CN113599053A - Self-adaptive adjustment method and system of air bag pillow and computer program - Google Patents
Self-adaptive adjustment method and system of air bag pillow and computer program Download PDFInfo
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Abstract
The invention discloses a self-adaptive adjustment method of an air bag pillow, which comprises the steps of detecting snore events of a user in a sleep cycle, identifying whether snore exists or not, measuring the volume of the snore, and storing whether the snore exists or not and the measured volume of the snore into a sleep parameter database as snore audio data; responding to the latest snore audio data and carrying out self-adaptive adjustment on at least one air bag in the air bag pillow according to the data stored in the sleep parameter database so as to change the air pressure of the air bag until a sleep end event occurs or the snore disappears or reaches the minimum. The invention can accurately judge the snoring state of the user in real time, slowly adjust the height of the pillow by self-adaptive air bag inflation/deflation, intervene the snoring sound on the premise of not interfering deep sleep and relieve the snoring symptom of the user. Corresponding systems and computer programs are also disclosed.
Description
Technical Field
The invention relates to the field of smart home and healthy sleep, in particular to an adjusting method, an adjusting system and a computer program for an adjustable air bag pillow.
Background
Snoring is a ubiquitous sleep phenomenon, and according to incomplete statistics, two nearly adult groups in China have the snoring phenomenon. The patient with serious snoring can cause the phenomenon of apnea in the sleeping process to affect the sleeping quality, and the snoring easily causes cerebral blood hypoxia, induces various cardiovascular and cerebrovascular diseases and seriously affects the body health. In the prior art, a sleep intervention device and an intervention method exist, which can intervene in snoring of a user by adjusting the body of the user, so that the snoring condition of the user is relieved to a certain extent.
For example, chinese patent No. CN108742518B discloses a snoring detection and intervention method and system based on an intelligent pillow, which collects audio through a sensor, determines the snoring state of a user, and then reminds the user of changing the sleeping posture through electromagnetic waves and vibrations, so as to intervene snoring. Chinese patent application No. CN211674823U discloses a snoring intervention device, which performs snoring intervention by using a motor to push a user to turn over after recognizing the snoring of the user. The two snore intervention methods force the user to change the sleeping position through external stimulation or force, thereby playing the effect of snore intervention, interfering the sleeping of the user and reducing the sleeping quality of the user.
Chinese patent application No. CN108697528B discloses an air bag control method and device, which changes the local height of the pillow by adopting the way of curve inflation and staged deflation to the air bag of the pillow, deflects the head of the user, and improves the unblocked degree of the respiratory tract, thereby realizing the snore intervention effect; the method can effectively interfere snore under the condition of not interfering sleep, but seriously changes the original comfortable sleep state of the pillow in a mode of deflecting the head of a user through air inflation and air deflation of the air bag, and influences the comfortable sleep quality.
Chinese patent application No. CN109223291B discloses a multifunctional intelligent pillow capable of independently adjusting the height of head and neck and the included angle of head, which automatically identifies the sleeping posture by building a mechanical adjusting function pillow, and adjusts the included angle of head and neck by module driving after detecting the snore, so as to improve the smoothness of the airway of the user and prevent snoring. However, different users cannot have universality for snore intervention by adjusting angles of the head and the neck due to different body types and differences of neck curves.
Disclosure of Invention
In order to solve the above problems, an embodiment of the present invention provides a snore intervention method based on an adaptive air bag pillow, which accurately determines a snore state of a user in real time, and gradually adjusts a contour of a curve of a skin surface of the pillow to a neck physiological curve with a best snore stopping effect when the user sleeps by charging/discharging the adaptive air bag and slowly adjusting the contour of the skin surface curve of the pillow, so as to maximally alleviate a snore symptom of the user on the premise of not interfering with deep sleep.
In order to achieve the above object, the present invention provides a method for adaptively adjusting an airbag pillow, comprising: detecting snore events of a user in a sleep cycle, wherein the snore events comprise the steps of identifying whether snore exists or not and measuring the volume of the snore, and storing the existence of the snore and the measured volume of the snore as snore audio data into a sleep parameter database; responding to the latest snore audio data and carrying out self-adaptive adjustment on at least one air bag in an air bag pillow according to the stored data in the sleep parameter database so as to change the air pressure of the air bag until a sleep end event occurs or the snore disappears or reaches the minimum; and after a sleep end event is detected, storing the optimal adjustment parameters including the air pressure of the air bag, which correspond to the snore and disappear or reach the minimum optimal adjustment state, of the air bag in the sleep period into the sleep parameter database.
