CN114304971B - Intelligent household soft bed based on Internet of things - Google Patents
Intelligent household soft bed based on Internet of things Download PDFInfo
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- CN114304971B CN114304971B CN202111678652.7A CN202111678652A CN114304971B CN 114304971 B CN114304971 B CN 114304971B CN 202111678652 A CN202111678652 A CN 202111678652A CN 114304971 B CN114304971 B CN 114304971B
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Abstract
The invention discloses an intelligent household soft bed based on the Internet of things, and belongs to the field of intelligent consumption equipment. An intelligent household soft bed based on the Internet of things comprises a processor and a detection contact positioned on the upper surface of the soft bed, wherein the detection contact comprises a receiving film made of a piezoelectric material and a compression rod made of a rigid material; the receiving film is attached to the surface of the skin to receive the muscle tension reflection signal and transmit the muscle tension reflection signal to the processor; the top of the compression rod protrudes out of the upper surface of the soft bed to receive the muscle hardness of the abutted skin and transmit the muscle hardness to the processor; the processor controls the fluctuation range of the surface of the soft bed according to the received information; it can realize that the intelligent analysis user is fit for what kind of appearance of sleeping, adjusts the appearance of sleeping when the user sleeps deeply, under the circumstances of guaranteeing that the user sleeps, carries out accurate regulation and control to user's sleep health.
Description
Technical Field
The invention belongs to the field of intelligent consumption equipment, and particularly relates to an intelligent household soft bed based on the Internet of things.
Background
The physical condition of each person determines the appropriate sleeping position for each person.
Due to factors such as muscle habits, a person can automatically adjust to a habitual sleeping posture when sleeping, but the habitual sleeping posture is unhealthy and aggravates sleeping discomfort, and the habitual sleeping posture aggravates fatigue of the person for a long time.
The healthy sleeping postures corresponding to different people are as follows: the pregnant woman is suitable for lying on the left side; the baby is suitable for lying on the stomach, the snorer is suitable for lying on the left side or the right side, the patient suffering from neck and back is suitable for lying on the left side or the right side, the patient suffering from gastroesophageal reflux is suitable for lying on the back with a raised upper cushion, and the patient suffering from waist is suitable for lying on the back with a raised lower cushion.
The existing intelligent furniture capable of adjusting the sleeping posture only sets one sleeping posture to be determined as the healthy sleeping posture, cannot meet the healthy sleeping requirements of all people, is easy to wake up the sleeping people when adjusting the sleeping posture, cannot adjust the sleeping posture to enable the sleeping state to be better, but also enables the user to be difficult to fall asleep, and has reverse side effect.
Disclosure of Invention
The invention aims to provide an intelligent household soft bed based on the Internet of things, which can intelligently analyze what kind of sleeping posture a user is suitable for, adjust the sleeping posture of the user when the user sleeps well, and accurately adjust and control the sleeping health of the user under the condition of ensuring the sleeping of the user.
The invention discloses an intelligent household soft bed based on the Internet of things, which comprises a processor and a detection contact positioned on the upper surface of the soft bed, wherein the detection contact comprises a receiving film made of a piezoelectric material and a compression rod made of a rigid material; the receiving film is attached to the surface of the skin to receive the muscle tension reflection signal and transmit the muscle tension reflection signal to the processor; the top of the compression rod protrudes out of the upper surface of the soft bed to receive the muscle hardness of the abutted skin and transmit the muscle hardness to the processor; the processor controls the fluctuation amplitude of the surface of the soft bed according to the received information.
The invention is further improved, and comprises an acquisition layer, a cushion layer and a base layer which are sequentially superposed from top to bottom; the acquisition layer is sequentially divided into a head-neck region, a trunk region and a shin-thigh region along the length direction, the detection contacts are uniformly distributed in the head-neck region, the trunk region and the shin-thigh region, and a substrate of the acquisition layer is made of a flexible material; the cushion layer comprises an elastic component which is abutted with the acquisition layer and is controlled to deform by the processor; the base layer is a rigid component; the pressed rods of the detection contacts in different zones protrude at different heights, which are preset by the processor.
As a further improvement of the invention, the preset reference of the height is the distance from the surface of the acquisition layer at each position of the back curve of the human body.
