CN114343373A - Method, system and storage medium for intelligently adjusting mattress - Google Patents
Method, system and storage medium for intelligently adjusting mattress Download PDFInfo
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- CN114343373A CN114343373A CN202210005065.XA CN202210005065A CN114343373A CN 114343373 A CN114343373 A CN 114343373A CN 202210005065 A CN202210005065 A CN 202210005065A CN 114343373 A CN114343373 A CN 114343373A
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- 238000000034 method Methods 0.000 title claims abstract description 41
- 230000007958 sleep Effects 0.000 claims description 49
- 206010041235 Snoring Diseases 0.000 claims description 31
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- 230000003750 conditioning effect Effects 0.000 claims 3
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- 206010003497 Asphyxia Diseases 0.000 description 8
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47C—CHAIRS; SOFAS; BEDS
- A47C23/00—Spring mattresses with rigid frame or forming part of the bedstead, e.g. box springs; Divan bases; Slatted bed bases
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47C—CHAIRS; SOFAS; BEDS
- A47C21/00—Attachments for beds, e.g. sheet holders, bed-cover holders; Ventilating, cooling or heating means in connection with bedsteads or mattresses
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47C—CHAIRS; SOFAS; BEDS
- A47C27/00—Spring, stuffed or fluid mattresses or cushions specially adapted for chairs, beds or sofas
- A47C27/08—Fluid mattresses or cushions
- A47C27/081—Fluid mattresses or cushions of pneumatic type
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47C—CHAIRS; SOFAS; BEDS
- A47C27/00—Spring, stuffed or fluid mattresses or cushions specially adapted for chairs, beds or sofas
- A47C27/08—Fluid mattresses or cushions
- A47C27/10—Fluid mattresses or cushions with two or more independently-fillable chambers
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Abstract
The application discloses a method, a system and a storage medium for intelligently adjusting a mattress, which are applied to an adjustable mattress, wherein the method comprises the following steps: acquiring pressure sensing values, sound information and mattress state information of all positions in a mattress; sending the pressure sensing value, the sound information and the mattress state information to a server side; acquiring body state information of a user in a preset time period; analyzing according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain an optimal adjustment parameter; and sending the optimal adjustment parameters to the mattress controller for adjustment. The invention enables the mattress to carry out self-adaptive angle and hardness adjustment according to the state of the user, and can determine the identity of the user to carry out independent partition adjustment according to the voiceprint of the user, thereby improving the sleep quality of the user.
Description
Technical Field
The present application pertains to the field of sensing and data processing, and more particularly, to a method, system, and storage medium for intelligently adjusting a mattress.
Background
The mattress is an article between the human body and the bed, which is used for ensuring that consumers obtain healthy and comfortable sleep, one third of people spend in sleep, the sleep is a rest link essential for life, human beings must ensure certain sleep time and sleep quality every day to maintain sufficient life vitality, so to speak, the sleep is the basis of human survival, and the mattress is a necessary tool for ensuring that the sleepers obtain healthy and comfortable sleep.
At present, a multifunctional mattress capable of being adjusted through an air cushion and a movable support exists, a user can adjust the multifunctional mattress according to needs, but the state of the mattress cannot be changed when the user sleeps well, and if the user has the condition of low sleep quality, such as snoring and the like, and the mattress cannot be adjusted in a self-adaptive manner, the sleep quality of the user cannot be changed.
The prior art has defects and needs to be improved urgently.
Disclosure of Invention
In view of the above, the present application provides a method, system and storage medium for intelligently adjusting a mattress, which enables a movable mattress to be adaptively adjusted according to a user's status, and enables individual zone adjustment according to a user's voiceprint to determine a user's identity.
The invention discloses a method for intelligently adjusting a mattress in a first aspect, which comprises the following steps:
acquiring pressure sensing values, sound information and mattress state information of all positions in a mattress;
sending the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring body state information of a user in a preset time period;
analyzing according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain an optimal adjustment parameter;
and sending the optimal adjustment parameters to the mattress controller for adjustment.
In this scheme, after sending the best adjustment parameter to mattress controller and adjusting, still include:
acquiring user voice information within a preset time range;
analyzing the voice information of the user and judging whether the snoring condition exists or not;
if the pressure sensing value exists, the pressure sensing value, the sound information and the mattress state information are sent to a server side;
and the optimal adjustment parameters of the receiving server are adjusted again.
In this scheme, the analysis is carried out according to pressure sensing value, sound information, mattress state information and health state information, specifically is:
acquiring body information and mattress adjustment information of a user in a short time period and a long time period to obtain short-period information and long-period information;
multiplying the short period information by a short period coefficient, and adding the long period information by a long period coefficient to obtain a first prediction parameter;
and analyzing the first prediction parameter to obtain a first recommended adjustment parameter.
