CN113633277A - Intelligent mattress with health monitoring function - Google Patents
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- 230000036541 health Effects 0.000 title claims abstract description 68
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- 230000007958 sleep Effects 0.000 claims abstract description 60
- 230000001133 acceleration Effects 0.000 claims abstract description 29
- 238000001514 detection method Methods 0.000 claims abstract description 17
- 238000004458 analytical method Methods 0.000 claims abstract description 6
- 230000003860 sleep quality Effects 0.000 claims description 31
- 238000000034 method Methods 0.000 claims description 14
- 230000000747 cardiac effect Effects 0.000 claims description 12
- 238000007405 data analysis Methods 0.000 claims description 10
- 230000008667 sleep stage Effects 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 9
- 230000029058 respiratory gaseous exchange Effects 0.000 claims description 9
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- 230000000737 periodic effect Effects 0.000 claims description 7
- 239000011159 matrix material Substances 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
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- 238000010586 diagram Methods 0.000 claims description 5
- 229920000742 Cotton Polymers 0.000 claims description 4
- 206010062519 Poor quality sleep Diseases 0.000 claims description 3
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1102—Ballistocardiography
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
- A61B5/346—Analysis of electrocardiograms
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4815—Sleep quality
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
- A61B5/6892—Mats
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Abstract
The utility model belongs to the field of medical care facilities, and discloses an intelligent mattress with health monitoring function, which comprises an intelligent mattress and a multi-sensor data acquisition pad, wherein the intelligent mattress is provided with the multi-sensor data acquisition pad, the multi-sensor data acquisition pad comprises a piezoelectric sensor acquisition module and an acceleration sensor acquisition module, the outer side of the intelligent mattress is provided with a data analyzer, the data analyzer is in electric signal connection with the piezoelectric sensor acquisition module and the acceleration sensor acquisition module, the scheme can realize that non-camera and non-wearable passive detection are formed to collect data through the laying of the multi-sensor data acquisition pad, interference information is removed through hidden Markov model algorithm analysis to obtain more accurate and comprehensive sleep health data information, information sharing is carried out through a wireless network, a health monitoring platform is established, and targeted sleep related services are provided, the professional and the accuracy of the sleep health monitoring are improved, and better use experience is brought.
Description
Technical Field
The application relates to the field of medical care facilities, in particular to an intelligent mattress with a health monitoring function.
Background
Health is a constant topic of human life, while a healthy body cannot leave enough sleep, and the sleep can promote physical strength and mental recovery and memory consolidation, and is an indispensable part in life activities. Sleep quality affects the health and longevity of a person. Therefore, improving sleep quality is a prerequisite to ensure quality of life, improve work efficiency and maintain physical health. When information is rapidly developed, the attention of modern people to health is higher and higher, health preservation and health care become higher pursuits of modern people, and detection of sleep quality becomes the most popular topic at present.
People in various industries in the society face great mental stress, insomnia or low sleep quality become common diseases of many modern people, and some people still have the problem of low sleep efficiency, but still feel insufficient sleep and tired and hypodynamia although the sleep time is more than 8 hours. Therefore, insomnia and low sleep quality become common phenomena affecting life, work and health of modern people, and most of the existing sleep health monitoring facilities are very complex and are in contact with human bodies, so that physical and psychological conflicts are generated for people, and data collection of sleep health monitoring is affected.
Disclosure of Invention
1. Technical problem to be solved
The intelligent mattress with the health monitoring function can be laid through a multi-sensor data acquisition pad (2), a non-camera is formed, non-wearable passive detection is carried out to collect data, interference information is removed through hidden Markov model algorithm analysis, more accurate and comprehensive sleep health data information is obtained, information sharing is carried out through a wireless network, a health monitoring platform is established, targeted sleep related services are provided, the professional and accuracy of sleep health monitoring are improved, and better use experience is brought.
2. Technical scheme
In order to solve the above problems, the present application adopts the following technical solutions.
