CN114343373B - 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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- CN114343373B CN114343373B CN202210005065.XA CN202210005065A CN114343373B CN 114343373 B CN114343373 B CN 114343373B CN 202210005065 A CN202210005065 A CN 202210005065A CN 114343373 B CN114343373 B CN 114343373B
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- 238000000034 method Methods 0.000 title claims abstract description 27
- 230000007958 sleep Effects 0.000 claims description 52
- 238000003062 neural network model Methods 0.000 claims description 32
- 206010041235 Snoring Diseases 0.000 claims description 31
- 238000004458 analytical method Methods 0.000 claims description 18
- 238000012937 correction Methods 0.000 claims description 8
- 238000005192 partition Methods 0.000 abstract description 3
- 238000012549 training Methods 0.000 description 22
- 206010003497 Asphyxia Diseases 0.000 description 14
- 230000029058 respiratory gaseous exchange Effects 0.000 description 8
- 230000008859 change Effects 0.000 description 6
- 238000007781 pre-processing Methods 0.000 description 6
- 238000012545 processing Methods 0.000 description 6
- 238000006243 chemical reaction Methods 0.000 description 4
- 230000008667 sleep stage Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000003860 sleep quality Effects 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 2
- 230000006399 behavior Effects 0.000 description 2
- 239000008280 blood Substances 0.000 description 2
- 210000004369 blood Anatomy 0.000 description 2
- 230000036772 blood pressure Effects 0.000 description 2
- 230000037396 body weight Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 230000003862 health status Effects 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 229910052760 oxygen Inorganic materials 0.000 description 2
- 239000001301 oxygen Substances 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 241001669679 Eleotris Species 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000004622 sleep time Effects 0.000 description 1
- 230000004083 survival effect Effects 0.000 description 1
Classifications
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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 or bed-cover holders; Ventilating, cooling or heating means in connection with bedsteads or mattresses
-
- 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
- A47C27/081—Fluid mattresses 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
- A47C27/10—Fluid mattresses with two or more independently-fillable chambers
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- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
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 the mattress; transmitting the pressure sensing value, the sound information and the mattress state information to a server side; acquiring physical 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 optimal adjustment parameters; and sending the optimal adjustment parameters to the mattress controller for adjustment. The application enables the mattress to carry out self-adaptive angle adjustment 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 sleeping quality of the user.
Description
Technical Field
The application belongs to the field of sensing and data processing, and particularly relates to a method, a system and a storage medium for intelligently adjusting a mattress.
Background
The mattress is an article between a human body and a bed, which is used for ensuring that a consumer obtains healthy and comfortable sleep, one third of life is spent in the sleep, the sleep is an essential rest link of life, the human needs to ensure certain sleep time and sleep quality every day to maintain enough vitality, so that the sleep is the basis of human survival, and the mattress is a necessary tool for ensuring that a sleeper obtains 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 requirements, but the state of the mattress cannot be changed when the user sleeps well, and if the user has a condition of low sleep quality, for example, snoring and other states, the mattress cannot be adjusted in a self-adaptive mode, so that the sleep quality of the user cannot be changed.
The prior art has defects and needs to be improved.
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 adjustments to be made according to a user's voiceprint determination.
The first aspect of the invention discloses a method for intelligently adjusting a mattress, which comprises the following steps:
acquiring pressure sensing values, sound information and mattress state information of all positions in the mattress;
transmitting the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring physical 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 optimal adjustment parameters;
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 sound information within a preset time range;
Analyzing the voice information of the user and judging whether snoring exists or not;
if the pressure sensing value exists, sending the pressure sensing value, the sound information and the mattress state information to a server side;
the optimal adjustment parameters of the receiving server are adjusted again.
In this scheme, according to pressure sensing value, sound information, mattress state information and health status information carry out the analysis, specifically do:
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 multiplying the long period information by a long period coefficient to obtain a first prediction parameter;
And analyzing the first prediction parameters to obtain first recommended adjustment parameters.