In some embodiments, said detecting a snore event during sleep comprises: slicing the sound signals collected by the sensor to obtain audio slices; judging whether sound exists in the audio slice by using a silence detection algorithm; performing Mel Frequency Cepstrum Coefficient (MFCC) feature extraction on the audio slices judged to contain the sound, and then performing depth feature extraction and classification by using a pre-trained deep learning model to classify each audio slice into an audio slice containing snore and an audio slice not containing snore; calculating the proportion of the audio slices classified as containing snore in a certain time period to the total number of the audio slices in the time period, and if the proportion exceeds a set threshold value, judging that the snore exists in the time period; and calculating and judging that each section of the snore audio frequency contains the maximum sound size of the snore audio frequency slice, and then calculating the average value of the maximum sound size to be used as snore sound volume size data of the snore sound volume size at the moment.
In some embodiments, the step of responding to the latest snore audio data and adaptively adjusting the air bag in the air bag pillow according to the data already stored in the sleep parameter database to change the air pressure of the air bag until a sleep end event occurs or the snore disappears or reaches a minimum includes: judging whether the snore volume data is the first snore volume data received in a preset time period or not, and if so, inquiring a sleep parameter database; if the optimal adjustment parameters which are stored are inquired in the sleep parameter database, automatically adjusting the air bag to the optimal adjustment parameters of the air bag; and if the prior optimal adjusting parameters are not inquired in the sleep parameter database, adjusting the air bag to a preset air bag initial snore stopping state.
In some embodiments, if it is determined that the data is not the data of the first snore volume in the preset time period, checking the sleep parameter database, using the data of the snore volume in the last air bag adjustment period stored in the sleep parameter database recently, determining whether the data of the snore volume is smaller than the previous volume, and if the volume is smaller, continuing to adjust the air bag by using an adjustment mode in the last air bag adjustment period, wherein the adjustment mode is the same as the adjustment mode in the previous air bag adjustment period; if the volume is greater than the previous volume, the air bag continues to be adjusted using the opposite adjustment to that in the previous air bag adjustment cycle.
In some embodiments, the method further comprises the steps of firstly adjusting a first air bag of the at least one air bag in response to the snore volume data, and stopping adjusting the first air bag when the first air bag is continuously inflated and deflated for a preset number of repeated iterations; beginning adjustment of a second air cell within the air cell pillow; and after the second air bag is continuously inflated and deflated for repeated iteration for a preset number of times, stopping adjusting the second air bag, and readjusting the first air bag.
In some embodiments, further comprising when the first and second balloons are continuously inflated and deflated, respectively, for a preset number of iterations; or when the snore audio data is not received in a preset regulation period; the adjustment of the first and second airbags is stopped.
In some embodiments, the optimal adjustment parameters of the air bag comprise air bag air pressure and snore volume data recorded when snore stops or snore is reduced to a minimum amount in the last adjustment period.
In some embodiments, the optimal adjustment parameter is obtained based on sleep data including a number of snores within the adjustment period, a snore time period, a snore duration, a sleep period, and overall course air bag adjustment data.
Further embodiments of the present application provide a system comprising means adapted for carrying out all the steps of the method according to any preceding method claim.
Further embodiments of the application provide a computer program comprising instructions for carrying out all the steps of the method according to any preceding method claim, when said computer program is executed on a computer system.
According to the method of the embodiment of the application, the pillow height can be slowly adjusted by self-adaptive air bag inflation/deflation, the sleeping of the user is not interfered, and the snoring symptom of the user can be relieved. The method according to the embodiment of the application can adjust the inflation/deflation of the air bags on the neck and the head, so that the pillow can still fit the neck and the head of a user, the contact surface pressure is reduced, and the user can sleep comfortably. According to the self-adaptive adjustment method of the embodiment of the application, snore intervention can be performed, the air bag pillow is subjected to non-supervised learning, for example, the head air bag and the neck air bag are adjusted for multiple times in a self-adaptive mode according to the snore condition of a user, the height of the pillow is adjusted, the radian curve of the pillow surface of the user is gradually adjusted to the neck physiological curve with the best snore stopping effect when the user sleeps, and then the snore symptom of the user is improved as much as possible; in addition, compared with the mechanical structure adjustment, the mechanical structure adjustment device is easy to realize, the adjustment process is more real-time and faster, and the mechanical structure adjustment device is more portable and convenient to move.