An intelligent mattress with a health monitoring function comprises an intelligent mattress and a multi-sensor data acquisition pad, wherein the intelligent mattress is provided with the multi-sensor data acquisition pad, the multi-sensor data acquisition pad comprises a piezoelectric sensor acquisition module and an acceleration sensor acquisition module, a data analyzer is arranged on the outer side of the intelligent mattress and is in electric signal connection with the piezoelectric sensor acquisition module and the acceleration sensor acquisition module, the data analyzer is internally provided with a data analysis module and is in signal connection with a health monitoring platform, the health monitoring platform comprises a cloud end, a mobile end and a medical end, a serial bus of the data analyzer is connected with a storage hard disk, the storage hard disk is positioned in the data analyzer, the data analyzer is in signal connection with the mobile end and the medical end, and a regulating device is arranged in the intelligent mattress, the adjusting device comprises a lifting pad and a small air pump, the multi-sensor data acquisition pad can be laid to form a non-camera and non-wearable passive detection to collect data, interference information is removed through hidden Markov model algorithm analysis to obtain more accurate and comprehensive sleep health data information, information sharing is performed through a wireless network, a health monitoring platform is established, targeted sleep related services are provided, the professional and accuracy of sleep health monitoring are improved, and better use experience is brought.
Furthermore, the piezoelectric sensor acquisition module collects the heart impact signals, the acceleration sensor acquisition module collects the sleeping body movement values, the heart impact signals are presented on a data analyzer as W-shaped cardiac periodic waveforms, one cardiac periodic waveform comprises H waves, I waves, J waves, K waves, L waves, M waves and N waves, the detection range of the piezoelectric sensor acquisition module is more than 80dB, the frequency of the heart impact signal is 100Hz, the method that the piezoelectric sensor acquisition module reflects the physiological information through the piezoelectric signal is adopted, can minimize the influence of sleep data collection on sleep, realize the application of family sleep monitoring, improve the accuracy of detected data, the body movement in the sleeping process can be detected by adopting the acceleration sensor acquisition module, so that the optimization of the detection data is carried out, and the accuracy of the detection data is further improved.
Further, the data analyzer processes the data collected by the piezoelectric sensor collecting module and the acceleration sensor collecting module by using a hidden markov model algorithm, wherein the hidden markov model comprises the following elements:
number N of all possible hidden states of HMM;
the number of observed states M;
state transition probability matrix: a ═ aij}
Wherein a isij＝p(qt+1＝j|qtI), the transition probability should satisfy the regular random constraint aij≥0，1≤i,j≤N,qtIndicating the current state.
Fourthly, confusion matrix: b ═ Bj(k)}
Wherein b isj(k)＝p{ot＝vk|qt＝j},1≤j≤N.1≤k≤M,otIndicating the observed value at time t.
Initial state probability distribution pi ═ piiIn which pii＝{q1＝i},1≤i≤N,
Thus, an HMM can be written as λ ═ { a, B, pi }, which comprises the following three important assumptions: markov assumption (states constitute a first order markov chain):
P(Xi|Xi-1...X1)＝P(X1|XI-1)；
immobility assumption (state independent of specific time):
P(Xi＝1|Xi)＝P(XJ+1|XJ)
output independence assumption (output is related to current state only):
P(Oi...OT|X...XT)＝ΠP(Ot|Xt)，
the HMM model is then imported into the forward, Viterbi, and Baum-Welch algorithms of the hidden Markov model algorithm for processing.
The hidden Markov model algorithm is adopted for data processing, effective body movement detection can be carried out, different staging modes are identified for the heart rate HMM and the respiration rate HMM, and the acquired sleep data are staged, so that the accuracy of sleep staging is improved.
Further, the data analyzer processes the data collected by the piezoelectric sensor collecting module and the acceleration sensor collecting module through a hidden Markov model algorithm to generate a health data graph, wherein the health data graph comprises a real-time heart rate; a real-time respiration rate; monitoring the body motion in real time; real-time BCG waveforms; pushing in the bed in real time; the real-time heart rate/breathing abnormity pushing method has the advantages that the data collected by the piezoelectric sensor collecting module and the acceleration sensor collecting module are subjected to visualization conversion through the health data graph, so that the real-time sleep health data of people are displayed more truly and accurately, and therefore health monitoring is carried out.
Furthermore, the data analysis appearance obtains the sleep stage through the data to piezoelectric sensor collection module and acceleration sensor collection module collection based on HMM operation, the sleep stage includes deep sleep, light sleep, REM, is awake, obtains the sleep quality picture through sleep stage data analysis, makes things convenient for people to obtain more accurate cognition to self sleep quality through the sleep quality picture, makes things convenient for medical personnel to make pertinence medical advice and measure.
Further, adjusting device adjusts according to the sleep quality map, data analysis appearance passes through the switching of the small-size air pump of signal of telecommunication control, the lifting is filled up and is equipped with a plurality of regulating blocks, and is a plurality of the regulating block all is linked together with small-size air pump, through the analysis to people's sleep quality, obtains people's sleep quality under the different shapes multisensor data acquisition pad to finely tune the shape of multisensor data acquisition pad through adjusting device, make people obtain higher sleep quality.