In this scheme, still include:
inputting the pressure sensing value, the sound information, the mattress state information and the body state information into a preset sleep neural network model to obtain a second prediction parameter;
and multiplying the first prediction parameter by a first coefficient, adding the second prediction parameter by a second coefficient, and dividing by 2 to obtain an optimal adjustment parameter, and sending the optimal adjustment parameter to the mattress controller for adjustment.
In the scheme, the method for acquiring the body state information of the user in the preset time period specifically comprises the following steps:
acquiring voiceprint information according to the sound information;
confirming the user identity according to the voiceprint information to obtain user ID information;
sending the user ID information to a server side;
and the server side acquires corresponding body state information according to the user ID information.
In this scheme, still include:
acquiring a current sleep posture of a user;
judging whether the optimal adjustment parameters are suitable for the sleep posture of the current user;
if so, adjusting according to the optimal adjustment parameters; if not, the optimal adjustment parameter is corrected.
A second aspect of the present invention provides a system for intelligently adjusting a mattress, comprising a memory and a processor, wherein the memory includes a method program for intelligently adjusting a mattress, and the processor executes the method program for intelligently adjusting a mattress to realize the following steps:
acquiring pressure sensing values, sound information and mattress state information of all positions in a mattress;
sending the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring body state information of a user in a preset time period;
analyzing according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain an optimal adjustment parameter;
and sending the optimal adjustment parameters to the mattress controller for adjustment.
In this scheme, after sending the best adjustment parameter to mattress controller and adjusting, still include:
acquiring user voice information within a preset time range;
analyzing the voice information of the user and judging whether the snoring condition exists or not;
if the pressure sensing value exists, the pressure sensing value, the sound information and the mattress state information are sent to a server side;
and the optimal adjustment parameters of the receiving server are adjusted again.
In this scheme, the analysis is carried out according to pressure sensing value, sound information, mattress state information and health state information, specifically is:
acquiring body information and mattress adjustment information of a user in a short time period and a long time period to obtain short-period information and long-period information;
multiplying the short period information by a short period coefficient, and adding the long period information by a long period coefficient to obtain a first prediction parameter;
and analyzing the first prediction parameter to obtain a first recommended adjustment parameter.
In this scheme, still include:
inputting the pressure sensing value, the sound information, the mattress state information and the body state information into a preset sleep neural network model to obtain a second prediction parameter;
and multiplying the first prediction parameter by a first coefficient, adding the second prediction parameter by a second coefficient, and dividing by 2 to obtain an optimal adjustment parameter, and sending the optimal adjustment parameter to the mattress controller for adjustment.
In the scheme, the method for acquiring the body state information of the user in the preset time period specifically comprises the following steps:
acquiring voiceprint information according to the sound information;
confirming the user identity according to the voiceprint information to obtain user ID information;
sending the user ID information to a server side;
and the server side acquires corresponding body state information according to the user ID information.
In this scheme, still include:
acquiring a current sleep posture of a user;
judging whether the optimal adjustment parameters are suitable for the sleep posture of the current user;
if so, adjusting according to the optimal adjustment parameters; if not, the optimal adjustment parameter is corrected.
A third aspect of the invention provides a computer-readable storage medium comprising a method program for intelligently adjusting a mattress, which method program, when executed by a processor, performs the steps of a method for intelligently adjusting a mattress as described in any one of the above.
The method, the system and the storage medium for intelligently adjusting the mattress are applied to the adjustable mattress, so that the movable mattress can be adjusted in angle and hardness in a self-adaptive mode according to the state of a user, the identity of the user can be determined according to the voiceprint of the user, independent partition adjustment can be carried out, and the sleep quality of the user is improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
FIG. 1 illustrates a flow chart of a method of intelligently adjusting a mattress of the present invention;
FIG. 2 shows a schematic diagram of a smart-tuned mattress of the present invention;
fig. 3 shows a system block diagram of a smart adjustment mattress of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application are clearly and completely described, and it is obvious that the embodiments described below are only a part of the embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 shows a flow chart of a method of intelligently adjusting a mattress of the present invention.
S102, as shown in figure 1, the invention discloses a method for intelligently adjusting a mattress, which comprises the following steps:
s104, acquiring pressure sensing values, sound information and mattress state information of all positions in the mattress;
s106, sending the pressure sensing value, the sound information and the mattress state information to a server side;
s108, acquiring body state information of a user in a preset time period;
s110, analyzing according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain an optimal adjustment parameter;
and sending the optimal adjustment parameters to the mattress controller for adjustment.
It should be noted that, as shown in fig. 2, the mattress 11 of the present application includes a plurality of air bag devices, which are disposed at different positions in the middle of the mattress according to requirements, and each air bag can be controlled individually, so that the corresponding mattress position is lifted up to form the local protrusions 12. The mattress is also provided with a support which can be controlled by a motor inside the mattress to control the folding angle of the mattress, as shown in figure 2, the mattress 11 being in a folded state. The folding position and the folding angle of the bracket can be set by the technicians in the field according to the actual needs. Wherein, still be provided with a plurality of pressure sensor in the mattress, pressure sensor sets up inside the mattress to be close to mattress surface position, with can accurately receive the pressure information on the mattress and give first place to, pressure sensor can be even set up inside the mattress, and the quantity that sets up is more, then the user's that detects pressure is just more accurate. The mattress is also provided with sound receivers, such as microphones, so as to collect sound data, and the sound receivers can be arranged in a plurality of positions of the mattress.