Drawings
FIGS. 1a, 1b are schematic structural views of an airbag pillow according to an embodiment of the present application;
FIG. 2 is a schematic flow diagram of an adaptive-based airbag pillow adjustment method according to an embodiment of the present application;
FIG. 3 is a flow chart of snore detection according to an embodiment of the present application;
Detailed Description
A sleep cycle: refers to a period from the time when the user lies on the air bag pillow to the time when the user leaves the air bag pillow, which is sensed and judged by the air bag pillow.
Snoring events: refers to an event triggered by a detected snore during a sleep cycle, which includes identifying the presence of a snore and measuring the volume of the snore.
And (3) detection period: refers to a time period corresponding to a complete process of detecting, processing and providing a processing result for snoring.
Adjusting the period: refers to the period of time from the beginning of an adjustment to the end of the adjustment in response to detected snoring, which may be an inflation procedure or a deflation procedure.
Volume of snore: refers to the intensity, and in particular the amplitude, of the snore signal detected by the sensor.
Airbag adjustment data: the method comprises the adjusting mode and the air pressure value of each adjustment of each air bag in each adjusting period and the air pressure state of the adjusted air bag.
The embodiment of the present application is based on a self-adaptive adjustment method of an airbag pillow, which includes: firstly, detecting snore events of a user in a sleep cycle, including but not limited to identifying whether snore exists or not and measuring the volume of the snore, and storing the existence of the snore and the measured volume of the snore as snore audio data into a sleep parameter database; secondly, responding to a snore event and carrying out self-adaptive adjustment on at least one air bag in the air bag pillow according to received snore volume data and data stored in the sleep parameter database so as to change the air pressure of the at least one air bag until the snore event is not detected in a preset detection period or the snore volume of the detected snore event is minimum; and after a sleep end event is detected, storing the optimal adjustment parameters including the air pressure of the air bag, which correspond to the snore and disappear or reach the minimum optimal adjustment state in the current sleep cycle, into the sleep parameter database as the basis for the next adjustment.
The following description will further explain the technical solutions of the present invention with reference to the specific embodiments of the drawings.
Fig. 1a and 1b are schematic structural diagrams of an airbag pillow according to an embodiment of the present application, and the specific structure of the airbag pillow according to fig. 1a and 1b includes an airbag pillow body 10 having an airbag pillow skin surface 101, the skin surface is an arc shape following an ergonomic human neck curve, and the material used for the airbag pillow body 10 may be medium-hardness memory cotton.
The airbag pillow body 10 may have a first airbag 21, and a second airbag 22 therein as shown in fig. 1a and 1 b. The first airbag 21 and the second airbag 22 are two elongated airbags extending along the length direction L of the airbag pillow body, wherein the first airbag 21 is generally disposed at the middle of the airbag pillow body 10 in the height direction H and corresponds to the head of the user when in use, and the second airbag 22 is generally disposed at the lower portion of the airbag pillow body 10 in the height direction H and corresponds to the neck of the user when in use. The two air bags may be inflated/deflated by a control unit 23 operatively connected to the first air bag 21 and the second air bag to adjust the height of the position of the air bag pillow corresponding to the neck and/or head of the user accordingly. The control unit 23 may include an air pump unit connected to the first and second air cells through valves, and an air pump unit controller. In other embodiments, the control unit 23 may be located outside the airbag pillow and communicate with the first and second airbags only through gas pipes and gas release pipes.
The control unit 23 may be controlled to perform the inflation/deflation operation of the first and/or second air cells to effect the intervention of the detected snoring of the user using the control procedure described below.
