CN110477887A - A kind of monitoring device of non-invasive long-range apnea syndrome - Google Patents
A kind of monitoring device of non-invasive long-range apnea syndrome Download PDFInfo
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- CN110477887A CN110477887A CN201910882178.6A CN201910882178A CN110477887A CN 110477887 A CN110477887 A CN 110477887A CN 201910882178 A CN201910882178 A CN 201910882178A CN 110477887 A CN110477887 A CN 110477887A
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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
- A61B5/02—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
- A61B5/1116—Determining posture transitions
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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
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4809—Sleep detection, i.e. determining whether a subject is asleep or not
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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
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4812—Detecting sleep stages or cycles
-
- A—HUMAN NECESSITIES
- 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
-
- A—HUMAN NECESSITIES
- 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
- A61B5/4818—Sleep apnoea
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- 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
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
- A61B5/0816—Measuring devices for examining respiratory frequency
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
- A61B5/0826—Detecting or evaluating apnoea events
Abstract
The invention discloses a kind of monitoring devices of non-invasive long-range apnea syndrome: sensor array generates resistance value and changes signal and be transmitted to Acquisition Circuit；Acquisition Circuit transmission resistance value changes signal to pre-processing circuit；Pretreatment circuit, which changes after signal carries out noise filtering resistance value, is transmitted to microprocessor；The body movement signal of acceleration sensor module acquisition turn is simultaneously transmitted to microprocessor；Microprocessor separates breathing and heartbeat signal in resistance value variation signal, obtains breathing classification and palmic rate and is transmitted to cloud platform；Cloud platform judges the Depth of sleep of people in bed, and period when record apnea whithin a period of time according to breathing classification, and the number turned over and frequency, palmic rate is combined to draw out sleep quality time diagram.The monitoring device can carry out human body to monitor without the heart rate and respiratory rate that influence formula, and available sleeper turns over number, can provide the analysis data of sleep quality and apnea illness for doctor or guardian.
Description
Technical field
The invention belongs to breathe to exhale with heartbeat signal acquisition and monitoring technical field, in particular to a kind of non-invasive long-range
Inhale pause syndrome detection device.
Background technique
Sleep is extremely important physiological requirements during human life, but according to investigations the crowd in China 38.2% have sleep
Dormancy problem on obstacle.Wherein, Sleep Apnea-hypopnea Syndrome (sleep apnea-hypopnea syndrome, SAHS)
It is a kind of sleeping disorders for seriously affecting people's sleep quality and health, common manifestation form is to snore, is of short duration in sleep
Asthma, breathing stop, body jerk is even suffered a shock, threat to life safety.
Sleep Apnea-hypopnea Syndrome has large effect to the health and quality of life of patient.It is clinical
Studies have shown that extended sleep apnea low syndrome can lead to arrhythmia cordis, myocardial infarction, hypertension, etc. a variety of diseases
Disease.Therefore, the early diagnosis of Sleep Apnea-hypopnea Syndrome is to treatment chronic hypertension disease, promotion life of elderly person matter
Measurer is significant.
But since Sleep Apnea-hypopnea Syndrome is the characteristics of sleeping intermittent breaking-out, even I,
Also it is difficult to understand breaking-out situation when its nighttime sleep with occasionally household, therefore acquires Sleep Apnea-hypopnea Syndrome disease
There are bigger difficulty for history.Existing Sleep Apnea-hypopnea Syndrome monitoring and detection device can divide from testing principle
Are as follows: (1) motion detection method: it is a kind of relatively simple, practical method that chest cavity movement when using breathing, which is converted to electric signal,.It lacks
Point is that each individual variation of breath size in sleep is very big, but common detection threshold is fixed and invariable,
Therefore to judge that apnea can only be as rough judgement.(2) Chest X-rays detection method: lung tissue's resistivity when breathing is utilized
Variation is to judge apnea.Electrical impedance method be to the detection of apnea it is highly effective, it can directly reflect pulmonary ventilation
Whether there is or not, and it is simple and easy, it is lossless harmless, it is cheap.Patient also without significant discomfort sense, corresponding apparatus is small-sized,
It is light, it can be widely applied in family and ward.But in actual measurement, this impedance variations include electrode polarization, cortex group
Equal tissue changes, motion artifacts are knitted, therefore cause the difficulty in measurement.Impedance method also needs further perfect in use.(3) hot
Quick air-flow detection method: breath state when sleep is judged using the gas flow temperature variation at mouth and nose when breathing, such method is excellent
Point is not influenced by respirometric, but disadvantage is also the influence it is clear that vulnerable to environment temperature.