The invention firstly obtains pressure sensing values, sound information and mattress state information of all positions in the mattress, wherein the mattress state information is the folding state of each area of the mattress and the inflation state of a plurality of air cushions inside the mattress so as to reflect the specific shape state of the current mattress. Wherein, the pressure sensing value is obtained by the pressure sensor, and the sound information is obtained by the sound receiver. And then sending the pressure sensing value, the sound information and the mattress state information to a server, and carrying out data analysis by the server to determine the optimal adjustment mode. The invention also obtains the body state information of the user in a preset time period, wherein the preset time period can be set by the technical personnel in the field according to the actual needs and can be the latest month or the latest week, and the current optimal adjustment parameters of the mattress can be more accurately analyzed through the body state information of the user. After the server acquires the information, the server analyzes the information according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain the optimal adjustment parameter, wherein the analysis can be performed in a big data mode or a cloud computing or fog computing mode. And finally, the optimal adjustment parameters are sent to a mattress controller for adjustment, and the controller controls an air bag and a motor in the mattress according to the optimal adjustment parameters, so that the mattress is adjusted to be most suitable for the angle and the protruding mode of the user, and the sleeping quality of the user is improved.
According to the embodiment of the invention, after the optimal adjustment parameters are sent to the mattress controller for adjustment, the method further comprises the following steps:
acquiring user voice information within a preset time range;
analyzing the voice information of the user and judging whether the snoring condition exists or not;
if the pressure sensing value exists, the pressure sensing value, the sound information and the mattress state information are sent to a server side;
and the optimal adjustment parameters of the receiving server are adjusted again.
It should be noted that, after the state of the mattress is adjusted, the invention can also continuously detect the sound to determine whether the user snores, and if the user snores, the user is proved to be in a bad sleeping state, a light sleeping state and a suffocation risk, so that the adjustment needs to be performed again. First, user voice information is acquired within a preset time range. The preset time range can be set by a person skilled in the art according to actual needs, for example, the preset time range is 10 minutes or 30 minutes later. And acquiring the sound of the user through the sound receiver, judging whether the user snores, and if the user snores, continuously sending the pressure sensing value, the sound information and the mattress state information to the server side. And the server readjusts according to the received pressure sensing value, the sound information, the mattress state information and the previously acquired body state information, so that the mattress is automatically adjusted, the snoring condition of the user is reduced, or the snoring is stopped, and the sleeping quality of the user is improved.
According to the embodiment of the invention, the analysis is performed according to the pressure sensing value, the sound information, the mattress state information and the body state information, and specifically comprises the following steps:
acquiring body information and mattress adjustment information of a user in a short time period and a long time period to obtain short-period information and long-period information;
multiplying the short period information by a short period coefficient, and adding the long period information by a long period coefficient to obtain a first prediction parameter;
and analyzing the first prediction parameter to obtain a first recommended adjustment parameter.
It should be noted that the server performs analysis according to the body information of the user in a long time period and a short time period, and the information of the body state of the user can be more accurate through the analysis of the long time period and the short time period. The long period can reflect the body state of the body for a longer period of time, the short period can reflect the recent body state of the body, the body change state of the user, such as the state of weight, blood oxygen and blood pressure, can be analyzed through the combination of the long period and the short period, the change of the mattress can be more accurately controlled through the analysis of the body change state of the user, and the sleep quality of the user is improved. When the specific analysis calculation is carried out, the short period information is multiplied by the short period coefficient, and the long period information is added to be multiplied by the long period coefficient to obtain a first prediction parameter. Wherein the sum of the short period coefficient and the long period coefficient is 1, and the short period coefficient and the long period coefficient may be dynamically changed or may be set by those skilled in the art according to actual needs. The first prediction parameter is actually a parameter reflecting body state information of the user, and the first prediction parameter is analyzed, wherein the analysis combines mattress adjustment information, sound information and pressure sensing value information, and then a first recommended adjustment parameter is obtained.
According to the embodiment of the invention, the method further comprises the following steps:
inputting the pressure sensing value, the sound information, the mattress state information and the body state information into a preset sleep neural network model to obtain a second prediction parameter;
and multiplying the first prediction parameter by a first coefficient, adding the second prediction parameter by a second coefficient, and dividing by 2 to obtain an optimal adjustment parameter, and sending the optimal adjustment parameter to the mattress controller for adjustment.