Fig. 2 is a schematic flow chart of a snoring intervention process based on an adaptive airbag pillow according to an embodiment of the present application, which specifically includes the following steps:
step S201, snore detection, namely acquiring audio data through a sensor, carrying out slice subsection snore detection, judging whether snore exists in an audio slice, measuring and calculating the volume of the snore when the snore exists, and storing the existence of the snore, the volume of the snore and the like serving as the snore audio data into a sleep parameter database;
step S202, receiving a snore detection result, and judging whether the user has snore during sleeping;
step S203, responding to the detected snore and the volume in the sleeping process, carrying out self-adaptive inflation/deflation adjustment on the pillow air bag through the snore, adjusting the arc line of the skin surface to change the support of the head and/or the neck of the user, improving the snore condition and realizing snore intervention;
in step S204, it is determined whether the sleep is finished, for example, by determining that the pressure acting on the airbag pillow is gradually disappeared by the pressure sensor unit, and if it is determined that the sleep is finished, a sleep-finished event may be generated. If not, no sleep end event is generated, the steps S201, S202 and S203 are continuously repeated, snore intervention is continuously carried out, and if the sleep end event is ended, the step S205 is executed;
step S205, if the user is judged to be sleeping finished, analyzing the sleeping state, and setting the air bag adjusting state parameter with the minimum snore volume or the snore stopping state as the optimal adjusting parameter of the sleeping;
step S206, storing the sleep data generated in the sleep cycle including the optimal adjustment parameters into a database.
The steps of the above-described method and/or software functions are described in detail below.
In this embodiment, a specific flow of step S201 snore detection is shown in the flow chart of fig. 3,
in step S301, the audio sensor collects audio data with a sampling frequency of 16KHZ, and the collection process continues from the beginning of a sleep cycle until the end of the sleep cycle. The audio sensor may be disposed on the airbag pillow or may be disposed on an electric bed operatively connected, e.g., communicatively connected, to the airbag pillow. The signal of the start of the sleep cycle can be obtained by, for example, detecting by means of a pressure sensor, for example, provided on the airbag pillow, and the start of the sleep cycle can be determined, for example, when a stable pressure for a certain period of time is detected by means of the pressure sensor. The end of the sleep cycle may be detected by the pressure sensor, for example, and when a stable pressure cannot be detected by the pressure sensor for a certain period of time, it may be determined that the sleep cycle is ended.
In step S302, the acquired audio data is sliced, in this embodiment, audio slicing is performed in a 3-second sliding window manner with a length of 6 seconds as a unit, and audio slicing is performed until the sleep is finished, audio acquisition is no longer performed, or a new 6-second audio is not intercepted.
In step S303, it is determined whether the 6-second audio slice in S302 contains sound, that is, silence detection is performed. By calculating the maximum energy value, the minimum energy value and the standard deviation of the energy value of the sampling value in the audio slice, and comparing the three values with the preset mute threshold, if the mute condition is met, the current audio slice is considered to contain no sound, the audio slice does not perform the subsequent snore detecting steps S304, S305 and S306, and the audio slice is judged to be snore-free and is directly stored in the judgment queue with the fixed duration of 120 seconds in the step S307.
For the audio slice including sound detected in step S303, subsequent snore detection is performed, and steps are S304, S305, and S306.
Specifically, step S304, the audio slice including the sound is standardized, and the energy range of the audio is limited between negative 1 and positive 1, which is beneficial to the fitting of the subsequent snore detection algorithm; then, the audio slice data is framed, in this embodiment, the length of each frame is 25ms, the frame is shifted by 10ms, the frame is divided into 598 frames, then, 64-dimensional MFCC (mel frequency cepstrum coefficient) features are extracted for each frame of audio, the audio can be processed into 598 x 64-dimensional arrays every 6 seconds, the arrays are transformed into 3-dimensional image data dimensions 96 x 64 x 6 and input into the neural network, and the step S305 is entered, and the features of the convolutional neural network are extracted.
The convolutional neural network is a neural network structure which is dominant in the field of computer vision image processing, has the characteristics of translation invariance and local parameter sharing, and is very suitable for extracting some abstract depth features in class image data. Step S305 receives the MFCC (mel frequency cepstrum coefficient) spectrum feature input convolution neural network in step S304, and outputs 128-dimensional feature. The 128-dimensional features are then input to the fully connected layer for final classification, i.e., step S306.
Step S307, storing the audio slice result obtained by the classification in the above step into a queue with a fixed duration of, for example, 120 seconds.