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 plus the second prediction parameter by a second coefficient, dividing by 2 to obtain an optimal adjustment parameter, and transmitting the optimal adjustment parameter to a mattress controller for adjustment.
In this scheme, acquire user's physical state information of preset time quantum, specifically be:
acquiring voiceprint information according to the sound information;
Confirming the identity of a user according to the voiceprint information to obtain user ID information;
the user ID information is sent to a server side;
And the server side acquires corresponding physical state information according to the user ID information.
In this scheme, still include:
Acquiring a current sleeping posture of a user;
Judging whether the optimal adjustment parameters are suitable for the sleeping posture of the current user;
If yes, adjusting according to the optimal adjustment parameters; if not, the correction of the optimal adjustment parameters is performed.
The second aspect of the present invention provides a system for intelligently adjusting a mattress, comprising a memory and a processor, wherein the memory comprises a method program for intelligently adjusting the mattress, and the method program for intelligently adjusting the 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 the mattress;
transmitting the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring physical 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 optimal adjustment parameters;
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 sound information within a preset time range;
Analyzing the voice information of the user and judging whether snoring exists or not;
if the pressure sensing value exists, sending the pressure sensing value, the sound information and the mattress state information to a server side;
the optimal adjustment parameters of the receiving server are adjusted again.
In this scheme, according to pressure sensing value, sound information, mattress state information and health status information carry out the analysis, specifically do:
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 multiplying the long period information by a long period coefficient to obtain a first prediction parameter;
And analyzing the first prediction parameters to obtain first recommended adjustment parameters.
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 plus the second prediction parameter by a second coefficient, dividing by 2 to obtain an optimal adjustment parameter, and transmitting the optimal adjustment parameter to a mattress controller for adjustment.
In this scheme, acquire user's physical state information of preset time quantum, specifically be:
acquiring voiceprint information according to the sound information;
Confirming the identity of a user according to the voiceprint information to obtain user ID information;
the user ID information is sent to a server side;
And the server side acquires corresponding physical state information according to the user ID information.
In this scheme, still include:
Acquiring a current sleeping posture of a user;
Judging whether the optimal adjustment parameters are suitable for the sleeping posture of the current user;
If yes, adjusting according to the optimal adjustment parameters; if not, the correction of the optimal adjustment parameters is performed.
A third aspect of the present invention provides a computer readable storage medium having embodied therein a method program for intelligently adjusting a mattress, which when executed by a processor, implements the steps of a method for intelligently adjusting a mattress as described in any one of the preceding claims.
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 carry out self-adaptive angle adjustment and hardness adjustment according to the state of a 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 sleeping quality of the user.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the application, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
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 the intelligent mattress of the present invention;
Fig. 3 shows a system block diagram of an intelligent 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 of the embodiments of the present application are clearly and completely described, and it is apparent that the embodiments described below are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Fig. 1 shows a flow chart of a method of intelligently adjusting a mattress according to the present invention.
S102, as shown in FIG. 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, transmitting the pressure sensing value, the sound information and the mattress state information to a server side;
S108, acquiring physical 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 physical state information to obtain the optimal adjustment parameters;
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, and each air bag device may be separately controlled according to the requirement and disposed at different positions in the middle of the mattress, so that the corresponding mattress position is lifted up to form a local protrusion 12. The mattress is also provided with a stand which controls the angle of folding of the mattress by means of a motor inside the mattress, as shown in fig. 2, the mattress 11 being in a folded state. The support can be set by a person skilled in the art according to actual needs to the folding position and the folding angle. The mattress is also provided with a plurality of pressure sensors, the pressure sensors are arranged inside the mattress and are close to the surface of the mattress, so that the pressure information on the mattress can be accurately received, the pressure sensors can be uniformly arranged inside the mattress, and the more the number of the pressure sensors is, the more accurate the pressure of a detected user is. The mattress is also provided with sound receivers, such as microphones, for collecting sound data, and the sound receivers can be arranged in a plurality of parts distributed on the mattress.