Further, be equipped with the subassembly of making an uproar of falling around the small-size air pump, the subassembly of making an uproar of falling includes the sound-proof housing, the sound cotton is inhaled to sound laid on the sound-proof housing inner wall, low frequency trap device is installed to the sound-proof housing outer end, reduces the noise of small-size air pump when the operation through the subassembly of making an uproar of falling, reduces the influence to the people sleep, promotes the accuracy of sleep data collection.
Further, the end of doctorsing and nurses and remove through signal connection between the end, intelligence mattress outer end is equipped with emergency call button, emergency call button and the end of doctorsing and nurses between signal connection carries out the worker's share of the healthy data of sleeping through the health guardianship platform to make medical personnel can real time monitoring user's sleep condition, in time make corresponding countermeasure, user's relatives also can know relevant information in real time simultaneously.
3. Advantageous effects
Compare in prior art, the advantage of this application lies in:
(1) according to the scheme, the laying of the multi-sensor data acquisition pad (2) can be realized, non-camera and non-wearable passive detection is formed for collecting data, interference information is removed through hidden Markov model algorithm analysis, more accurate and comprehensive sleep health data information is obtained, information sharing is carried out through a wireless network, a health monitoring platform is established, targeted sleep related services are provided, the specialty and the accuracy of sleep health monitoring are improved, and better use experience is brought;
(2) the method that the piezoelectric sensor acquisition module reflects the physiological information through the piezoelectric signal can minimize the influence of sleep data acquisition on sleep, can realize the application of family sleep monitoring, and improves the accuracy of detected data;
(3) the hidden Markov model algorithm is adopted for data processing, so that effective body movement detection can be performed, different staging modes are identified for the heart rate HMM and the respiration rate HMM, and the acquired sleep data are staged, so that the accuracy rate of sleep staging is improved;
(4) the data collected by the piezoelectric sensor acquisition module and the acceleration sensor acquisition module are subjected to visualization conversion through the health data graph, so that the real-time sleep health data of people can be displayed more truly and accurately, and the health monitoring is carried out;
(5) the sleep quality map is obtained through sleep stage data analysis, people can conveniently and accurately know the sleep quality of the people through the sleep quality map, and medical care personnel can conveniently make targeted medical care suggestions and measures;
(6) the sleep quality of people under the multi-sensor data acquisition pads in different shapes is obtained by analyzing the sleep quality of people, so that the shape of the multi-sensor data acquisition pad is finely adjusted by the adjusting device, and people can obtain higher sleep quality;
(7) the noise of the small air pump during operation is reduced through the noise reduction assembly, the influence on the sleep of people is reduced, and the accuracy of sleep data collection is improved;
(8) the health monitoring platform is used for sharing the sleep health data, so that medical staff can monitor the sleep condition of the user in real time, corresponding measures can be taken in time, and relatives of the user can know related information in real time.
Drawings
FIG. 1 is a schematic diagram of a smart mattress construction of the present application;
FIG. 2 is a schematic view of a cardiac periodic waveform configuration of the present application;
FIG. 3 is a schematic structural diagram of a healthcare platform according to the present application;
FIG. 4 is a schematic view of a lift pad configuration of the present application;
fig. 5 is a schematic view of the structure at a in fig. 4.
The reference numbers in the figures illustrate:
1 intelligence mattress, 2 multisensor data acquisition pad, 3 piezoelectric sensor collection module, 4 acceleration sensor collection module, 5 data analysis appearance, 6 storage hard disks, 7 high in the clouds, 8 remove the end, the end is doctorsed and nurses to 9, 10 lifting pads, 11 small-size air pumps, 12 regulating blocks, 13 noise reduction assembly, 14 sound-proof housing, 15 inhale the sound cotton, 16 low frequency trap devices, 17 emergency call button.
Detailed Description
The technical solution in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application; it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all embodiments, and all other embodiments obtained by those of ordinary skill in the art without any inventive work based on the embodiments in the present application belong to the protection scope of the present application.
In the description of the present application, it should be noted that the terms "upper", "lower", "inner", "outer", "top/bottom", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplification of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present application, it should be noted that, unless otherwise specifically stated or limited, the terms "mounted," "disposed," "sleeved/connected," "connected," and the like are used in a broad sense, and for example, "connected" may be a fixed connection, a detachable connection, an integral connection, a mechanical connection, an electrical connection, a direct connection, an indirect connection via an intermediate medium, and a communication between two elements.