It should be noted that, the present invention may not only analyze the body state data of the user in long and short periods, but also perform predictive analysis according to the neural network model, and obtain the optimal adjustment parameter by combining the first predictive parameter. The preset sleep neural network model is trained in advance, and the pressure sensing value, the sound information, the mattress state information and the body state information are input into the preset sleep neural network model to obtain a second prediction parameter. And then, multiplying the first prediction parameter by a first coefficient, adding the second prediction parameter by a second coefficient, and dividing by 2 to obtain an optimal adjustment parameter, and sending the optimal adjustment parameter to the mattress controller for adjustment. The first coefficient and the second coefficient are numbers larger than 0, can be integers or decimal numbers, and the sum is divided by 2 to obtain the optimal adjustment parameter. It should be noted that, a person skilled in the art may set the first coefficient and the second coefficient according to actual needs, and in addition, the first coefficient and the second coefficient may also be dynamically changed.
According to the embodiment of the invention, the body state information of the user in the preset time period is acquired, and the method specifically comprises the following steps:
acquiring voiceprint information according to the sound information;
confirming the user identity according to the voiceprint information to obtain user ID information;
sending the user ID information to a server side;
and the server side acquires corresponding body state information according to the user ID information.
It should be noted that the mattress of the present invention can collect the voice information of the user through the voice receiver, the voice information can be the snoring sound of the user or the voice of the user during speaking, the voiceprint information can be obtained through the voice information, and since the voiceprint information of each person is special and can also be unique, the identity information of the user can be obtained through the voiceprint information, and further the user ID information can be obtained. And then sending the user ID information to a server side to acquire corresponding body state information, wherein the body state information of the user can be pre-stored in the server or acquired by the server from other third-party platforms.
According to the embodiment of the invention, the method further comprises the following steps:
acquiring a current sleep posture of a user;
judging whether the optimal adjustment parameters are suitable for the sleep posture of the current user;
if so, adjusting according to the optimal adjustment parameters; if not, the optimal adjustment parameter is corrected.
It should be noted that the invention can also perform adaptive adjustment of the mattress according to the sleeping posture of the user. First, it is necessary to say that the current user is sleeping. And then judging whether the optimal adjustment parameters are suitable for the sleeping posture of the current user, and if so, adjusting the mattress according to the optimal adjustment parameters. If not, the optimal adjustment parameter is corrected. The sleeping posture of the user can be judged by the numerical values of the pressure sensors distributed in the mattress, and the numerical value and the distribution position of each sensor can indirectly analyze the current sleeping posture of the user. For example, the sensor distribution and values for side and lying sleep are not the same.
According to the embodiment of the present invention, the correcting the optimal adjustment parameter specifically includes:
determining the most suitable posture of the current sleep time period according to the sleep posture and the body state information of the current user;
judging a mattress adjustment curve according to the current sleeping posture of the user and the most suitable posture of the current sleeping time period;
and generating adjustment information according to the mattress adjustment curve, and sending the adjustment information to a mattress controller for adjustment.
It should be noted that, if a user keeps a certain posture for a long time while sleeping, the user may not be good for physical health, for example, the user may press the heart when lying on the stomach for a long time. Therefore, the invention can detect the sleeping posture of the user in real time, then determine the optimal sleeping posture at present and then adjust. Firstly, the most suitable posture of the current sleep time interval is determined according to the sleep posture and the body state information of the current user, the current sleep time interval is the time interval in the sleep cycle of the whole night, the general sleep time interval is divided into deep sleep stages and light sleep stages, and the most suitable posture can be determined according to each sleep time interval. Then, a mattress adjustment curve is judged according to the most suitable posture of the current sleeping posture of the user and the current sleeping time period, wherein the mattress adjustment curve is a curve of time and a mattress state, for example, the mattress is in an A state at the time t1, and is to be changed to a B state at the time t2, and the changing process is the curve. And finally, generating adjustment information according to the mattress adjustment curve, and sending the adjustment information to a mattress controller for adjustment.
According to the embodiment of the present invention, the generation of the preset sleep neural network model specifically comprises:
acquiring historical state data; preprocessing the historical state data to obtain a training array; sending the training array to an initialized neural network model for training; acquiring the error rate of the trained neural network model; and if the error rate is less than a preset error rate threshold value, stopping training to obtain a preset sleep neural network model.
It should be noted that the historical state data is data of the sleep state, the physical state, and the like of the user, and the more the acquired historical data amount is, the more accurate the trained neural network model is. Firstly, after obtaining the historical text feature value, preprocessing is required, for example, normalization processing or format conversion processing is performed on the data to facilitate training of the neural network, and after preprocessing, a training data set is obtained. And then inputting the training data set into the initialized neural network model for training, wherein the training is automatic training, and finally the behavior scoring neural network model is obtained. And then inputting test data, and judging the accuracy of the prediction result output by the sleep neural network model. And comparing the prediction accuracy with a preset accuracy threshold, if the prediction accuracy exceeds the accuracy threshold, indicating that the sleep neural network model can achieve a better prediction effect, and stopping training. Wherein the accuracy threshold may be 80-95%.