As a further improvement of the invention, the pressure-bearing rod is arranged in the acquisition layer in a sliding manner in the vertical direction, and the sliding is controlled and driven by the processor.
As a further improvement of the invention, the medical examination arm sleeve is included; the physical examination arm sleeve is fixedly arranged on the outer side of the trunk area in the width direction; the physical examination arm sleeve is divided into an upper arm sleeve and a lower arm sleeve, and the upper arm sleeve is rotatably connected with the lower arm sleeve; the lower arm sleeve is a fixing piece, and the inner wall of the lower arm sleeve is provided with a detection point which is used for collecting pulse information, and the pulse information is transmitted to the processor through a network; the upper arm sleeve is a rotating part, and the rotation is controlled and driven by the processor.
As a further improvement of the invention, the health examination bracelet is included; the physical examination bracelet is connected with the processor through a network; the physical examination bracelet is sleeved on the wrist of the human body to collect pulse information.
As a further improvement of the invention, the device comprises an auxiliary acquisition part, wherein the auxiliary acquisition part acquires at least one of sound information, image information or physical condition information of a user of the soft bed; supplementary collection piece and treater electric connection, the information of supplementary collection piece collection is collected by the treater.
As a further improvement of the invention, the operation steps comprise:
s10, enabling a user to lie on the collection layer with the back side skin exposed, enabling the compression rods abutted against the skin of the human body to collect stress data, and enabling the receiving membranes abutted against the skin of the human body to collect muscle tension reflection frequency data; the stress magnitude data and the muscle tonus reflex frequency data are fed back to the processor; the processor judges the sleeping postures which are beneficial to the health of the user, wherein the sleeping postures comprise left-side sleeping, right-side sleeping, upper cushion high lying on the back, lower cushion high lying on the back and lying on the front;
s20, the processor judges whether the user falls asleep or not according to the pulse information and/or the information acquired by the auxiliary acquisition piece, if so, the processor enters S30, and if not, the processor loops S20;
s30, judging the sleeping posture used by the user according to the number and the positions of the detection contacts triggered in the head-neck area, the trunk area and the shin-thigh area by the processor, and comparing the sleeping posture with the sleeping posture beneficial to the health of the user to judge whether the sleeping postures are the same or not; if yes, loop S30; if not, the step goes to S40;
s40, the processor judges the body axis of the user according to the triggered detection touch point of the trunk area; according to the position of the axis of the body and the sleeping posture beneficial to the health of the user, the processor judges the number and the position of the detection contacts which are required to be triggered by the user;
s50, the processor drives the elastic component to deform in the vertical direction, drives the body of the user to move, and covers all detection contacts to be triggered; the deformation amplitude of the elastic component is 0.5-1.5 cm/s; the processor judges whether the user is awakened in real time according to the information acquired by the auxiliary acquisition part; if yes, stopping deformation and returning to S20; if not, the elastic component continuously deforms until all detection contacts to be triggered are covered and the step S60 is carried out;
s60, in the sleeping state of the user, the processor judges whether the user is comfortable when sleeping according to the stress magnitude data and the muscle stress reflex frequency data collected by the detection contact and the comparison of the initially set threshold; if yes, returning to S30; if not, the pressure bar 42 covered by the user is finely adjusted in the vertical direction at a deformation frequency of 0.2-0.5 cm/S until the user is comfortable during sleeping, and the process returns to S30.
As a further improvement of the present invention, in step S10, the stress magnitude data and the muscle tone reflex frequency data are acquired N times per second, and the fluctuation value of the data per second is X; after the data acquisition is started, the processor limits the data acquisition within M seconds, after the sum of all the X data is equal to or smaller than a limited threshold value, the average value of the stress magnitude data and the muscle tension reflex frequency data acquired in Y seconds is used as correct data, and the correct data is acquired by the processor and used for judging the sleeping posture beneficial to the health of the user.
As a further improvement of the invention, the factors of the sleeping posture which are beneficial to the health of the user and are determined by the processor comprise a snoring condition, a pregnant condition, an age condition and a sick condition which are input to the processor by the auxiliary acquisition element.
Compared with the prior art, the invention has the beneficial effects that:
the invention is beneficial to judging the part of the user used as the supporting surface by detecting the muscle hardness and the muscle tension reflection frequency so as to determine the proper and healthy sleeping posture.