Example (b):
referring to fig. 1-2, an intelligent mattress with health monitoring function comprises an intelligent mattress 1 and a multi-sensor data acquisition pad 2, the multi-sensor data acquisition pad 2 is arranged on the intelligent mattress 1, the multi-sensor data acquisition pad 2 comprises a piezoelectric sensor acquisition module 3 and an acceleration sensor acquisition module 4, a data analyzer 5 is arranged on the outer side of the intelligent mattress 1, the data analyzer 5 is in electrical signal connection with the piezoelectric sensor acquisition module 3 and the acceleration sensor acquisition module 4, a data analysis module is arranged in the data analyzer 5, referring to fig. 3, the data analyzer 5 is in signal connection with a health monitoring platform, the health monitoring platform comprises a cloud 7, a mobile terminal 8 and a medical terminal 9, the data analyzer 5 is in serial bus connection with a storage hard disk 6, the storage hard disk 6 is positioned in the data analyzer 5, the data analyzer 5 is in signal connection with the mobile terminal 8 and the medical terminal 9, referring to fig. 4-5, a regulating device is arranged in the intelligent mattress 1, the regulating device includes a lifting pad 10 and a small-sized air pump 11, the piezoelectric sensor acquisition module 3 collects a cardiac shock signal, and the acceleration sensor acquisition module 4 collects a sleep movement value, in this embodiment, the piezoelectric sensor acquisition module 3 adopts a sensing belt composed of piezoelectric film sensors, and the acceleration sensor acquisition module 4 is an MPU6050 model.
Referring to fig. 2, the cardiac shock signals are W-shaped cardiac periodic waveforms on the data analyzer 5, one cardiac periodic waveform includes H waves, I waves, J waves, K waves, L waves, M waves and N waves, the detection range of the piezoelectric sensor acquisition module 3 is greater than 80dB, the frequency of the cardiac shock signals is 100Hz, and the influence of sleep data acquisition on sleep can be minimized by using the method that the piezoelectric sensor acquisition module 3 reflects physiological information through the piezoelectric signals, so that the application of home sleep monitoring can be realized, the accuracy of the detection data is improved, the body movement in the sleep process can be detected by using the acceleration sensor acquisition module 4, and thus, the optimization of the detection data is performed, and the accuracy of the detection data is further improved.
The data analyzer 5 processes the data collected by the piezoelectric sensor acquisition module 3 and the acceleration sensor acquisition module 4 by adopting a hidden Markov model algorithm, wherein the hidden Markov model comprises the following elements:
number N of all possible hidden states of HMM;
the number of observed states M;
state transition probability matrix: a ═ aij}
Wherein a isij＝p(qt+1＝j|qtI), the transition probability should satisfy the regular random constraint aij≥0，1≤i,j≤N,qtIndicating the current state.
Fourthly, confusion matrix: b ═ Bj(k)}
Wherein b isj(k)＝p{ot＝vk|qt＝j},1≤j≤N.1≤k≤M,otIndicating the observed value at time t.
Initial state probability distribution pi ═ piiIn which pii＝{q1＝i},1≤i≤N,
Therefore, an HMM can be denoted as λ ═ { a, B, pi }, and the HMM includes the following three important assumptions: markov assumption (states constitute a first order markov chain):
P(Xi|Xi-1...X1)＝P(X1|XI-1)；
immobility assumption (state independent of specific time):
P(Xi＝1|Xi)＝P(XJ+1|XJ)
output independence assumption (output is related to current state only):
P(Oi...OT|X...XT)＝ΠP(Ot|Xt)，
the HMM model is then imported into the forward, Viterbi, and Baum-Welch algorithms of the hidden Markov model algorithm for processing.
The hidden Markov model algorithm is adopted for data processing, effective body movement detection can be carried out, different staging modes are identified for the heart rate HMM and the respiration rate HMM, and the acquired sleep data are staged, so that the accuracy of sleep staging is improved.
Referring to fig. 1 to 3, the data analyzer 5 processes the data collected by the piezoelectric sensor collection module 3 and the acceleration sensor collection module 4 by a hidden markov model algorithm to generate a health data graph, wherein the health data graph includes a real-time heart rate; a real-time respiration rate; monitoring the body motion in real time; real-time BCG waveforms; pushing in the bed in real time; real-time heart rate/breathing anomaly propelling movement, data that piezoelectric sensor collection module 3 and acceleration sensor collection module 4 collected are carried out visualization's conversion through the health data picture, real accurate demonstration people's real-time sleep health data more, thereby carry out health monitoring, data analysis appearance 5 obtains the sleep stage through the data based on HMM operation to piezoelectric sensor collection module 3 and acceleration sensor collection module 4 collection, the sleep stage includes deep sleep, light sleep, REM, it is awake, obtain the sleep quality picture through sleep stage data analysis, make things convenient for people to obtain more accurate cognition to the sleep quality of self through the sleep quality picture, make things convenient for medical personnel to make pertinence medical advice and measure.
