functions in the intelligent sleep assistance system in the foregoing embodiments.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.

Claims (10)

1. An intelligent sleep assistance system, comprising: the sleep assisting device, the cloud server and the mobile terminal are in communication connection;
the sleep auxiliary equipment is used for acquiring sleep data and controlling equipment corresponding to the sleep data to adjust based on the sleep data;
the cloud server is used for monitoring the sleep data and inputting the sleep data into a trained support vector machine model to obtain a sleep classification result;
the mobile terminal is used for receiving and displaying the sleep classification result.
2. The intelligent sleep assistance system of claim 1 wherein the sleep data comprises user voice data; the sleep aid comprises a controller, a sound sensor and an air bag;
the sound sensor is used for collecting user voice data in a sleep environment;
the controller is used for controlling the air bag to increase or decrease the inflating quantity when the user voice data comprises voice data with preset frequency.
3. The intelligent sleep assistance system as claimed in claim 1, wherein the sleep data comprises external voice data; the sleep assisting device comprises a microphone, a controller and a loudspeaker;
the microphone is used for collecting external voice data in a sleep environment;
the controller is used for controlling the loudspeaker to play white noise audio when the decibel of the external voice data is larger than a preset decibel.
4. The intelligent sleep assistance system of claim 1 wherein the sleep data comprises temperature and humidity data; the sleep auxiliary equipment comprises a temperature and humidity sensor, a controller and a temperature and humidity regulator;
the temperature and humidity sensor is used for collecting temperature and humidity data in a sleep environment;
the controller is used for controlling the temperature and humidity regulator to regulate the temperature and humidity in the sleeping environment when the temperature and humidity data are not in a preset temperature and humidity range.
5. The intelligent sleep assistance system of claim 1 wherein the sleep data comprises BCG signals; the sleep assisting device comprises a piezoelectric film sensor, wherein the piezoelectric film sensor is used for collecting BCG signals of a user;
the trained support vector machine model comprises an optimal support vector machine model trained with samples in an MIT-BIH database; the cloud server is specifically configured to:
separating and extracting a heartbeat interval sequence from the BCG signal;
extracting time domain features of the heartbeat interval sequence, and extracting frequency domain features of the heartbeat interval sequence by adopting a time-varying autoregressive model to form a first feature matrix;
performing dimensionality reduction on the first feature matrix by adopting a principal component analysis method to obtain a second feature matrix;
and inputting the second feature matrix into the optimal support vector machine model, and outputting sleep classification results of the rapid eye movement sleep period, the shallow sleep period and the deep sleep period of the user.
6. The intelligent sleep assistance system according to claim 1, wherein the mobile terminal is further configured to set sleep parameters, the sleep parameters including sleep on time;
the sleep assisting device comprises a vibration module, and the vibration module is used for vibrating during the sleep starting time.
7. The intelligent sleep assistance system of claim 1 wherein the sleep assistance device further comprises: an anion generator for releasing anions.
8. The intelligent sleep assistance system of claim 1 wherein the sleep assistance device further comprises: a pulse heart rate sensor for detecting a heart rate of a user.
9. A sleep state classification method based on the intelligent sleep assistance system of any one of claims 1 to 8, comprising:
acquiring sleep data through sleep auxiliary equipment, and controlling equipment corresponding to the sleep data to adjust based on the sleep data;
monitoring the sleep data through a cloud server, and inputting the sleep data into a trained support vector machine model to obtain a sleep state classification result;
and receiving and displaying the sleep state classification result through the mobile terminal.
10. A computer-readable storage medium for storing a computer-readable program or instructions, which when executed by a processor, is capable of implementing the functions of the intelligent sleep assistance system of any one of the preceding claims 1 to 8.
CN202210311325.6A 2022-03-28 2022-03-28 Intelligent sleep assisting system, sleep state classification method and storage medium Pending CN114588471A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210311325.6A CN114588471A (en) 2022-03-28 2022-03-28 Intelligent sleep assisting system, sleep state classification method and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210311325.6A CN114588471A (en) 2022-03-28 2022-03-28 Intelligent sleep assisting system, sleep state classification method and storage medium

Publications (1)

Publication Number Publication Date
CN114588471A true CN114588471A (en) 2022-06-07

Family

ID=81819018

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210311325.6A Pending CN114588471A (en) 2022-03-28 2022-03-28 Intelligent sleep assisting system, sleep state classification method and storage medium

Country Status (1)

Country Link
CN (1) CN114588471A (en)

Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103584840A (en) * 2013-11-25 2014-02-19 天津大学 Automatic sleep stage method based on electroencephalogram, heart rate variability and coherence between electroencephalogram and heart rate variability
CN106419869A (en) * 2016-08-24 2017-02-22 电子科技大学 Real-time sleep staging detection method based on piezoelectric sensor and device for realizing method
CN108937865A (en) * 2018-06-28 2018-12-07 重庆邮电大学 A kind of wisdom sleep monitor system based on cloud framework
CN109044272A (en) * 2018-07-20 2018-12-21 渝新智能科技（上海）有限公司 Sleep state monitoring and sleep environment parameter regulation method, system and terminal device
CN110368173A (en) * 2019-08-27 2019-10-25 东南大学 Sleep apnea syndrome based on sound of snoring identification assists in the treatment of pillow
CN110742585A (en) * 2019-10-10 2020-02-04 北京邮电大学 Sleep staging method based on BCG (BCG-broadcast) signals
CN110811563A (en) * 2019-12-04 2020-02-21 佛山职业技术学院 Wearable sleep quality monitoring device
CN111631697A (en) * 2020-06-15 2020-09-08 电子科技大学 Intelligent sleep and fatigue state information monitoring control system and method and monitor
CN111685731A (en) * 2020-05-19 2020-09-22 珠海格力电器股份有限公司 Sleep data processing method, device, equipment and storage medium
CN112022134A (en) * 2020-07-22 2020-12-04 无锡金童科技有限公司 Heartbeat detection method based on ballistocardiogram
CN113925496A (en) * 2021-10-20 2022-01-14 中国人民解放军海军特色医学中心 Fatigue sleep analysis method and device
CN114129853A (en) * 2021-11-25 2022-03-04 深圳市奥尔智慧健康有限公司 Intelligent control system of white noise sleep instrument

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103584840A (en) * 2013-11-25 2014-02-19 天津大学 Automatic sleep stage method based on electroencephalogram, heart rate variability and coherence between electroencephalogram and heart rate variability
CN106419869A (en) * 2016-08-24 2017-02-22 电子科技大学 Real-time sleep staging detection method based on piezoelectric sensor and device for realizing method
CN108937865A (en) * 2018-06-28 2018-12-07 重庆邮电大学 A kind of wisdom sleep monitor system based on cloud framework
CN109044272A (en) * 2018-07-20 2018-12-21 渝新智能科技（上海）有限公司 Sleep state monitoring and sleep environment parameter regulation method, system and terminal device
CN110368173A (en) * 2019-08-27 2019-10-25 东南大学 Sleep apnea syndrome based on sound of snoring identification assists in the treatment of pillow
CN110742585A (en) * 2019-10-10 2020-02-04 北京邮电大学 Sleep staging method based on BCG (BCG-broadcast) signals
CN110811563A (en) * 2019-12-04 2020-02-21 佛山职业技术学院 Wearable sleep quality monitoring device
CN111685731A (en) * 2020-05-19 2020-09-22 珠海格力电器股份有限公司 Sleep data processing method, device, equipment and storage medium
CN111631697A (en) * 2020-06-15 2020-09-08 电子科技大学 Intelligent sleep and fatigue state information monitoring control system and method and monitor
CN112022134A (en) * 2020-07-22 2020-12-04 无锡金童科技有限公司 Heartbeat detection method based on ballistocardiogram
CN113925496A (en) * 2021-10-20 2022-01-14 中国人民解放军海军特色医学中心 Fatigue sleep analysis method and device
CN114129853A (en) * 2021-11-25 2022-03-04 深圳市奥尔智慧健康有限公司 Intelligent control system of white noise sleep instrument

Similar Documents

Publication Publication Date Title
CN109936999B (en) Sleep assessment using a home sleep system
CN108310587B (en) Sleep control device and method
CN105592881B (en) System and method for determining the timing of the stimulus to the sense organ during sleep
US10685577B2 (en) Systems and methods for delivering sensory input during a dream state
CN108419096B (en) Intelligent voice playing method and system
CN109936997A (en) Sleep system
CN109937010A (en) Sleep quality scoring and improvement
CN105377129A (en) Adjustment of sensory stimulation intensity to enhance sleep slow wave activity
EP1886707A1 (en) Sleep enhancing device
CN106488740A (en) System and method for adjusting the intensity of the sensory stimuli of during sleeping based on sleep spindle
CN116328142A (en) Method and system for sleep management
CN1882372A (en) Sleep guidance system and related methods
CN104257381A (en) Voice frequency sleep assisting device based on brain wave signals
CN107875496A (en) A kind of intelligent sleep management eye-shade device and its control method
CN107466241A (en) Sensory stimuli is provided based on the slow wave cycle
CN115813146A (en) Intelligent body sensing sound wave physiotherapy mattress and use method thereof
CN112717253A (en) Acousto-optic combined awakening device based on brain wave monitoring
WO2021027593A1 (en) Automobile control method and apparatus based on electroencephalogram data, and storage medium
KR101319917B1 (en) Method, system for sound sleep using born connection pillow
CN107823775B (en) Sleep aiding method and sleep aiding pillow
JP7296626B2 (en) Information processing device and program
CN114588471A (en) Intelligent sleep assisting system, sleep state classification method and storage medium
CN108399061A (en) The control method and system of playout of voice
CN207477310U (en) Pillow
US11707596B2 (en) Method and system to deliver timed and grouped sensory stimulation

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