The invention firstly acquires pressure sensing values, sound information and mattress state information of all positions in the mattress, wherein the mattress state information is a folding state of each area of the mattress and an inflation state of a plurality of air cushions in the mattress so as to reflect the specific shape state of the current mattress. Wherein the pressure sensing value is obtained by a pressure sensor, and the sound information is obtained by a sound receiver. And then the pressure sensing value, the sound information and the mattress state information are sent to a server side, and the server performs data analysis to determine the optimal adjustment mode. The invention also obtains the physical state information of the user in the preset time period, wherein the preset time period can be set by a person skilled in the art according to actual needs and can be the last month or the last week, and the optimal adjustment parameters of the current mattress can be more accurately analyzed through the physical state information of the user. After the server acquires the information, the server analyzes according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain the optimal adjustment parameters, wherein the analysis can be performed by a big data mode or a cloud computing or fog computing mode. And finally, sending the optimal adjustment parameters to a mattress controller for adjustment, wherein 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 a user, and the sleeping quality of the user is improved.
According to an embodiment of the present invention, after sending the optimal adjustment parameters to the mattress controller for adjustment, the method further includes:
acquiring user sound information within a preset time range;
Analyzing the voice information of the user and judging whether snoring exists or not;
if the pressure sensing value exists, sending the pressure sensing value, the sound information and the mattress state information to a server side;
the optimal adjustment parameters of the receiving server are adjusted again.
It should be noted that, the present invention can also continuously detect sound after adjusting the state of the mattress to determine whether the user snores, if snoring exists, the sleeping state of the user is not good, the user is in a shallow sleeping state, and there is a risk of asphyxia, so that the user needs to adjust again. First, user sound information is acquired within a preset time range. The preset time range may be set by those skilled in the art according to actual needs, for example, after 10 minutes or 30 minutes. And acquiring the voice of the user through the voice receiver, judging whether the user snores, and if the user snores, continuously transmitting the pressure sensing value, the voice information and the mattress state information to a server side. The server side 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 can be automatically adjusted, the snoring condition of the user can be reduced, or the snoring can be stopped, and the sleeping quality of the user can be 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 physical state information, specifically:
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 multiplying the long period information by a long period coefficient to obtain a first prediction parameter;
And analyzing the first prediction parameters to obtain first recommended adjustment parameters.
It should be noted that, the server analyzes 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 in the short time period. The long period can reflect the body state of the body for a long time, the short period can reflect the body state of the body in the near future, the body change state of the user, such as the state of body weight, blood oxygen and blood pressure, can be analyzed through the combination of the long period and the short period, the mattress change can be controlled more accurately through the analysis of the body change state of the user, and the sleeping quality of the user is improved. When specific analysis and calculation are carried out, the invention multiplies the short period information by the short period coefficient, and multiplies the long period information 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 can be dynamically changed or set by a person skilled in the art according to actual needs. The first prediction parameters are actually parameters reflecting the physical state information of the user, and are analyzed, wherein the analysis combines the mattress adjustment information, the sound information and the pressure sensing value information, so that the first recommended adjustment parameters are obtained.
According to an embodiment of the present invention, 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 plus the second prediction parameter by a second coefficient, dividing by 2 to obtain an optimal adjustment parameter, and transmitting the optimal adjustment parameter to a mattress controller for adjustment.
It should be noted that, the invention not only analyzes the physical state data of the user with long and short periods, but also can perform predictive analysis according to the neural network model, and combines the first predictive parameters to obtain the optimal adjustment parameters. 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 and multiplying the second prediction parameter by a second coefficient, dividing by 2 to obtain an optimal adjustment parameter, and transmitting the optimal adjustment parameter to a mattress controller for adjustment. Wherein the first coefficient and the second coefficient are numbers greater than 0, which can be integers or decimal, and dividing the sum by 2 can obtain the optimal adjustment parameters. 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 physical state information of the user in the preset time period is acquired, specifically:
acquiring voiceprint information according to the sound information;
Confirming the identity of a user according to the voiceprint information to obtain user ID information;
the user ID information is sent to a server side;
And the server side acquires corresponding physical state information according to the user ID information.