Sleep monitor is classified from the type of detection device, is had: (1) leading sleep detection (PSG): polysomnogram prison more
Survey is most authoritative method, is current internationally recognized " goldstandard ".PSG can recorde multinomial physiological parameter include electroencephalogram,
Electrocardiogram, mouth and nose air-flow, blood oxygen saturation, the sound of snoring, position, eye movement, limb motion, chest and abdomen respiratory movement etc..PSG is not only
It may determine that the severity of sleep apnea syndrome, and patient can be understood with the Sleep architecture of quantitative analysis patient
The variation of blood oxygen, respiratory rhythm and electrocardio blood pressure in sleep procedure.The disadvantage is that PSG, which monitors the primary time, needs at least 8
A hour, patient's needs waited for upper entire evening that PSG inspection fee is expensive in hospital monitor room, next needs patient to be covered with it
Various sensors.Unused sleep environment can generate certain influence to the quality of the sleep of detected person, to influence to measure
As a result.(2) wearable detection: commonly wristband type universal serial is speculated using the EGC sensor in bracelet with acceleration transducer
The situation of sleep knows sleep state by body dynamic frequency, and deep sleep user's body is moved relatively fewer, and either shallow sleep is then on the contrary.
But bracelet is unable to monitor out breath state, and is difficult to receive to wear bracelet sleep by major part user.(3) it is exhaled based on mattress formula
Inhale detection: the parameters such as breathing, heart rate when using resistance or the acquisition sleep of capacitive films sensor, body are dynamic, such method
Patient is more bonded for wearable device, precision is higher, and the interference being subject to is smaller, because being hidden in mattress,
It is not easy to be discovered by patient, more can really react the sleep state and apnea situation of patient.Lead sleep detection compared to more
For it is low in cost, be more suitable at home self monitor either home for destitute concentrate monitoring.
Summary of the invention
The object of the present invention is to provide a kind of monitoring devices of non-invasive long-range apnea syndrome, sleep in people
When, human body can be carried out to monitor without the heart rate and respiratory rate that influence formula, and available sleeper turns over number, can be doctor
Or guardian provides the analysis data of sleep quality and apnea illness.
To achieve the above objectives, the present invention is realized using following technical approach:
A kind of monitoring device of non-invasive long-range apnea syndrome, the monitoring device include:
Sensor array, the plastics for being fitted in a plurality of pressure sensitivity sensing zone two sides including a plurality of pressure sensitivity sensing zone and interval are thin
Plate, the variation for being moved according to sleeper's body generate resistance value and change signal and be transmitted to Acquisition Circuit；
Acquisition Circuit collects resistance value and changes signal and be transmitted to pretreatment circuit；
Circuit is pre-processed, resistance value is changed after signal carries out noise filtering and is transmitted to microprocessor；
Acceleration sensor module, the body movement signal that acquisition sleeper turns in sleep procedure, the number including turn
With frequency, and it is transmitted to microprocessor；
Microprocessor, separation resistance value change breathing and heartbeat signal in signal, differentiate respectively and are breathed after counting
Classification and palmic rate are simultaneously transmitted to cloud platform by Internet of Things communication module；
Cloud platform carries out Time alignment to the breathing classification uploaded, judges the sleep of people in bed whithin a period of time
Depth, and period when record apnea, and combine the number turned over and frequency, palmic rate when drawing out sleep quality
Between scheme, and these information are uploaded to client.
The principle of the invention lies in: it lies on a bed in sleep procedure, turns in people, lung shrinks, and heartbeat can all produce
The body movement signal of raw some strength, can be captured by processed pressure sensor band with acceleration transducer
In monitoring device provided by the invention, the data that the Internet of Things communications module is transmitted to cloud platform are all by micro-
It manages device and calculates packing, and can show the data briefing of network connection state and transmission in subsidiary OLED display screen.It is logical
The displaying of cloud platform software is crossed, it can be by data sharing to guardian and doctor, in remote, non-intrusive, loss when being not required to long
The data of patient respiratory pause symptom and sleep quality are obtained in the case where the human observer time.
The sheet plastic includes square plastic thin plate and thin elliptical plate, and the thin elliptical plate is located at a plurality of pressure sensitivity biography
Feel the centre of band, the area of the thin elliptical plate is greater than square plastic thin plate.
Centre sheet plastic is ellipse, lung's projected position in thoracic cavity, energy when can more be fitted in normal sleeping position
It is enough preferably to extract body movement signal.