Referring to fig. 4-5, the adjusting device adjusts according to the sleep quality diagram, the data analyzer 5 controls the small air pump 11 to open and close through an electrical signal, the plurality of adjusting blocks 12 are disposed in the lifting pad 10, the plurality of adjusting blocks 12 are all communicated with the small air pump 11, the sleep quality of people under the multi-sensor data collecting pad 2 with different shapes is obtained through analyzing the sleep quality of people, so that the shape of the multi-sensor data collecting pad 2 is finely adjusted through the adjusting device, people can obtain higher sleep quality, the noise reduction assembly 13 is disposed around the small air pump 11, the noise reduction assembly 13 includes a sound-proof cover 14, sound-absorbing cotton 15 is laid on the inner wall of the sound-proof cover 14, a low-frequency trap device 16 is mounted at the outer end of the sound-proof cover 14, the low-frequency trap device in this embodiment is made of hard glass fiber, the low-frequency noise is reduced, and the noise of the small air pump 11 during operation is reduced through the noise reduction assembly 13, the influence on the sleep of the human is reduced, and the accuracy of the sleep data collection is improved.
Referring to fig. 3, the medical care end 9 is in signal connection with the mobile end 8, the emergency call button 17 is arranged at the outer end of the intelligent mattress 1, the emergency call button 17 is in signal connection with the medical care end 9, and the health monitoring platform is used for sharing sleep health data, so that medical care personnel can monitor the sleep condition of the user in real time, make corresponding measures in time, and simultaneously, the relatives of the user can also know related information in real time.
When in use, please refer to fig. 1-5, a user lays the multi-sensor data acquisition pad 2 at a proper position on the intelligent mattress 1, then lies on the multi-sensor data acquisition pad 2 to sleep, then the piezoelectric sensor acquisition module 3 and the acceleration sensor acquisition module 4 collect the cardiac shock signals and the physical movement data of the user and transmit the cardiac shock signals and the physical movement data to the data analyzer 5, the data analyzer 5 processes the data collected by the piezoelectric sensor acquisition module 3 and the acceleration sensor acquisition module 4 through the hidden markov model algorithm to generate a health data graph and carries out sleep staging, the sleep quality graph of the user is obtained through the sleep staging, during the period, the data information generated by the data analyzer 5 is shared in real time through the health monitoring platform, so that operators at the medical care end 9 and the mobile end 8 can obtain the sleep health data of the user in time, the method comprises the steps of making targeted measures, simultaneously using for many times, according to the shape of an intelligent mattress 1 with high human body sleep quality in a sleep quality diagram, adjusting the shape of the targeted intelligent mattress 1 by an adjusting device, further improving the sleep quality of a user, paving a multi-sensor data acquisition pad 2 to form a non-camera, collecting data through non-wearable passive detection, analyzing through a hidden Markov model algorithm, removing interference information to obtain more accurate and comprehensive sleep health data, sharing information through a wireless network, establishing a health monitoring platform, providing targeted sleep related services, improving the profession and accuracy of sleep health monitoring, and bringing better use experience.
The foregoing is only a preferred embodiment of the present application; the scope of protection of the present application is not limited thereto. Any person skilled in the art should be able to cover all equivalent or changes within the technical scope of the present disclosure, which is equivalent to the technical solution and the improvement concept of the present disclosure, and the protection scope of the present disclosure.
Claims (8)
1. The utility model provides an intelligence mattress with health care function, includes intelligent mattress (1) and multisensor data acquisition pad (2), its characterized in that: the intelligent mattress (1) is provided with a multi-sensor data acquisition pad (2), the multi-sensor data acquisition pad (2) comprises a piezoelectric sensor acquisition module (3) and an acceleration sensor acquisition module (4), the intelligent mattress (1) is provided with a data analyzer (5) on the outer side, the data analyzer (5) is in electric signal connection with the piezoelectric sensor acquisition module (3) and the acceleration sensor acquisition module (4), the data analyzer (5) is internally provided with a data analysis module, the data analyzer (5) is in signal connection with a health monitoring platform, the health monitoring platform comprises a cloud end (7), a mobile end (8) and a medical care end (9), the data analyzer (5) is in serial bus connection with a storage hard disk (6), the storage hard disk (6) is positioned in the data analyzer (5), and the mobile end (8) and the medical care end (9) are in signal connection with each other, be equipped with adjusting device in intelligence mattress (1), adjusting device includes lifting pad (10) and small-size air pump (11).