The mattress can collect the voice information of the user through the voice receiver, the voice information can be the snoring voice of the user or the voice of the user when speaking, the voice information can be obtained through the voice information, and the voice information of each person is special and can be unique, so that the identity information of the user can be obtained through the voice information, and further the user ID information is obtained. And then the user ID information is sent to a server side to acquire corresponding physical state information, wherein the physical state information of the user can be pre-stored in the server or acquired by the server from other third-party platforms.
According to an embodiment of the present invention, further comprising:
Acquiring a current sleeping posture of a user;
Judging whether the optimal adjustment parameters are suitable for the sleeping posture of the current user;
If yes, adjusting according to the optimal adjustment parameters; if not, the correction of the optimal adjustment parameters is performed.
The invention can also adaptively adjust the mattress according to the sleeping posture of the user. First, the current user sleep gesture needs to be spoken. And 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 parameters are modified. The sleeping posture of the user can be obtained through judging the values of the pressure sensors distributed in the mattress, and the current sleeping posture of the user can be indirectly analyzed through the value of each sensor and the distributed positions. For example, the sensor distribution and the values are different for side sleep and for lying down sleep.
According to the embodiment of the invention, the correction for performing the optimal adjustment parameter specifically includes:
determining the most suitable posture of the current sleep period according to the current sleep posture and the body state information of the user;
Judging a mattress adjusting curve according to the sleeping posture of the current user and the most suitable posture of the current sleeping 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 the user keeps a certain posture for a long time while sleeping, the user may be unfavorable to physical health, for example, the user may easily press the heart while lying down for a long time. The present invention can detect the sleeping posture of the user in real time, then determine the optimal posture of the current sleep, and then adjust. Firstly, determining the most suitable posture of a current sleep period according to the current sleep posture and the physical state information of a user, wherein the current sleep period is a period in a whole night sleep period, and the general sleep period is divided into a deep sleep stage and a shallow sleep stage. Then, according to the most suitable posture of the current sleeping posture of the user and the current sleeping period, the mattress adjusting curve is judged, the mattress adjusting curve is a curve of time and mattress state, for example, the mattress is in an A state at the time t1, and the mattress is converted into a B state at the time t2, and the conversion 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 invention, the generation of the preset sleep neural network model is specifically as follows:
acquiring historical state data; preprocessing the historical state data to obtain a training array; transmitting the training array to an initialized neural network model for training; obtaining the error rate of the trained neural network model; and if the error rate is smaller than a preset error rate threshold, stopping training to obtain a preset sleep neural network model.
The historical state data is data of sleep, physical state and the like of the user, and the more the number of the obtained historical data is, the more accurate the trained neural network model is. Firstly, after the historical text characteristic value is obtained, preprocessing, for example, normalization processing or format conversion processing is required to be carried out on the data so as to facilitate training of the neural network, and a training data set is obtained after preprocessing. And inputting the training data set into the initialized neural network model for training, wherein the training is automatic training, and finally obtaining the behavior scoring neural network model. 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 accuracy threshold is exceeded, the sleep neural network model can reach a better prediction effect, and training can be stopped. Wherein the accuracy threshold may be 80-95%.
According to an embodiment of the present invention, further comprising:
determining snoring conditions and breathing conditions of the user according to the user sound information;
Analyzing and obtaining the asphyxia risk according to the snoring condition and the breathing state;
and if the asphyxia risk is higher than a preset threshold, sending warning information to a preset terminal.