According to the embodiment of the invention, the method further comprises the following steps:
determining the snoring condition and the breathing state of the user according to the sound information of the user;
analyzing according to the snoring condition and the breathing state to obtain the asphyxia risk degree;
and if the suffocation risk degree is higher than a preset threshold value, sending warning information to a preset terminal.
The information about the sound frequency, the sound level, and the like of the user can be analyzed to obtain the snoring condition and the breathing state of the user. Then, an apnea risk degree is obtained according to the snoring condition and the breathing state, wherein the apnea risk degree is a numerical value, and the higher the numerical value is, the higher the apnea risk caused by the snoring in the sleeping is. When the suffocation risk degree is higher than a preset threshold value, warning information is sent to a preset terminal to prompt risks, the preset terminal can be a current sleep user terminal or a family terminal of a user, and the preset terminal is specifically set by a person skilled in the art according to actual needs.
According to the embodiment of the present invention, the short-period coefficient, the long-period coefficient, the first coefficient, and the second coefficient are dynamically changed, and the coefficient determination method specifically includes:
acquiring body state information of a user in a preset period, and calculating an optimal adjustment parameter to obtain a third prediction parameter;
acquiring body state information for presetting a next period, and calculating an optimal adjustment parameter to obtain a fourth prediction parameter;
comparing the difference rate of the third prediction parameter and the fourth prediction parameter;
and if the difference rate is greater than the preset difference rate threshold value, calculating the short-period coefficient, the long-period coefficient, the first coefficient and the second coefficient according to the fourth prediction parameter.
When the short-period coefficient, the long-period coefficient, the first coefficient, and the second coefficient are dynamically adjusted, the adjustment may be performed based on the historical physical state information of the user. A time window is set, namely a preset period is set, then the body state information of the preset period is obtained, and a third prediction parameter is obtained through calculation. Then, in the next time window, i.e. in the next preset period, the fourth prediction parameter is calculated. And comparing the difference rate of the third prediction parameter and the fourth prediction parameter, and if the difference is larger, indicating that the coefficient at the moment does not accord with the body state of the latest window, determining the coefficient by using the parameter of the latest window. The third prediction parameter and the fourth prediction parameter are parameters obtained by predicting a preset sleep neural network model. The coefficient is determined in a sliding window mode of historical state data, so that the prediction result is more accurate.
Fig. 3 shows a block diagram of a system for intelligently adjusting a mattress according to the present invention.
As shown in fig. 3, the present invention discloses a system 3 for intelligently adjusting a mattress, comprising a memory 31 and a processor 32, wherein the memory includes a method program for intelligently adjusting a mattress, and the method program for intelligently adjusting a mattress realizes the following steps when being executed by the processor:
acquiring pressure sensing values, sound information and mattress state information of all positions in a mattress;
sending the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring body state information of a user in a preset time period;
analyzing according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain an optimal adjustment parameter;
and sending the optimal adjustment parameters to the mattress controller for adjustment.
It should be noted that, as shown in fig. 2, the mattress 11 of the present application includes a plurality of air bag devices, which are disposed at different positions in the middle of the mattress according to requirements, and each air bag can be controlled individually, so that the corresponding mattress position is lifted up to form the local protrusions 12. The mattress is also provided with a support which can be controlled by a motor inside the mattress to control the folding angle of the mattress, as shown in figure 2, the mattress 11 being in a folded state. The folding position and the folding angle of the bracket can be set by the technicians in the field according to the actual needs. Wherein, still be provided with a plurality of pressure sensor in the mattress, pressure sensor sets up inside the mattress to be close to mattress surface position, with can accurately receive the pressure information on the mattress and give first place to, pressure sensor can be even set up inside the mattress, and the quantity that sets up is more, then the user's that detects pressure is just more accurate. The mattress is also provided with sound receivers, such as microphones, so as to collect sound data, and the sound receivers can be arranged in a plurality of positions of the mattress.
The invention firstly obtains pressure sensing values, sound information and mattress state information of all positions in the mattress, wherein the mattress state information is the folding state of each area of the mattress and the inflation state of a plurality of air cushions inside the mattress so as to reflect the specific shape state of the current mattress. Wherein, the pressure sensing value is obtained by the pressure sensor, and the sound information is obtained by the sound receiver. And then sending the pressure sensing value, the sound information and the mattress state information to a server, and carrying out data analysis by the server to determine the optimal adjustment mode. The invention also obtains the body state information of the user in a preset time period, wherein the preset time period can be set by the technical personnel in the field according to the actual needs and can be the latest month or the latest week, and the current optimal adjustment parameters of the mattress can be more accurately analyzed through the body state information of the user. After the server acquires the information, the server analyzes the information according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain the optimal adjustment parameter, wherein the analysis can be performed in a big data mode or a cloud computing or fog computing mode. And finally, the optimal adjustment parameters are sent to a mattress controller for adjustment, and the controller controls an air bag and a motor in the mattress according to the optimal adjustment parameters, so that the mattress is adjusted to be most suitable for the angle and the protruding mode of the user, and the sleeping quality of the user is improved.