Between the square plastic thin plate or the spacing distance of square plastic thin plate and thin elliptical plate is 8-12 centimetres.It is described
The size of square plastic thin plate is 5*10cm.
The pressure sensitivity sensing zone is two, is fitted at 1/4 and 3/4 position of sheet plastic longitudinal direction respectively.By that will press
Sense sensing zone is arranged in above-mentioned sheet plastic position, can carry out the signal acquisition between different muscle groups in a relatively uniform fashion, and
Multiple sensor signal is carried out in the algorithm to merge into each other compensation, optimizes data.
The Acquisition Circuit is that there are the damping conversion circuit and analog to digital conversion circuit of certain proportion amplification, the pretreatments
Circuit is Butterworth low pass wave circuit.Analog-digital converter is 24 high-precision adcs, and pretreatment circuit mainly filters out
The interference of ambient noise and the body movement signal of high frequency.
Upper back position when the sensing zone array is installed on mattress close to sleeper's ortho, the acceleration sensing
Device module is mounted on a side or bed back.
In the present invention, the acceleration sensor module is mounted on to the position for being not easy to be touched by sleeper, is prevented
Influence sleep environment.Velocity sensor can intercept the signal for the bigger movement of amplitudes such as turning over, in conjunction with the signal of pressure sensitivity band,
It is dry that removal abnormal state is provided when can evaluate the sleep quality of user, and substantially body movement signal can be truncated to for sensing zone simultaneously
The effect disturbed.
The method that the microprocessor separation resistance value changes breathing and heartbeat signal in signal are as follows: pass through empirical modal point
Resolving Algorithm carries out the assertive evidence Frequency extraction of heartbeat, breathing, and both separation obtain signal independent, and in letter independent
The characteristic vector space that average amplitude, variance and short-term spectrum form respective independent signal model identification is extracted in number, is finally adopted
The differentiation and counting of the two respectively are carried out with clustering.
Wherein, it is intercepted using threshold value, convolution, clustering scheduling algorithm divides breath signal window, in one section of resistance value of interception
Change the separation that breathing and heartbeat signal are carried out in signal.
Preferably, when the acceleration transducer collects the body movement signal of turn, the resistance of sensor array generation at this time
Value change signal be interference signal, microprocessor after remove interference signal again carry out separation resistance value change signal in breathing with
Heartbeat signal.
That is, suitably being deleted when acceleration transducer collects the body movement signal of turn to synchronous pressure sensitivity transducing signal
It removes, avoids interfering calculating and influencing.
Compared with prior art, monitoring device provided by the invention is a kind of non-invasive device, can be right in people's sleep
Human body is carried out without the heart rate for influencing formula and respiratory rate monitoring, and available sleeper turns over number, can be doctor or monitoring
The analysis data of person offer sleep quality and apnea illness.
Detailed description of the invention
Fig. 1 is the functional block diagram of the monitoring device of non-invasive long-range apnea syndrome provided by the invention.
Fig. 2 is the peace of the sensor array of the monitoring device of non-invasive long-range apnea syndrome provided by the invention
Assembling structure schematic diagram.
Fig. 3 is the apparatus structure signal of the monitoring device of non-invasive long-range apnea syndrome provided by the invention
Figure.
Fig. 4 is empirical mode decomposition algorithm flow schematic diagram.
Fig. 5 is that the initial acquisition of the monitoring device of non-invasive long-range apnea syndrome provided by the invention obtains number
Scheme according to drawing.
Fig. 6 is a kind of former acquisition data of monitoring device of non-invasive long-range apnea syndrome of the present invention by warp
It tests mode decomposition and obtains the drafting figure of heartbeat breath signal.
Wherein, the 1, first sheet plastic；2, pressure sensor band；3, the second sheet plastic；4, square plastic thin plate；5, it presses
Force snesor band；6, oval sheet plastic；7, total system circuit board；8, Internet of Things communication module；9, acceleration transducer mould
Block；10, microprocessor；11, display module.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention is completely retouched
It states.It is clear that saying that the specific embodiment of description is used only for explaining the present invention rather than limiting the invention herein.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment belongs to the scope of the present invention.