The user's voice information can also be analyzed to obtain the voice frequency, tone level and other information, and the snoring condition and breathing state of the user can be obtained through the information. Then, according to the snoring condition and the breathing state, the asphyxia risk degree can be obtained, wherein the asphyxia risk degree is a numerical value, and the higher the numerical value is, the higher the asphyxia risk caused by snoring in sleeping is. When the suffocation risk degree is higher than a preset threshold, warning information is sent to a preset terminal to prompt the risk, wherein 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 invention, the short period coefficient, the long period coefficient, the first coefficient and the second coefficient are dynamically changed, and the coefficient determining mode specifically comprises the following steps:
acquiring physical state information of a user preset period, and calculating an optimal adjustment parameter to obtain a third prediction parameter;
acquiring body state information for presetting the 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;
If the difference rate is larger than the preset difference rate threshold, calculating a short period coefficient, a long period coefficient, a first coefficient and a second coefficient according to the fourth prediction parameter.
In the case of dynamically adjusting the short-period coefficient, the long-period coefficient, the first coefficient, and the second coefficient, the adjustment may be performed based on the user's historical physical state information. Setting a time window, namely setting a preset period, then acquiring physical state information of the preset period, and calculating to obtain a third prediction parameter. Then, in the next time window, that is, the next preset period range, a fourth prediction parameter is calculated. Comparing the difference rates of the third predicted parameter and the fourth predicted parameter, if the difference is large, indicating that the coefficient at this time does not conform to the state of the body of the latest window, the coefficient will be determined with 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 prediction result of the invention can be more accurate by determining the coefficient in a sliding window mode of the historical state data.
Fig. 3 shows a block diagram of a system for intelligently adjusting a mattress in accordance with the present invention.
As shown in fig. 3, the present invention discloses a system 3 for intelligently adjusting a mattress, which comprises a memory 31 and a processor 32, wherein the memory comprises a method program for intelligently adjusting the mattress, and the method program for intelligently adjusting the 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 the mattress;
transmitting the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring physical 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 optimal adjustment parameters;
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, and each air bag device may be separately controlled according to the requirement and disposed at different positions in the middle of the mattress, so that the corresponding mattress position is lifted up to form a local protrusion 12. The mattress is also provided with a stand which controls the angle of folding of the mattress by means of a motor inside the mattress, as shown in fig. 2, the mattress 11 being in a folded state. The support can be set by a person skilled in the art according to actual needs to the folding position and the folding angle. The mattress is also provided with a plurality of pressure sensors, the pressure sensors are arranged inside the mattress and are close to the surface of the mattress, so that the pressure information on the mattress can be accurately received, the pressure sensors can be uniformly arranged inside the mattress, and the more the number of the pressure sensors is, the more accurate the pressure of a detected user is. The mattress is also provided with sound receivers, such as microphones, for collecting sound data, and the sound receivers can be arranged in a plurality of parts distributed on the mattress.
The invention firstly acquires pressure sensing values, sound information and mattress state information of all positions in the mattress, wherein the mattress state information is a folding state of each area of the mattress and an inflation state of a plurality of air cushions in the mattress so as to reflect the specific shape state of the current mattress. Wherein the pressure sensing value is obtained by a pressure sensor, and the sound information is obtained by a sound receiver. And then the pressure sensing value, the sound information and the mattress state information are sent to a server side, and the server performs data analysis to determine the optimal adjustment mode. The invention also obtains the physical state information of the user in the preset time period, wherein the preset time period can be set by a person skilled in the art according to actual needs and can be the last month or the last week, and the optimal adjustment parameters of the current mattress can be more accurately analyzed through the physical state information of the user. After the server acquires the information, the server analyzes according to the pressure sensing value, the sound information, the mattress state information and the body state information to obtain the optimal adjustment parameters, wherein the analysis can be performed by a big data mode or a cloud computing or fog computing mode. And finally, sending the optimal adjustment parameters to a mattress controller for adjustment, wherein 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 a user, and the sleeping quality of the user is improved.