According to the embodiment of the invention, after the optimal adjustment parameters are sent to the mattress controller for adjustment, the method further comprises the following steps:
acquiring user voice information within a preset time range;
analyzing the voice information of the user and judging whether the snoring condition exists or not;
if the pressure sensing value exists, the pressure sensing value, the sound information and the mattress state information are sent to a server side;
and the optimal adjustment parameters of the receiving server are adjusted again.
It should be noted that, after the state of the mattress is adjusted, the invention can also continuously detect the sound to determine whether the user snores, and if the user snores, the user is proved to be in a bad sleeping state, a light sleeping state and a suffocation risk, so that the adjustment needs to be performed again. First, user voice information is acquired within a preset time range. The preset time range can be set by a person skilled in the art according to actual needs, for example, the preset time range is 10 minutes or 30 minutes later. And acquiring the sound of the user through the sound receiver, judging whether the user snores, and if the user snores, continuously sending the pressure sensing value, the sound information and the mattress state information to the server side. And the server readjusts according to the received pressure sensing value, the sound information, the mattress state information and the previously acquired body state information, so that the mattress is automatically adjusted, the snoring condition of the user is reduced, or the snoring is stopped, and the sleeping quality of the user is improved.
According to the embodiment of the invention, the analysis is performed according to the pressure sensing value, the sound information, the mattress state information and the body state information, and specifically comprises the following steps:
acquiring body information and mattress adjustment information of a user in a short time period and a long time period to obtain short-period information and long-period information;
multiplying the short period information by a short period coefficient, and adding the long period information by a long period coefficient to obtain a first prediction parameter;
and analyzing the first prediction parameter to obtain a first recommended adjustment parameter.
It should be noted that the server performs analysis according to the body information of the user in a long time period and a short time period, and the information of the body state of the user can be more accurate through the analysis of the long time period and the short time period. The long period can reflect the body state of the body for a longer period of time, the short period can reflect the recent body state of the body, the body change state of the user, such as the state of weight, blood oxygen and blood pressure, can be analyzed through the combination of the long period and the short period, the change of the mattress can be more accurately controlled through the analysis of the body change state of the user, and the sleep quality of the user is improved. When the specific analysis calculation is carried out, the short period information is multiplied by the short period coefficient, and the long period information is added to be multiplied by the long period coefficient to obtain a first prediction parameter. Wherein the sum of the short period coefficient and the long period coefficient is 1, and the short period coefficient and the long period coefficient may be dynamically changed or may be set by those skilled in the art according to actual needs. The first prediction parameter is actually a parameter reflecting body state information of the user, and the first prediction parameter is analyzed, wherein the analysis combines mattress adjustment information, sound information and pressure sensing value information, and then a first recommended adjustment parameter is obtained.
According to the embodiment of the invention, the method further comprises the following steps:
inputting the pressure sensing value, the sound information, the mattress state information and the body state information into a preset sleep neural network model to obtain a second prediction parameter;
and multiplying the first prediction parameter by a first coefficient, adding the second prediction parameter by a second coefficient, and dividing by 2 to obtain an optimal adjustment parameter, and sending the optimal adjustment parameter to the mattress controller for adjustment.
It should be noted that, the present invention may not only analyze the body state data of the user in long and short periods, but also perform predictive analysis according to the neural network model, and obtain the optimal adjustment parameter by combining the first predictive parameter. The preset sleep neural network model is trained in advance, and the pressure sensing value, the sound information, the mattress state information and the body state information are input into the preset sleep neural network model to obtain a second prediction parameter. And then, multiplying the first prediction parameter by a first coefficient, adding the second prediction parameter by a second coefficient, and dividing by 2 to obtain an optimal adjustment parameter, and sending the optimal adjustment parameter to the mattress controller for adjustment. The first coefficient and the second coefficient are numbers larger than 0, can be integers or decimal numbers, and the sum is divided by 2 to obtain the optimal adjustment parameter. It should be noted that, a person skilled in the art may set the first coefficient and the second coefficient according to actual needs, and in addition, the first coefficient and the second coefficient may also be dynamically changed.
According to the embodiment of the invention, the body state information of the user in the preset time period is acquired, and the method specifically comprises the following steps:
acquiring voiceprint information according to the sound information;
confirming the user identity according to the voiceprint information to obtain user ID information;
sending the user ID information to a server side;
and the server side acquires corresponding body state information according to the user ID information.
It should be noted that the mattress of the present invention can collect the voice information of the user through the voice receiver, the voice information can be the snoring sound of the user or the voice of the user during speaking, the voiceprint information can be obtained through the voice information, and since the voiceprint information of each person is special and can also be unique, the identity information of the user can be obtained through the voiceprint information, and further the user ID information can be obtained. And then sending the user ID information to a server side to acquire corresponding body state information, wherein the body state information of the user can be pre-stored in the server or acquired by the server from other third-party platforms.