In step 311, the snore audio data of step S309 may be stored in the sleep parameter database, where the snore audio data at least includes the volume of the snore. The snore audio data recorded in the sleep parameter database may be used in a subsequent procedure as a reference for the adjustment of the air bag pillow.
In this embodiment, the airbag cushion may be configured to receive the snore detection result of step S201 in step S202, including determining whether the received data is snore audio data, so as to determine whether the user has snore during sleep. If no snore exists, directly entering step S204 to judge whether the sleep is finished; if the snore exists, the step S203 is carried out, the self-adaptive adjustment of the first air bag and the second air bag is started, and the snore intervention of the air bag pillow on the user is realized.
In some embodiments, specifically, the step S203 of adaptive airbag adjustment may include the following steps:
step S2031, after receiving the snore data, checking the sleep parameter database, judging whether the snore is the first snore in the sleep cycle, if so, executing steps S2032, S2033 and S2034, and if not, executing steps S2035, S2036 and S2037.
Step S2032 continues to determine whether the airbag pillow is used for the first time, and if it is determined that the airbag pillow is used for the first time, step S2033 is executed to inflate the airbag to an initial snore-stopping state preset by the product according to the initial snore-stopping parameters, where the initial snore-stopping state may be a two-airbag air pressure state meeting a good snore intervention effect for most people, obtained according to ergonomics, big data analysis and product tests. If the product is not used for the first time, step S2034 is executed, in which the sleep parameter database is checked, and the air bag inflation/deflation is returned to the air bag pressure in the optimal state of the air bag pillow in the last sleep cycle stored in the database. Whether the product is used for the first time can be judged according to whether the optimal adjustment parameters of the air bag pillow are stored in the sleep parameter database.
The first and/or second balloons may be in a fully deflated state or a fully inflated state in the initial state. Or in some embodiments, before the air bag pillow is not used or snore intervenes, the air pressures in the two air bags are in a safe low-pressure state, for example, the air pressure value is 5KPa, and the first snore intervening air bag inflation and deflation in the second sleep can be effectively reduced while the comfortable sleep of a user is met.
When the detected snore is judged not to be the first snore of the sleep, the sleep parameter database is checked, last snore audio data stored in the sleep parameter database is used, step S2035 is executed, namely whether the volume of the snore is smaller than the volume in the last snore audio data or not is judged, if the volume is smaller, the snore intervention effect is good, step S2036 is executed, the air bag is adjusted in the mode of air bag inflation/deflation adjustment last time, namely, if the snore is the inflation operation last time, the inflation operation is also the current time, and if the snore is the deflation operation last time, the deflation operation is also the current time; if it is determined that the snore sound becomes loud, which indicates that the last snore intervention effect is not good, the snore improving effect is not achieved, and even the snore symptom is aggravated, step S2037 is executed, in which the air bag is adjusted in a manner opposite to the last air bag inflation/deflation, that is, if the last time is an inflation operation, the current time is a deflation operation, and if the last time is a deflation operation, the current time is an inflation operation.
Specifically, each time the air bag is inflated/deflated, the second air bag corresponding to the neck can be adjusted preferentially, and then the first air bag positioned at the head can be adjusted, and the single air bag adjustment mode is performed based on the S203 air bag adaptive adjustment. Normally, continuous inflation or deflation of the air bag is the case that the snoring symptom is effectively improved, but when the adjustment air bag cannot continuously improve the snoring symptom, the air bag is inflated at a time, and is deflated at a time, for example, when the inflation/deflation of the second air bag at the neck part is iterated for 3 times, where the 3 times of iteration are the last four times of adjustment of the air bag: inflating, deflating, inflating and deflating; or deflating, inflating, deflating and inflating, at the moment, the adjustment of the neck air bag is judged to be incapable of continuously improving the snoring symptom, the adjustment of the second air bag is stopped, and the adjustment of the first air bag corresponding to the head position is started. Similarly, when the first air bag at the head part is normally and continuously inflated or deflated to improve the snore symptom, the situation that inflation/deflation is iterated for 3 times also occurs, which also indicates that the adjustment of the first air bag at the head part cannot continuously improve the snore symptom, the adjustment of the first air bag is stopped, the second air bag is adjusted again, and so on, and the alternating self-adaptive adjustment of the two air bags is realized.