The invention judges the physical condition of the user through the detection contact, the sound receiver, the visual camera, the physical examination arm sleeve and the like so as to accurately analyze the proper and healthy sleeping posture in real time.
The deformation amplitude of the elastic component is 0.5-1.5 cm/s, the action is soft, a user is not easy to awaken, and the deformation of the elastic component is performed after the user falls asleep, so that the sleep quality of the user is effectively ensured.
Drawings
FIG. 1 is a schematic perspective view of the present invention;
FIG. 2 is a schematic perspective view of the detection contact according to the present invention;
FIG. 3 is a schematic perspective view of the lower arm cover of the present invention;
FIG. 4 is a flowchart illustrating the operation of the present invention.
The reference numbers in the figures illustrate:
the medical examination arm sleeve comprises a collection layer 1, a head and neck region 11, a trunk region 12, a shin and thigh region 13, a cushion layer 2, a base layer 3, a detection contact 4, a receiving film 41, a compression rod 42, a physical examination arm sleeve 5 and a detection point 51.
Detailed Description
The first embodiment is as follows: please refer to fig. 1-4, which illustrate an intelligent home soft bed based on the internet of things, comprising a collection layer 1, a soft cushion layer 2 and a base layer 3, which are sequentially stacked from top to bottom.
The surface of the acquisition layer 1 is provided with a plurality of detection contacts 4, and the substrate of the acquisition layer 1 is made of flexible material; the acquisition layer 1 is divided into a head and neck region 11, a torso region 12 and a shin and thigh region 13 in sequence along the length direction; the detection contacts 4 of the head and neck region 11, the torso region 12 and the tibiofemoral region 13 are all evenly distributed.
The detection contact 4 includes a receiving film 41 made of a piezoelectric material and a pressure receiving rod 42 made of a rigid material; the receiving film 41 is attached to the surface of the skin to receive the muscle tension reflection signal and transmit the muscle tension reflection signal to the processor; the top of the compression rod 42 protrudes out of the upper surface of the soft bed to receive the muscle hardness of the abutted skin and transmit the muscle hardness to the processor; the receiving film 41 is a piezoelectric film sensor and is in a sucker shape; the compression rod 42 is a plastic rod with a round head at the top end; the receiving film 41 is fixedly arranged on the upper surface of the acquisition layer 1, and the pressed rod 42 protrudes upwards through the center of the receiving film 41;
when the spine or soft tissues are diseased or fatigued, muscles of corresponding parts can be hardened to protect nerves and bones at the parts, which is an operation mechanism for self-protection of a human body, and when the hardness of the muscles exceeds a normal value, the muscles are proved to be incapable of being stressed and cannot be used as a supporting surface during sleeping;
muscle tension occurs due to muscle hardening, the muscle tension is due to slow and continuous traction of the muscle, the whole muscle is in a continuous and weak contraction state to prevent the muscle from being elongated, and different muscle fibers in the same muscle alternately contract in the muscle tension reaction process, so the muscle tension reaction can occur permanently and the muscle tension reaction is not easy to fatigue, which is an operation mechanism for human body self-protection;
the muscle mass of different people is different, so that the detection result has errors, and the muscle tension of people who exercise frequently is greater than that of people who do not exercise frequently; the muscle tonus reflex frequency of different people is different, and the muscle tonus reflex frequency of people with pathological changes in nerve center is enhanced or weakened compared with that of normal people; therefore, the data of muscle hardness and muscle tension reflection frequency are introduced simultaneously, and whether the detected part is suitable for being used as the supporting surface of the body during sleeping is considered through two-phase synthesis, namely, only the part with the muscle hardness higher than a normal value and the muscle tension frequency higher than the normal value is considered to be not suitable for being used as the supporting surface of the body during sleeping.
Meanwhile, the pressed rods 42 of the detection contacts 4 in different zones protrude at different heights, which are preset by the processor; the preset reference is the distance from each position of the human body back side curve to the surface of the acquisition layer 1, namely the compression rods 42 at different positions are abutted against the human body back side curve in a free state, and the height of the top end of each compression rod 42 is 1-2 cm higher than the corresponding coordinate point of the human body back side curve in the free state; such an arrangement allows measurement of the stiffness of the muscles of the back side of the body without resulting in contact comfort for the user.