According to the embodiment of the invention, the method further comprises the following steps:
acquiring a current sleep posture of a user;
judging whether the optimal adjustment parameters are suitable for the sleep posture of the current user;
if so, adjusting according to the optimal adjustment parameters; if not, the optimal adjustment parameter is corrected.
It should be noted that the invention can also perform adaptive adjustment of the mattress according to the sleeping posture of the user. First, it is necessary to say that the current user is sleeping. And then judging whether the optimal adjustment parameters are suitable for the sleeping posture of the current user, and if so, adjusting the mattress according to the optimal adjustment parameters. If not, the optimal adjustment parameter is corrected. The sleeping posture of the user can be judged by the numerical values of the pressure sensors distributed in the mattress, and the numerical value and the distribution position of each sensor can indirectly analyze the current sleeping posture of the user. For example, the sensor distribution and values for side and lying sleep are not the same.
According to the embodiment of the present invention, the correcting the optimal adjustment parameter specifically includes:
determining the most suitable posture of the current sleep time period according to the sleep posture and the body state information of the current user;
judging a mattress adjustment curve according to the current sleeping posture of the user and the most suitable posture of the current sleeping time period;
and generating adjustment information according to the mattress adjustment curve, and sending the adjustment information to a mattress controller for adjustment.
It should be noted that, if a user keeps a certain posture for a long time while sleeping, the user may not be good for physical health, for example, the user may press the heart when lying on the stomach for a long time. Therefore, the invention can detect the sleeping posture of the user in real time, then determine the optimal sleeping posture at present and then adjust. Firstly, the most suitable posture of the current sleep time interval is determined according to the sleep posture and the body state information of the current user, the current sleep time interval is the time interval in the sleep cycle of the whole night, the general sleep time interval is divided into deep sleep stages and light sleep stages, and the most suitable posture can be determined according to each sleep time interval. Then, a mattress adjustment curve is judged according to the most suitable posture of the current sleeping posture of the user and the current sleeping time period, wherein the mattress adjustment curve is a curve of time and a mattress state, for example, the mattress is in an A state at the time t1, and is to be changed to a B state at the time t2, and the changing process is the curve. And finally, generating adjustment information according to the mattress adjustment curve, and sending the adjustment information to a mattress controller for adjustment.
According to the embodiment of the present invention, the generation of the preset sleep neural network model specifically comprises:
acquiring historical state data; preprocessing the historical state data to obtain a training array; sending the training array to an initialized neural network model for training; acquiring the error rate of the trained neural network model; and if the error rate is less than a preset error rate threshold value, stopping training to obtain a preset sleep neural network model.
It should be noted that the historical state data is data of the sleep state, the physical state, and the like of the user, and the more the acquired historical data amount is, the more accurate the trained neural network model is. Firstly, after obtaining the historical text feature value, preprocessing is required, for example, normalization processing or format conversion processing is performed on the data to facilitate training of the neural network, and after preprocessing, a training data set is obtained. And then inputting the training data set into the initialized neural network model for training, wherein the training is automatic training, and finally the behavior scoring neural network model is obtained. And then inputting test data, and judging the accuracy of the prediction result output by the sleep neural network model. And comparing the prediction accuracy with a preset accuracy threshold, if the prediction accuracy exceeds the accuracy threshold, indicating that the sleep neural network model can achieve a better prediction effect, and stopping training. Wherein the accuracy threshold may be 80-95%.
According to the embodiment of the invention, the method further comprises the following steps:
determining the snoring condition and the breathing state of the user according to the sound information of the user;
analyzing according to the snoring condition and the breathing state to obtain the asphyxia risk degree;
and if the suffocation risk degree is higher than a preset threshold value, sending warning information to a preset terminal.
The information about the sound frequency, the sound level, and the like of the user can be analyzed to obtain the snoring condition and the breathing state of the user. Then, an apnea risk degree is obtained according to the snoring condition and the breathing state, wherein the apnea risk degree is a numerical value, and the higher the numerical value is, the higher the apnea risk caused by the snoring in the sleeping is. When the suffocation risk degree is higher than a preset threshold value, warning information is sent to a preset terminal to prompt risks, the preset terminal can be a current sleep user terminal or a family terminal of a user, and the preset terminal is specifically set by a person skilled in the art according to actual needs.
According to the embodiment of the present invention, the short-period coefficient, the long-period coefficient, the first coefficient, and the second coefficient are dynamically changed, and the coefficient determination method specifically includes:
acquiring body state information of a user in a preset period, and calculating an optimal adjustment parameter to obtain a third prediction parameter;
acquiring body state information for presetting a next period, and calculating an optimal adjustment parameter to obtain a fourth prediction parameter;
comparing the difference rate of the third prediction parameter and the fourth prediction parameter;
and if the difference rate is greater than the preset difference rate threshold value, calculating the short-period coefficient, the long-period coefficient, the first coefficient and the second coefficient according to the fourth prediction parameter.