According to an embodiment of the present invention, after sending the optimal adjustment parameters to the mattress controller for adjustment, the method further includes:
acquiring user sound information within a preset time range;
Analyzing the voice information of the user and judging whether snoring exists or not;
if the pressure sensing value exists, sending the pressure sensing value, the sound information and the mattress state information to a server side;
the optimal adjustment parameters of the receiving server are adjusted again.
It should be noted that, the present invention can also continuously detect sound after adjusting the state of the mattress to determine whether the user snores, if snoring exists, the sleeping state of the user is not good, the user is in a shallow sleeping state, and there is a risk of asphyxia, so that the user needs to adjust again. First, user sound information is acquired within a preset time range. The preset time range may be set by those skilled in the art according to actual needs, for example, after 10 minutes or 30 minutes. And acquiring the voice of the user through the voice receiver, judging whether the user snores, and if the user snores, continuously transmitting the pressure sensing value, the voice information and the mattress state information to a server side. The server side 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 can be automatically adjusted, the snoring condition of the user can be reduced, or the snoring can be stopped, and the sleeping quality of the user can be 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 physical state information, specifically:
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 multiplying the long period information by a long period coefficient to obtain a first prediction parameter;
And analyzing the first prediction parameters to obtain first recommended adjustment parameters.
It should be noted that, the server analyzes 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 in the short time period. The long period can reflect the body state of the body for a long time, the short period can reflect the body state of the body in the near future, the body change state of the user, such as the state of body weight, blood oxygen and blood pressure, can be analyzed through the combination of the long period and the short period, the mattress change can be controlled more accurately through the analysis of the body change state of the user, and the sleeping quality of the user is improved. When specific analysis and calculation are carried out, the invention multiplies the short period information by the short period coefficient, and multiplies the long period information 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 can be dynamically changed or set by a person skilled in the art according to actual needs. The first prediction parameters are actually parameters reflecting the physical state information of the user, and are analyzed, wherein the analysis combines the mattress adjustment information, the sound information and the pressure sensing value information, so that the first recommended adjustment parameters are obtained.
According to an embodiment of the present invention, 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 plus the second prediction parameter by a second coefficient, dividing by 2 to obtain an optimal adjustment parameter, and transmitting the optimal adjustment parameter to a mattress controller for adjustment.
It should be noted that, the invention not only analyzes the physical state data of the user with long and short periods, but also can perform predictive analysis according to the neural network model, and combines the first predictive parameters to obtain the optimal adjustment parameters. 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 and multiplying the second prediction parameter by a second coefficient, dividing by 2 to obtain an optimal adjustment parameter, and transmitting the optimal adjustment parameter to a mattress controller for adjustment. Wherein the first coefficient and the second coefficient are numbers greater than 0, which can be integers or decimal, and dividing the sum by 2 can obtain the optimal adjustment parameters. 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 physical state information of the user in the preset time period is acquired, specifically:
acquiring voiceprint information according to the sound information;
Confirming the identity of a user according to the voiceprint information to obtain user ID information;
the user ID information is sent to a server side;
And the server side acquires corresponding physical state information according to the user ID information.
The mattress can collect the voice information of the user through the voice receiver, the voice information can be the snoring voice of the user or the voice of the user when speaking, the voice information can be obtained through the voice information, and the voice information of each person is special and can be unique, so that the identity information of the user can be obtained through the voice information, and further the user ID information is obtained. And then the user ID information is sent to a server side to acquire corresponding physical state information, wherein the physical state information of the user can be pre-stored in the server or acquired by the server from other third-party platforms.
According to an embodiment of the present invention, further comprising:
Acquiring a current sleeping posture of a user;
Judging whether the optimal adjustment parameters are suitable for the sleeping posture of the current user;
If yes, adjusting according to the optimal adjustment parameters; if not, the correction of the optimal adjustment parameters is performed.
The invention can also adaptively adjust the mattress according to the sleeping posture of the user. First, the current user sleep gesture needs to be spoken. And 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 parameters are modified. The sleeping posture of the user can be obtained through judging the values of the pressure sensors distributed in the mattress, and the current sleeping posture of the user can be indirectly analyzed through the value of each sensor and the distributed positions. For example, the sensor distribution and the values are different for side sleep and for lying down sleep.