The cushion layer 2 comprises an elastic component abutting the acquisition layer 1 and being deformed by the processor; the elastic component can adopt a spring with an electromagnet or an air bag with a sufficient amount controlled by an air pump, and various solutions are provided in the prior art and are not described herein; in order to make the present embodiment fully disclosed, the present embodiment adopts a scheme that the elastic component is an air pump which controls the air bag at best, and the air pump in the scheme is controlled by the processor; after the air pump is started to inflate, the air bag expands, a bulge is generated at the position corresponding to the acquisition layer 1, and the more the inflation amount is, the greater the bulge degree is; after the air pump sucks air, the air bag collapses, a recess is generated at the position corresponding to the acquisition layer 1, and the more the air displacement is, the larger the recess degree is.
The base layer 3 is a rigid member; the base layer 3 is a base of the cushion layer 2, and the processor is positioned in the base layer 3 and used for protecting the processor from being damaged; the processor is wired to the piezoelectric film sensor, and the pressure sensor is provided on the lower side of the pressure receiving rod 42 and wired to the processor.
The pressed rod 42 is arranged to slide vertically within the acquisition layer 1, said sliding being driven by the processor control; when a user sleeps well and keeps the sleeping posture set by the processor, the pressed rod 42 can be retracted into the acquisition layer 1, so that the surface of the soft bed is smooth, and the experience feeling is facilitated.
The soft bed also comprises a physical examination arm sleeve 5; the physical examination arm sleeve 5 is fixedly arranged at the outer side of the trunk area 12 in the width direction; the physical examination arm sleeve 5 is divided into an upper arm sleeve and a lower arm sleeve which are rotatably connected; the lower arm sleeve is a fixed part, the inner wall of the lower arm sleeve is provided with a detection point 51, the detection point 51 is used for collecting pulse information, and the pulse information is transmitted to the processor through a network; the upper arm sleeve is a rotating part, and the rotation is controlled and driven by the processor; when a user lies down to prepare for sleeping, the user needs to put arms in the physical examination arm sleeve 5 to detect pulses, the physical examination arm sleeve 5 is positioned on the outer side of the trunk area 12 in the width direction, so that the body parts of the user after lying down correspond to the head and neck area 11, the trunk area 12 and the tibiofemoral area 13 which are divided by the acquisition layer 1, namely, the head and neck are positioned in the head and neck area 11, the hands, the chest and the waist are positioned in the trunk area 12, the buttocks, the thighs, the crus and the feet are positioned in the tibiofemoral area 13, and the body axis of the user is parallel to the length direction of the soft bed; the physical examination arm sleeve 5 is convenient for pairing the body positions of the information of muscle hardness and muscle tension reflection frequency, so that the work of a processor is reduced; the pulse information is used for judging whether the user enters a sleep state, and the pulse frequency is reduced after the user enters the sleep state and can be used as a basis for judging whether the user enters the sleep state; meanwhile, the pulse can also detect whether the user has the symptom of nervous center pathological change or not, and the pulse is used as an auxiliary basis for judging whether the frequency of the muscle tension reflex is normal or not; after the processor collects the pulse information, the upper arm sleeve can be controlled to be loosened, so that a user can freely rotate the arm to change the sleeping posture during sleeping.
A sound receiver, a visual camera and a network background are arranged outside the soft bed; the sound receiver, the visual camera and the network background are all communicated with a processor network or a circuit; the sound receiving device receives sound to the surrounding environment of the user after the processor judges that the user enters the sleep state, and when the similarity between the recorded sound waveforms and the waveform of the snoring sound exceeds 75%, the user is judged to be in the snoring state, and the appropriate sleeping posture of the snorer is left side lying or right side lying; the vision camera is controlled to be turned on by the processor when a user is in bed, records the body shape of the user and is used as an auxiliary basis for judging the identity state of the user, if the user is judged to be a baby or a pregnant woman, the baby is in a lying prone position in a proper sleeping posture, and the pregnant woman is in a left side lying position in a proper sleeping posture; the network background can transmit the illness state of the user to the processor by using a network, and the illness state is used as an auxiliary basis for judging whether the user is ill, such as judging that the user suffers from the gastroesophageal reflux disease, and the person suffering from the gastroesophageal reflux disease is in a high-cushion and supine state.