The airbag pillow may be configured such that adaptive adjustment of the airbag is temporarily stopped when the following two conditions occur during the above-described adjustment of the airbag: firstly, the snore symptom is stopped, namely after the snore audio data are continuously received and correspondingly adjusted, the snore audio data are not detected again in a preset detection period, the self-adaptive adjustment of the air bag is stopped, and the air bag maintains the air pressure state of the air bag which is finally adjusted until the snore is detected again and starts again; secondly, the snoring symptom can not be improved continuously, namely, the two air bags of the pillow continuously generate certain times of inflation/deflation iteration, for example, the condition of 3 times, namely, the latest 8 times of air bag adjustment do not have continuous inflation or deflation, and the inflation/deflation iteration is only the alternate iteration of inflation/deflation, at the moment, the self-adaptive adjustment is stopped after the air pressure of the two air bags of the pillow is adjusted to the air pressure state of the air bag of the previous time of adjustment, and the adjustment is restarted until snore sound audio data representing higher volume is detected.
It may be set such that the air pressure inside the air bag is changed at every inflation/deflation of the air bag in every adjustment period to a fixed value, for example, 0.5KPa, 0.4KPa, 0.3KPa, etc., or it may be set such that different air pressure change values are used in one adjustment period, for example, that snoring is improved at the first time when the air bag is inflated at 0.5KPa and snoring is not improved at the second time when the air bag is inflated at 0.5KPa, the next operation is to deflate 0.4KPa, and it is judged whether or not the volume of snoring is contributing to be reduced.
After each time of adaptive adjustment of the air bag, the step S204 is carried out to judge whether the sleep of the user is finished, if the sleep of the user is not finished, the steps S201, S202 and S203 are continuously repeated, and a new round of adaptive adjustment is started. The adaptive adjustment of the air bag is performed until the snore stops or the volume of the snore is reduced to the minimum, and the adaptive adjustment is performed after the snore is monitored again or the snore is increased, so that the step S203 is performed again to start the adaptive adjustment. Judging whether the sleep is finished or not may include judging the pressure of the head and neck of the human body against the airbag pillow through the pressure sensor to judge whether the human body has left the airbag pillow or not, and then judging whether the sleep is finished or not. In the embodiment that the airbag pillow is in communication connection with the electric bed, the method can further comprise the step of judging whether the sleep is finished or not by obtaining a signal provided by the electric bed and indicating whether the human body is on the electric bed or not.
After the user is judged to have finished sleeping in step S204, the method proceeds to step S205 to analyze the sleeping state in the sleeping period. The state of the adjusting air bag in the snore volume minimum state or the snore stop state can be determined as the optimal state of the sleep. And storing the optimal adjustment parameters corresponding to the optimal adjustment state of the sleep air bag in a sleep parameter database for calling the next sleep cycle.
Alternatively, after the sleep is determined to be finished in step S204, the airbag pillow may be restored to a safe low-pressure state in which the air pressure in the airbag is at when the airbag pillow is not in use.
After the sleep state is analyzed S205, step S206 is executed to store the sleep-related data in the sleep cycle into the database. The stored sleep-related data may include the number of snores, snore time period, snore time duration, snore maximum volume, adjustment cycle duration, sleep cycle length, and overall process airbag adjustment data, etc. The overall process air bag adjusting data can comprise adjusting times in each adjusting period, adjusting modes of each adjusting, specific air pressure parameters of each adjusting, air pressure parameters of the adjusted air bag, and corresponding snore volume change trends and magnitude values after adjusting.
It will be appreciated that in embodiments with two air cells, the adjustment of the first air cell for the corresponding head position may be initiated first in some cases, for example, if the air pressure of the second air cell is higher at the neck position of the pillow, approaching a critical air pressure maximum, then the adjustment of the first air cell for the head position is initiated preferentially.
It should be understood that, besides the 3 iterations of inflation and deflation, other iterations, such as 2, 4, 5, 6, etc., may be used as the triggering condition for the adjustment switching of the first and second air bags. The first and second airbags may be iterated continuously for 2, 4, 5, 6, etc. times as a trigger to end the adjustment.