According to the embodiment of the invention, the correction for performing the optimal adjustment parameter specifically includes:
determining the most suitable posture of the current sleep period according to the current sleep posture and the body state information of the user;
Judging a mattress adjusting curve according to the sleeping posture of the current user and the most suitable posture of the current sleeping 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 the user keeps a certain posture for a long time while sleeping, the user may be unfavorable to physical health, for example, the user may easily press the heart while lying down for a long time. The present invention can detect the sleeping posture of the user in real time, then determine the optimal posture of the current sleep, and then adjust. Firstly, determining the most suitable posture of a current sleep period according to the current sleep posture and the physical state information of a user, wherein the current sleep period is a period in a whole night sleep period, and the general sleep period is divided into a deep sleep stage and a shallow sleep stage. Then, according to the most suitable posture of the current sleeping posture of the user and the current sleeping period, the mattress adjusting curve is judged, the mattress adjusting curve is a curve of time and mattress state, for example, the mattress is in an A state at the time t1, and the mattress is converted into a B state at the time t2, and the conversion 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 invention, the generation of the preset sleep neural network model is specifically as follows:
acquiring historical state data; preprocessing the historical state data to obtain a training array; transmitting the training array to an initialized neural network model for training; obtaining the error rate of the trained neural network model; and if the error rate is smaller than a preset error rate threshold, stopping training to obtain a preset sleep neural network model.
The historical state data is data of sleep, physical state and the like of the user, and the more the number of the obtained historical data is, the more accurate the trained neural network model is. Firstly, after the historical text characteristic value is obtained, preprocessing, for example, normalization processing or format conversion processing is required to be carried out on the data so as to facilitate training of the neural network, and a training data set is obtained after preprocessing. And inputting the training data set into the initialized neural network model for training, wherein the training is automatic training, and finally obtaining the behavior scoring neural network model. 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 accuracy threshold is exceeded, the sleep neural network model can reach a better prediction effect, and training can be stopped. Wherein the accuracy threshold may be 80-95%.
According to an embodiment of the present invention, further comprising:
determining snoring conditions and breathing conditions of the user according to the user sound information;
Analyzing and obtaining the asphyxia risk according to the snoring condition and the breathing state;
and if the asphyxia risk is higher than a preset threshold, sending warning information to a preset terminal.
The user's voice information can also be analyzed to obtain the voice frequency, tone level and other information, and the snoring condition and breathing state of the user can be obtained through the information. Then, according to the snoring condition and the breathing state, the asphyxia risk degree can be obtained, wherein the asphyxia risk degree is a numerical value, and the higher the numerical value is, the higher the asphyxia risk caused by snoring in sleeping is. When the suffocation risk degree is higher than a preset threshold, warning information is sent to a preset terminal to prompt the risk, wherein 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 invention, the short period coefficient, the long period coefficient, the first coefficient and the second coefficient are dynamically changed, and the coefficient determining mode specifically comprises the following steps:
acquiring physical state information of a user preset period, and calculating an optimal adjustment parameter to obtain a third prediction parameter;
acquiring body state information for presetting the 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;
If the difference rate is larger than the preset difference rate threshold, calculating a short period coefficient, a long period coefficient, a first coefficient and a second coefficient according to the fourth prediction parameter.
In the case of dynamically adjusting the short-period coefficient, the long-period coefficient, the first coefficient, and the second coefficient, the adjustment may be performed based on the user's historical physical state information. Setting a time window, namely setting a preset period, then acquiring physical state information of the preset period, and calculating to obtain a third prediction parameter. Then, in the next time window, that is, the next preset period range, a fourth prediction parameter is calculated. Comparing the difference rates of the third predicted parameter and the fourth predicted parameter, if the difference is large, indicating that the coefficient at this time does not conform to the state of the body of the latest window, the coefficient will be determined with 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 prediction result of the invention can be more accurate by determining the coefficient in a sliding window mode of the historical state data.