In the prior art, methods and steps for adjusting the sleeping posture of a user by driving an elastic member are not described herein.
The soft bed operation steps comprise:
s10, enabling a user to lie on the collection layer 1 with the back side skin exposed, collecting stress data by the compression rods 42 abutted against the skin of the human body, and collecting muscular tension reflection frequency data by the receiving membranes 41 abutted against the skin of the human body; the stress magnitude data and the muscle tonus reflex frequency data are fed back to the processor; the processor judges sleeping postures beneficial to the health of a user according to the acquired stress magnitude data and the muscle tension reflection frequency data, wherein the sleeping postures comprise left-side sleeping, right-side sleeping, upper cushion high supine, lower cushion high supine and lying prone; if the over-hard muscle is detected to be positioned on the left side of the back of the neck, judging that the healthy sleeping posture is right-side lying; if the detected over-hard muscle is positioned on the right side of the back of the neck, judging that the healthy sleeping posture is left side lying; if the over-hard muscle is detected to be positioned in the middle of the back of the neck, judging that the healthy sleeping posture is left-side lying or right-side lying; if the over-hard muscle is detected to be positioned at the waist, judging the healthy sleeping posture to be a low-cushion high-lying state;
the stress magnitude data and the muscle stress reflex frequency data are collected 5 times per second, and the fluctuation value of the data in each second is X; after the data acquisition is started, the processor limits the data to be acquired within 3 seconds, after the sum of all the xs is equal to or smaller than a limited threshold value, the average value of the stress magnitude data and the muscular tonus reflex frequency data acquired in 4 seconds is correct data, and the correct data is acquired by the processor and used for judging the sleeping posture beneficial to the health of a user;
s20, the processor judges whether the user falls asleep according to the pulse information, the information collected by the sound collector and the visual camera, if so, the processor enters S30, and if not, the processor loops S20;
s30, the processor judges the sleeping posture used by the user according to the number and the positions of the detection contacts 4 triggered in the head and neck area 11, the trunk area 12 and the shin and thigh area 13, and compares the sleeping posture with the sleeping posture beneficial to the health of the user to judge whether the sleeping postures are the same or not; if yes, loop S30; if not, the step S40 is entered;
s40, the processor judges the body axis of the user according to the detection contact 4 triggered by the trunk area 12; according to the position of the axis of the body and the sleeping posture beneficial to the health of the user, the processor judges the number and the position of the detection contacts 4 which are triggered by the user;
s50, the processor drives the elastic component to deform in the vertical direction, drives the body of the user to move, and covers all the detection contacts 4 to be triggered; the deformation amplitude of the elastic component is 0.5-1.5 cm/s; the processor judges whether the user is awakened in real time according to the information acquired by the auxiliary acquisition part; if yes, stopping deformation and returning to S20; if not, the elastic component continuously deforms until all the detection contacts 4 to be triggered are covered and the step S60 is carried out;
s60, in the sleeping state of the user, the processor judges whether the user is comfortable during sleeping by comparing the stress magnitude data and the muscle stress reflex frequency data collected by the detection contact 4 with the initially set threshold; if yes, returning to S30; if not, the pressure bar 42 covered by the user is finely adjusted in the vertical direction at a deformation frequency of 0.2-0.5 cm/S until the user is comfortable during sleeping, and the process returns to S30.