When the short-period coefficient, the long-period coefficient, the first coefficient, and the second coefficient are dynamically adjusted, the adjustment may be performed based on the historical physical state information of the user. A time window is set, namely a preset period is set, then the body state information of the preset period is obtained, and a third prediction parameter is obtained through calculation. Then, in the next time window, i.e. in the next preset period, the fourth prediction parameter is calculated. And comparing the difference rate of the third prediction parameter and the fourth prediction parameter, and if the difference is larger, indicating that the coefficient at the moment does not accord with the body state of the latest window, determining the coefficient by using the parameter of the latest window. The third prediction parameter and the fourth prediction parameter are parameters obtained by predicting a preset sleep neural network model. The coefficient is determined in a sliding window mode of historical state data, so that the prediction result is more accurate.
A third aspect of the invention provides a computer-readable storage medium comprising a method program for intelligently adjusting a mattress, which method program, when executed by a processor, performs the steps of a method for intelligently adjusting a mattress as described in any one of the above.
The method, the system and the storage medium for intelligently adjusting the mattress are applied to the adjustable mattress, so that the movable mattress can be adjusted in angle and hardness in a self-adaptive mode according to the state of a user, the identity of the user can be determined according to the voiceprint of the user, independent partition adjustment can be carried out, and the sleep quality of the user is improved.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
Claims (10)
1. A method of intelligently adjusting a mattress, comprising:
acquiring pressure sensing values, sound information and mattress state information of all positions in a mattress;
sending the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring body state information of a user in a preset time period;
analyzing according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain an optimal adjustment parameter;
and sending the optimal adjustment parameters to the mattress controller for adjustment.
2. The method of claim 1, further comprising, after sending the optimal adjustment parameters to the mattress controller for adjustment:
acquiring user voice information within a preset time range;
analyzing the voice information of the user and judging whether the snoring condition exists or not;
if the pressure sensing value exists, the pressure sensing value, the sound information and the mattress state information are sent to a server side;
and the optimal adjustment parameters of the receiving server are adjusted again.
3. The method for intelligently adjusting a mattress according to claim 1, wherein the analysis is performed based on the pressure sensing values, the sound information, the mattress state information and the body state information, in particular:
acquiring body information and mattress adjustment information of a user in a short time period and a long time period to obtain short-period information and long-period information;
multiplying the short period information by a short period coefficient, and adding the long period information by a long period coefficient to obtain a first prediction parameter;
and analyzing the first prediction parameter to obtain a first recommended adjustment parameter.
4. The method of intelligently adjusting a mattress of claim 3, further comprising:
inputting the pressure sensing value, the sound information, the mattress state information and the body state information into a preset sleep neural network model to obtain a second prediction parameter;
and multiplying the first prediction parameter by a first coefficient, adding the second prediction parameter by a second coefficient, and dividing by 2 to obtain an optimal adjustment parameter, and sending the optimal adjustment parameter to the mattress controller for adjustment.
5. The method for intelligently adjusting a mattress according to claim 1, wherein the obtaining of the body state information of the user for a preset time period is specifically:
acquiring voiceprint information according to the sound information;
confirming the user identity according to the voiceprint information to obtain user ID information;
sending the user ID information to a server side;
and the server side acquires corresponding body state information according to the user ID information.
6. The method of intelligently adjusting a mattress of claim 1, further comprising:
acquiring a current sleep posture of a user;
judging whether the optimal adjustment parameters are suitable for the sleep posture of the current user;
if so, adjusting according to the optimal adjustment parameters; if not, the optimal adjustment parameter is corrected.
7. A system for intelligently adjusting a mattress, comprising a memory and a processor, the memory including a method program for intelligently adjusting a mattress, the method program for intelligently adjusting a mattress when executed by the processor implementing the steps of:
acquiring pressure sensing values, sound information and mattress state information of all positions in a mattress;
sending the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring body state information of a user in a preset time period;
analyzing according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain an optimal adjustment parameter;
and sending the optimal adjustment parameters to the mattress controller for adjustment.
8. The system for intelligently conditioning a mattress according to claim 7, further comprising, after sending the optimal conditioning parameters to the mattress controller for conditioning:
acquiring user voice information within a preset time range;
analyzing the voice information of the user and judging whether the snoring condition exists or not;
if the pressure sensing value exists, the pressure sensing value, the sound information and the mattress state information are sent to a server side;
and the optimal adjustment parameters of the receiving server are adjusted again.
9. The system for intelligently adjusting a mattress of claim 7, further comprising:
acquiring a current sleep posture of a user;
judging whether the optimal adjustment parameters are suitable for the sleep posture of the current user;
if so, adjusting according to the optimal adjustment parameters; if not, the optimal adjustment parameter is corrected.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium contains a method program for intelligently adjusting a mattress, which method program, when executed by a processor, carries out the steps of a method for intelligently adjusting a mattress as claimed in any one of claims 1 to 6.
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