A third aspect of the present invention provides a computer readable storage medium having embodied therein a method program for intelligently adjusting a mattress, which when executed by a processor, implements the steps of a method for intelligently adjusting a mattress as described in any one of the preceding claims.
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 carry out self-adaptive angle adjustment and hardness adjustment according to the state of a 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 sleeping quality of the user.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or optical disk, or the like, which can store program codes.
Or the above-described integrated units of the invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
Claims (8)
1. A method of intelligently adjusting a mattress, comprising:
acquiring pressure sensing values, sound information and mattress state information of all positions in the mattress;
transmitting the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring physical 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 optimal adjustment parameters;
sending the optimal adjustment parameters to a mattress controller for adjustment;
the analysis is performed according to the pressure sensing value, the sound information, the mattress state information and the physical 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 multiplying the long period information by a long period coefficient to obtain a first prediction parameter;
Analyzing the first prediction parameters to obtain first recommended adjustment parameters;
Further comprises: 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 plus the second prediction parameter by a second coefficient, dividing by 2 to obtain an optimal adjustment parameter, and transmitting the optimal adjustment parameter to a mattress controller for adjustment.
2. The method of intelligently adjusting a mattress of claim 1, further comprising, after sending the optimal adjustment parameters to the mattress controller for adjustment: acquiring user sound information within a preset time range;
Analyzing the voice information of the user and judging whether snoring exists or not;
if the pressure sensing value exists, sending the pressure sensing value, the sound information and the mattress state information to a server side;
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 physical state information of the user for a preset period of time is obtained, specifically: acquiring voiceprint information according to the sound information;
Confirming the identity of a user according to the voiceprint information to obtain user ID information;
the user ID information is sent to a server side;
And the server side acquires corresponding physical state information according to the user ID information.
4. The method of intelligently adjusting a mattress of claim 1, further comprising: acquiring a current sleeping posture of a user;
Judging whether the optimal adjustment parameters are suitable for the sleeping posture of the current user;
If yes, adjusting according to the optimal adjustment parameters; if not, the correction of the optimal adjustment parameters is performed.
5. 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 method program for intelligently adjusting a mattress, when executed by the processor, performs the steps of:
acquiring pressure sensing values, sound information and mattress state information of all positions in the mattress;
transmitting the pressure sensing value, the sound information and the mattress state information to a server side;
acquiring physical 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 optimal adjustment parameters;
sending the optimal adjustment parameters to a mattress controller for adjustment;
the analysis is performed according to the pressure sensing value, the sound information, the mattress state information and the physical 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 multiplying the long period information by a long period coefficient to obtain a first prediction parameter;
Analyzing the first prediction parameters to obtain first recommended adjustment parameters;
Further comprises: 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 plus the second prediction parameter by a second coefficient, dividing by 2 to obtain an optimal adjustment parameter, and transmitting the optimal adjustment parameter to a mattress controller for adjustment.
6. The system for intelligently adjusting a mattress according to claim 5, further comprising, after sending the optimal adjustment parameters to the mattress controller for adjustment: acquiring user sound information within a preset time range;
Analyzing the voice information of the user and judging whether snoring exists or not;
if the pressure sensing value exists, sending the pressure sensing value, the sound information and the mattress state information to a server side;
the optimal adjustment parameters of the receiving server are adjusted again.
7. The system for intelligently adjusting a mattress according to claim 5, further comprising: acquiring a current sleeping posture of a user;
Judging whether the optimal adjustment parameters are suitable for the sleeping posture of the current user;
If yes, adjusting according to the optimal adjustment parameters; if not, the correction of the optimal adjustment parameters is performed.
8. A computer readable storage medium, characterized in that it comprises a method program for intelligently adjusting a mattress, which, when being executed by a processor, implements the steps of a method for intelligently adjusting a mattress according to any one of claims 1 to 4.
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