The second concrete embodiment: different from the first embodiment, the soft bed operation steps comprise:
s10, enabling a user to lie on the collection layer 1 with the back side skin exposed, collecting stress data by the compression rods 42 abutted against the skin of the human body, and collecting muscular tension reflection frequency data by the receiving membranes 41 abutted against the skin of the human body; the stress magnitude data and the muscle tonus reflex frequency data are fed back to the processor; the processor judges sleeping postures beneficial to the health of a user according to the acquired stress magnitude data, the muscle tension reflection frequency data, the identity state data recorded by the visual camera and the sick data recorded by the network background, wherein the sleeping postures comprise left-side sleeping, right-side sleeping, upper cushion lying on the back, lower cushion lying on the back and lying on the front; if the detected over-hard muscle is positioned on the left side of the back of the neck, judging that the healthy sleeping posture is right side lying; if the over-hard muscle is detected to be positioned at the right side of the back of the neck, judging that the healthy sleeping posture is left-side lying; if the over-hard muscle is detected to be positioned in the middle of the back of the neck, judging that the healthy sleeping posture is left-side lying or right-side lying; if the over-hard muscle is detected to be positioned at the waist, judging the healthy sleeping posture to be a low-cushion high-lying state; if the user at the detection position is a baby, judging that the healthy sleeping posture is lying prone; if the user at the detection position is a woman, judging that the healthy sleeping posture is left side lying;
the stress magnitude data and the muscle tonus reflex frequency data are acquired 5 times per second, and the fluctuation value of the data in each second is X; after the data acquisition is started, the processor limits the data to be acquired within 3 seconds, after the sum of all the xs is equal to or smaller than a limited threshold value, the average value of the stress magnitude data and the muscular tonus reflex frequency data acquired in 4 seconds is correct data, and the correct data is acquired by the processor and used for judging the sleeping posture beneficial to the health of a user;
s20, the processor judges whether the user falls asleep according to the pulse information, the information collected by the sound collector and the visual camera, if the user falls asleep, the processor updates the healthy sleeping posture of the user with the information newly recorded in S20 and enters S30, and if the user does not fall asleep, the processor loops S20;
s30, the processor judges the sleeping posture used by the user according to the number and the positions of the detection contacts 4 triggered in the head and neck area 11, the trunk area 12 and the shin and thigh area 13, and compares the sleeping posture with the sleeping posture beneficial to the health of the user to judge whether the sleeping postures are the same or not; if yes, loop S30; if not, the step goes to S40;
s40, the processor judges the body axis of the user according to the triggered detection contact 4 of the trunk area 12; according to the position of the axis of the body and the sleeping posture beneficial to the health of the user, the processor judges the number and the position of the detection contacts 4 which are triggered by the user;
s50, the processor drives the elastic component to deform in the vertical direction, drives the body of the user to move, and covers all the detection contacts 4 to be triggered; the deformation amplitude of the elastic component is 0.5-1.5 cm/s; the processor judges whether the user is awakened in real time according to the information acquired by the auxiliary acquisition piece; if yes, stopping deformation and returning to S20; if not, the elastic part continuously deforms until all the detection contacts 4 to be triggered are covered and the process goes to S60;
s60, in the sleeping state of the user, the processor judges whether the user is comfortable during sleeping by comparing the stress magnitude data and the muscle stress reflex frequency data collected by the detection contact 4 with the initially set threshold; if yes, returning to S30; if not, the compression bar 42 covered by the user is finely adjusted in the vertical direction at a deformation frequency of 0.2-0.5 cm/S until the user is comfortable during sleeping, and the process returns to S30.
The third concrete embodiment: on the basis of the first or second embodiment, if the processor determines that the healthy sleeping posture of the user is left-side lying or right-side lying, and the user enters sleep in the left-side lying or right-side lying state, the processor calculates the sleep time for keeping the user left-side lying or right-side lying, and after a set time (in this embodiment, the set time is 1 hour), the processor controls the elastic component to drive the user to adjust the sleeping posture, so that the user changes from left-side lying to right-side lying or from right-side lying to left-side lying; reduce the continuous pressure of the viscera at one side, and is beneficial to protecting the health of the viscera. The procedure of the adjustment process is the same as step S50.
The fourth concrete embodiment: different from the first embodiment, the second embodiment or the third embodiment, the physical examination arm sleeve 5 is replaced by a physical examination bracelet; the physical examination bracelet is connected with the processor through a network; human wrist department is located to physical examination bracelet cover, gathers pulse information for the detection means is more nimble, and the free space of user's activity is bigger.