2. The intelligent mattress with health monitoring function as claimed in claim 1, wherein: the sleep physical exercise monitoring system is characterized in that the piezoelectric sensor acquisition module (3) collects heart shock signals, the acceleration sensor acquisition module (4) collects sleep physical exercise values, the heart shock signals are in W-shaped cardiac periodic waveforms on the data analyzer (5), one cardiac periodic waveform comprises H waves, I waves, J waves, K waves, L waves, M waves and N waves, the detection range of the piezoelectric sensor acquisition module (3) is larger than 80dB, and the frequency of the heart shock signals is 100 Hz.
3. The intelligent mattress with health monitoring function as claimed in claim 2, wherein: the data analyzer (5) processes data collected by the piezoelectric sensor acquisition module (3) and the acceleration sensor acquisition module (4) by adopting a hidden Markov model algorithm, wherein the hidden Markov model comprises the following elements:
number N of all possible hidden states of HMM;
the number of observed states M;
state transition probability matrix: a ═ aij}
Wherein a isij＝p(qt+1＝j|qtI), the transition probability should satisfy the regular random constraint aij≥0，1≤i,j≤N,qtIndicating the current state.
Fourthly, confusion matrix: b ═ Bj(k)}
Wherein b isj(k)＝p{ot＝vk|qt＝j},1≤j≤N.1≤k≤M,otIndicating the observed value at time t.
Initial state probability distribution pi ═ piiIn which pii＝{q1＝i},1≤i≤N,
Thus, an HMM can be written as λ ═ { a, B, pi }, which comprises the following three important assumptions: markov assumption (states constitute a first order markov chain):
P(Xi|Xi-1...X1)＝P(X1|XI-1)；
immobility assumption (state independent of specific time):
P(Xi＝1|Xi)＝P(XJ+1|XJ)
output independence assumption (output is related to current state only):
P(Oi...OT|X...XT)＝ΠP(Ot|Xt)。
the HMM model is then imported into the forward, Viterbi, and Baum-Welch algorithms of the hidden Markov model algorithm for processing.
4. The intelligent mattress with health monitoring function as claimed in claim 3, wherein: the data analyzer (5) processes the data collected by the piezoelectric sensor collecting module (3) and the acceleration sensor collecting module (4) through a hidden Markov model algorithm to generate a health data graph, and the health data graph comprises a real-time heart rate; a real-time respiration rate; monitoring the body motion in real time; real-time BCG waveforms; pushing in the bed in real time; real-time heart rate/breathing anomaly push.
5. The intelligent mattress with health monitoring function as claimed in claim 4, wherein: the data analyzer (5) obtains sleep stages through the operation of the data collected by the piezoelectric sensor collecting module (3) and the acceleration sensor collecting module (4) based on an HMM, wherein the sleep stages comprise deep sleep, light sleep, REM and waking, and a sleep quality map is obtained through the analysis of the sleep stage data.
6. The intelligent mattress with health monitoring function as claimed in claim 5, wherein: the adjusting device adjusts according to the sleep quality diagram, the data analyzer (5) controls the opening and closing of the small air pump (11) through electric signals, a plurality of adjusting blocks (12) are arranged in the lifting pad (10), and the adjusting blocks (12) are communicated with the small air pump (11).
7. The intelligent mattress with health monitoring function as claimed in claim 6, wherein: be equipped with around small-size air pump (11) and fall noise assembly (13), it includes sound-proof housing (14) to fall noise assembly (13), sound-absorbing cotton (15) have been laid to sound-proof housing (14) inner wall, low frequency trap device (16) are installed to sound-proof housing (14) outer end.
8. The intelligent mattress with health monitoring function as claimed in claim 1, wherein: the medical care end (9) is connected with the moving end (8) through signals, an emergency call button (17) is arranged at the outer end of the intelligent mattress (1), and the emergency call button (17) is connected with the medical care end (9) through signals.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115381399A (en) * | 2022-08-12 | 2022-11-25 | 深圳市安康源科技有限公司 | Intelligent sleep monitoring equipment and cloud system |
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