It should be understood that the above-mentioned method for adjusting the air bag is not only applicable to an air bag pillow with two air bags, but also applicable to an air bag pillow with one, three or more air bags, and the main point of the method for adjusting is to determine the current adjustment mode, i.e. whether inflation or deflation is the ideal adjustment mode, by adaptively adjusting the air bag and detecting the volume of the adjusted snore audio through an audio sensor and comparing the detected volume with the volume of the snore audio stored in the last adjustment period, so that the system finds the most appropriate inflation pressure of each air bag by itself.
The difference with respect to the method described above with respect to the air bag pillow of an air bag is that it is not necessary to choose which air bag to activate first, and the criteria for ending the adjustment can be a preset number of iterations of successive inflation and deflation adjustments of that air bag. The operation steps of snore audio detection, adjustment operation, analysis, storage and the like are the same.
For the three-cell airbag pillow, the difference with respect to the above-described method is that it is not necessary to select which of the cells is to be activated first, and the criterion for switching the adjustment of the cells may be a predetermined number of iterations of the inflation and deflation adjustment of one cell, and the criterion for ending the adjustment of the cells may be a predetermined number of iterations of the inflation and deflation adjustment of all the cells. The operation steps of snore audio detection, adjustment, analysis, storage and the like are the same.
The execution of the above steps may be implemented by programming on a computing system or control system comprising a processor and a memory, which may be located inside the airbag pillow or operatively connected to said airbag pillow, for example receiving signals from an audio sensor of the airbag pillow. The sleep parameter database may be deployed within or external to the computing system or control system, for example in communicative connection with the computing system or control system.
Each of the procedures, steps described above may be implemented in whole or in part by computer software program modules. For example, the step in step S201 may be implemented as a snore detecting module. The steps in step S202 are implemented as a receiving module. The step in step S203 may be implemented as an airbag adaptive adjustment module. The step S204 is implemented as a sleep end determination module for the user alone. Step S205 is implemented solely as a sleep state analysis module.
In some example embodiments, the functions of any of the methods, processes, signaling diagrams, algorithms, or flow diagrams described herein may be implemented by software and/or computer program code or portions of code stored in memory or other computer-readable or tangible media, and executed by a processor.
In some example embodiments, the apparatus may be included or associated with at least one software application, module, unit or entity configured as an arithmetic operation, or as a program or portion thereof (including added or updated software routines), executed by at least one operating processor. Programs, also referred to as program products or computer programs, including software routines, applets and macros, may be stored in any device-readable data storage medium and may include program instructions for performing particular tasks.
A computer program product may comprise one or more computer-executable components configured to perform some example embodiments when the program is run. The one or more computer-executable components may be at least one software code or code portion. Changes and configurations to implement the functions of the example embodiments may be performed as routines, which may be implemented as added or updated software routines. In an example, a software routine may be downloaded into the device.
By way of example, the software or computer program code or portions of code may be in source code form, object code form, or in some intermediate form, and may be stored on some type of carrier, distribution medium, or computer-readable medium, which may be any entity or device capable of carrying the program. Such a carrier may comprise, for example, a record medium, computer memory, read-only memory, an optical and/or electrical carrier signal, a telecommunication signal and/or a software distribution package. Depending on the required processing power, the computer program may be executed in a single electronic digital computer or may be distributed over a plurality of computers. The computer-readable medium or computer-readable storage medium may be a non-transitory medium.
In other example embodiments, this functionality may be performed by hardware or circuitry included in the airbag pillow, for example, by using an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or any other hardware and software combination. In yet another example embodiment, the functionality may be implemented as a signal, such as a non-tangible means that may be carried by electromagnetic signals downloaded from the Internet or other networks.
According to example embodiments, an apparatus such as a node, device or response means may be configured as a circuit, a computer or a microprocessor (such as a single chip computer element) or a chipset, which may comprise at least a memory for providing storage capacity for arithmetic operations and/or an operation processor for performing arithmetic operations.
Finally, it should be noted that: the above embodiments are merely illustrative of the present invention, and any variations and modifications which do not require inventive efforts by those skilled in the art are within the scope of the present invention without departing from the core of the present invention.