Claims (10)
1. The utility model provides a soft bed of intelligence house based on thing networking which characterized in that: the detection contact (4) is positioned on the upper surface of the soft bed, and the detection contact (4) comprises a receiving film (41) made of piezoelectric material and a compression rod (42) made of rigid material; the receiving film (41) is attached to the surface of the skin to receive the muscle tension reflection signal and transmit the muscle tension reflection signal to the processor; the top of the compression rod (42) protrudes out of the upper surface of the soft bed to receive the muscle hardness at the abutted skin and transmit the muscle hardness to the processor; the processor controls the fluctuation range of the surface of the soft bed according to the received information; the processor judges the sleeping posture beneficial to the health of the user according to the stress data of the pressure rod (42) and the muscle tension reflection frequency data of the receiving membrane (41); the processor judges the sleeping posture used by the user according to the number and the position of the triggered detection contacts (4) and compares the sleeping posture with the sleeping posture beneficial to the health of the user; the processor judges the position of the bed surface which adjusts the sleeping posture used by the user to the healthy sleeping posture which should fluctuate; the processor controls the bed surface to fluctuate only when the user is asleep.
2. The smart home soft bed based on the Internet of things according to claim 1, characterized in that: comprises an acquisition layer (1), a cushion layer (2) and a base layer (3) which are sequentially superposed from top to bottom; the acquisition layer (1) is sequentially divided into a head-neck area (11), a trunk area (12) and a shin-thigh area (13) along the length direction, the detection contacts (4) are uniformly distributed in the head-neck area (11), the trunk area (12) and the shin-thigh area (13), and a substrate of the acquisition layer (1) is made of a flexible material; the cushion layer (2) comprises an elastic component which is abutted with the acquisition layer (1) and is subjected to deformation controlled by a processor; the base layer (3) is a rigid component; the pressed rods (42) of the detection contacts (4) in different zones protrude to different heights, which are preset by a processor.
3. The smart home soft bed based on the Internet of things according to claim 2, characterized in that: the preset reference of the height is the distance from each position of the back curve of the human body to the surface of the acquisition layer (1).
4. The smart home soft bed based on the Internet of things according to claim 3, characterized in that: the pressed rod (42) is arranged in a vertical sliding manner in the acquisition layer (1), and the sliding is controlled and driven by the processor.
5. The smart home soft bed based on the Internet of things according to claim 4, wherein: comprises a physical examination arm sleeve (5); the physical examination arm sleeve (5) is fixedly arranged on the outer side of the trunk area (12) in the width direction; the physical examination arm sleeve (5) is divided into an upper arm sleeve and a lower arm sleeve, and the upper arm sleeve is rotatably connected with the lower arm sleeve; the lower arm sleeve is a fixing piece, a detection point (51) is arranged on the inner wall of the lower arm sleeve, the detection point (51) is used for collecting pulse information, and the pulse information is transmitted to the processor through a network; the upper arm sleeve is a rotating part, and the rotation is controlled and driven by the processor.
6. The smart home soft bed based on the Internet of things according to claim 4, wherein: comprises a physical examination bracelet; the physical examination bracelet is connected with the processor through a network; the physical examination bracelet is sleeved on the wrist of the human body to collect pulse information.
7. The smart home soft bed based on the Internet of things of claim 5 or 6, which is characterized in that: the device comprises an auxiliary acquisition part, a control part and a display part, wherein the auxiliary acquisition part acquires at least one of sound information, image information or physical condition information of a user in the soft bed; supplementary collection piece and treater electric connection, the information of supplementary collection piece collection is collected by the treater.
8. The smart home soft bed based on the Internet of things according to claim 7, wherein: the operation steps comprise:
s10, enabling a user to lie on the back of the exposed back skin of the user on the acquisition layer (1), acquiring stress data by each pressure rod (42) abutted against the skin of the human body, and acquiring muscular tension reflection frequency data by each receiving film (41) abutted against the skin of the human body; the stress magnitude data and the muscle stress reflex frequency data are fed back to the processor; the processor judges the sleeping postures which are beneficial to the health of the user, and the sleeping postures comprise left side sleeping, right side sleeping, upper cushion height lying on the back, lower cushion height lying on the back and lying on the front;
s20, the processor judges whether the user falls asleep or not according to the pulse information and/or the information acquired by the auxiliary acquisition piece, if so, the processor enters S30, and if not, the processor loops S20;
s30, the processor judges the sleeping posture used by the user according to the number and the positions of the detection contacts (4) triggered in the head-neck area (11), the trunk area (12) and the shin-thigh area (13), and compares the sleeping posture with the sleeping posture beneficial to the health of the user to judge whether the sleeping postures are the same or not; if yes, loop S30; if not, the step S40 is entered;
s40, the processor judges the body axis of the user according to the detection contact (4) triggered by the trunk area (12); according to the position of the axis of the body and the sleeping posture which is beneficial to the health of a user, the processor judges the number and the position of the detection contacts (4) which are required to be triggered by the user;
s50, the processor drives the elastic component to deform in the vertical direction, drives the body of the user to move, and covers all detection contacts (4) to be triggered; the deformation amplitude of the elastic component is 0.5-1.5 cm/s; the processor judges whether the user is awakened in real time according to the information acquired by the auxiliary acquisition part; if yes, stopping deformation and returning to S20; if not, the elastic part continuously deforms until all the detection contacts (4) to be triggered are covered and the process goes to S60;
s60, in the sleeping state of the user, the processor judges whether the user is comfortable or not in the sleeping state by comparing the stress magnitude data and the myotonic reflex frequency data collected by the detection contact (4) with an initial set threshold; if yes, returning to S30; if not, the pressure bar (42) covered by the user is finely adjusted in the vertical direction at a deformation frequency of 0.2-0.5 cm/S until the user is comfortable during sleeping, and the process returns to S30.
9. The smart home soft bed based on the Internet of things according to claim 8, characterized in that: in step S10, acquiring stress magnitude data and muscle tonus reflex frequency data N times per second, wherein the fluctuation value of the data in each second is X; after the data acquisition is started, the processor limits the data acquisition within M seconds, after the sum of all the X data is equal to or smaller than a limited threshold value, the average value of the stress magnitude data and the muscle tension reflex frequency data acquired in Y seconds is used as correct data, and the correct data is acquired by the processor and used for judging the sleeping posture beneficial to the health of the user.
10. The smart home soft bed based on the Internet of things according to claim 8, characterized in that: the factors for the processor to determine the sleeping posture which is beneficial to the health of the user comprise a snoring condition, a pregnant condition, an age condition and a diseased condition which are input to the processor by the auxiliary acquisition element.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002224072A (en) * | 2001-02-02 | 2002-08-13 | Mazda Motor Corp | Muscular fatigue evaluating device, muscular fatigue evaluating method, computer program for executing this method and storage medium for storing this computer program |
| JP2006340942A (en) * | 2005-06-10 | 2006-12-21 | Sato Company:Kk | Mattress and bed with mattress |
| CN108175219A (en) * | 2017-12-11 | 2018-06-19 | 绵眠（上海）智能科技有限公司 | A kind of air bag sleep method for supporting and system based on pressure distribution |
| CN111610050A (en) * | 2020-06-30 | 2020-09-01 | 广东珞珈睡眠科技有限公司 | Mattress hardness distribution autonomous control system |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105380762B (en) * | 2014-09-05 | 2018-12-04 | 深圳市三分之一睡眠科技有限公司 | A kind of bed and its adjusting method of automatic adjustment |
| JP6766052B2 (en) * | 2015-01-27 | 2020-10-07 | アップル インコーポレイテッドＡｐｐｌｅ Ｉｎｃ． | Systems and methods for determining sleep quality |
| CN109645779A (en) * | 2018-12-20 | 2019-04-19 | 佛山市乙太医疗用品有限公司 | A kind of stress induction self-regulation waist pillow |
| TWM591795U (en) * | 2019-12-11 | 2020-03-11 | 醫博科技股份有限公司 | Supporting device adjusting system and supporting device |
-
2021
- 2021-12-31 CN CN202111678652.7A patent/CN114304971B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002224072A (en) * | 2001-02-02 | 2002-08-13 | Mazda Motor Corp | Muscular fatigue evaluating device, muscular fatigue evaluating method, computer program for executing this method and storage medium for storing this computer program |
| JP2006340942A (en) * | 2005-06-10 | 2006-12-21 | Sato Company:Kk | Mattress and bed with mattress |
| CN108175219A (en) * | 2017-12-11 | 2018-06-19 | 绵眠（上海）智能科技有限公司 | A kind of air bag sleep method for supporting and system based on pressure distribution |
| CN111610050A (en) * | 2020-06-30 | 2020-09-01 | 广东珞珈睡眠科技有限公司 | Mattress hardness distribution autonomous control system |
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