Claims (10)
1. A self-adaptive adjustment method of an air bag pillow is characterized by comprising the following steps: the method comprises the following steps:
detecting snore events of a user in a sleep cycle, wherein the snore events comprise the steps of identifying whether snore exists or not and measuring the volume of the snore, and storing the existence of the snore and the measured volume of the snore as snore audio data into a sleep parameter database;
responding to the latest snore audio data and carrying out self-adaptive adjustment on at least one air bag in an air bag pillow according to the stored data in the sleep parameter database so as to change the air pressure of the air bag until a sleep end event occurs or the snore disappears or reaches the minimum; and
and after a sleep end event is detected, storing the optimal adjustment parameters including the air pressure of the air bag, which correspond to the optimal adjustment state that the snore disappears or the optimal adjustment state reaches the minimum, of the air bag in the current sleep cycle into the sleep parameter database.
2. The adaptive adjustment method of an airbag pillow according to claim 1, characterized in that: the detection of snoring events in the sleeping process comprises:
slicing the sound signals collected by the sensor to obtain audio slices;
judging whether sound exists in the audio slice by using a silence detection algorithm;
performing Mel Frequency Cepstrum Coefficient (MFCC) feature extraction on the audio slices judged to contain the sound, and then performing depth feature extraction and classification by using a pre-trained deep learning model to classify each audio slice into an audio slice containing snore and an audio slice not containing snore;
calculating the proportion of the audio slices classified as containing snore in a certain time period to the total number of the audio slices in the time period, and if the proportion exceeds a set threshold value, judging that the snore exists in the time period;
and calculating and judging that each section of the snore audio contains the maximum sound size of the snore audio slice, and then calculating the average value of the maximum sound size to serve as snore volume size data of the snore volume size at the moment.
3. The adaptive adjustment method of an airbag pillow according to claim 1, characterized in that:
the step of responding the latest snore audio data and carrying out self-adaptive adjustment on the air bag in the air bag pillow according to the data stored in the sleep parameter database so as to change the air pressure of the air bag until a sleep end event occurs or the snore disappears or reaches the minimum comprises the following steps:
judging whether the snore volume data is the first snore volume data received in a preset time period or not, and if so, inquiring a sleep parameter database; if the optimal adjustment parameters which are stored are inquired in the sleep parameter database, automatically adjusting the air bag to the optimal adjustment parameters of the air bag; and if the prior optimal adjusting parameters are not inquired in the sleep parameter database, adjusting the air bag to a preset air bag initial snore stopping state.
4. The adaptive adjustment method of an airbag pillow according to claim 3, characterized in that: if the data is not the data of the first snore volume in the preset time period, checking the sleep parameter database, using the data of the snore volume in the last air bag adjusting period which is stored in the sleep parameter database recently, judging whether the data of the snore volume is smaller than the last volume or not, and if the volume is smaller, continuing to use the adjusting mode which is the same as the adjusting mode in the last air bag adjusting period to adjust the air bag; if the volume is greater than the previous volume, the air bag continues to be adjusted using the opposite adjustment to that in the previous air bag adjustment cycle.
5. The adaptive adjustment method of an airbag pillow according to claim 3, characterized in that:
the snore sound volume data is responded, a first air bag in the at least one air bag is adjusted, and when the first air bag is continuously inflated and deflated for repeated iteration preset times, the adjustment of the first air bag is stopped; beginning adjustment of a second air cell within the air cell pillow; and after the second air bag is continuously inflated and deflated for repeated iteration for a preset number of times, stopping adjusting the second air bag, and readjusting the first air bag.
6. The adaptive adjustment method of an airbag pillow according to claim 5, characterized in that: when the first air bag and the second air bag are continuously and respectively inflated and deflated for repeated iteration preset times; or when the snore audio data is not received in a preset regulation period; the adjustment of the first and second airbags is stopped.
7. The adaptive adjustment method of an airbag pillow according to claim 1, characterized in that: the optimal adjusting parameters of the air bag comprise air pressure of the air bag and snore volume data recorded when snore stops or snore is reduced to the minimum in the last adjusting period.
8. The adaptive adjustment method of an airbag pillow according to claim 1, characterized in that: the optimal adjustment parameters are obtained based on sleep data including the number of snores, the snore time period, the snore duration, the sleep cycle and the overall process air bag adjustment data in the adjustment period.
9. A system comprising means adapted for carrying out all the steps of the method according to any preceding method claim.
10. A computer program comprising instructions for carrying out all the steps of the method according to any preceding method claim, when said computer program is executed on a computer system.
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