As shown in Figure 1-Figure 3, the monitoring device of non-invasive long-range apnea syndrome provided by the invention includes:
Sensor array, the plastics for being fitted in a plurality of pressure sensitivity sensing zone two sides including a plurality of pressure sensitivity sensing zone and interval are thin
Plate, the variation for being moved according to sleeper's body generate resistance value and change signal and be transmitted to Acquisition Circuit；
Acquisition Circuit collects resistance value and changes signal and be transmitted to pretreatment circuit；
Circuit is pre-processed, resistance value is changed after signal carries out noise filtering and is transmitted to microprocessor；
Acceleration sensor module 9, the body movement signal that acquisition sleeper turns in sleep procedure, the number including turn
With frequency, and it is transmitted to microprocessor；
Microprocessor 10, separation resistance value change breathing and heartbeat signal in signal, differentiate respectively and are exhaled after counting
It inhales classification and palmic rate and cloud platform is transmitted to by Internet of Things communication module 8；
Cloud platform carries out Time alignment to the breathing classification uploaded, judges the sleep of people in bed whithin a period of time
Depth, and period when record apnea, and combine the number turned over and frequency, palmic rate when drawing out sleep quality
Between scheme, and these information are uploaded to client.
Wherein, microprocessor 10 is STM32F407, breathes heartbeat separation algorithm, and recognizer is all embedded in STM32 chip
In the middle, as shown in Figure 1, microprocessor also assumes responsibility for arranging data, the work communicated with Internet of Things mould group.
Wherein, as shown in Fig. 2, the partial structurtes of sensor array are as follows: the two sides interval of pressure sensitivity sensing zone 2 is fitted with first
Sheet plastic 1 and the second sheet plastic 2.
Wherein, as shown in figure 3, the overall structure of sensor array are as follows: two FSR408 pressure sensitivity sensing zones 5, its every
Pair 5*10cm square plastic thin plates 4, pressure sensor band 5 are fitted in square plastic thin plate 4 respectively and indulge the addition of ten centimeters up and down
To 1/4,3/4 position at, and 5 centre sheet plastic of pressure sensor band is changed to oval sheet plastic 6, to be bonded use
Lung's projected position in family thoracic cavity in normal sleeping position.Pressure sensor band 5 and human body can be increased by increasing sheet plastic
Contact area, and centre sheet plastic is changed to oval sheet plastic 6, can more add close to the position of cardiopulmonary
Site preparation acquires human body body movement signal.
Wherein, Acquisition Circuit and pretreatment circuit, Acquisition Circuit are that there are the damping conversion circuits of certain proportion amplification
And analog to digital conversion circuit, pretreatment circuit are Butterworth 200Hz low-pass filter circuit.Analog-digital converter uses ADS1220,
Divide ADC for 24 potential difference of multichannel, programming makes it carry out the sampling of 45Hz sample frequency.Amplifier used in foregoing circuit is that LM4562 is low
It is distorted low-noise operational amplifier.(total system circuit board 7 is also integrated on total system circuit board 7 for Acquisition Circuit and pretreatment circuit integration
There are power supply circuit and microprocessor peripheral circuit etc.).Impedance matching, filter can be carried out by changing signal to resistance value by analog circuit
The analog signal that body moves parameter, is then converted into digital signal by analog to digital conversion circuit, is by the processing such as wave, signal amplification
Microprocessor provides data.It include various noises since the resistance value of Acquisition Circuit acquisition changes signal, partial data is non-useful
Data, the useful information contained in signal are difficult to extract.By pre-processing the Butterworth 200Hz low-pass filter circuit of circuit,
Filtered preferable signal can be obtained.Fig. 5 be Acquisition Circuit be collected into sleep quality when signal map, wherein 0-1200 frame be
Signal under eupnea state, experimenter ceases breathing after 1200 frames, it is seen then that sensor array and Acquisition Circuit are slept in people
The data obtained during apnea have quite apparent characteristic.
Since the heart rate collecting part of monitoring device provided by the invention only provides tally function rather than ecg analysis function,
Therefore and high frequency sampling is not used, purpose, which obtains, meets the waveform of heartbeat feature.
Wherein, acceleration sensor module 9 is mpu6050 module.In data collection and analysis, the body movement signal of turn is
By a relatively large margin, and irregular signal section, when microprocessor carries out normal signal processing, the partial data can be considered for
Breathing and the interference data for heartbeat signal, but in sleep monitor, turning over equally is the significant data for needing to record.Therefore add
Enter acceleration transducer, carries out synchronous signal acquisition with other analog circuits, it, can be in the same of record when significantly body is dynamic for generation
When, the function of removing part interference is provided for breathing heartbeat data part.
Optionally, ESP8266 or raspberry pie can be selected in Internet of Things communication module 8, both can by serial ports with it is micro-
Processor is communicated, and is linked up data and Internet cloud platform using mqtt agreement, and system receiving is made centainly may be used
The control of conditioning function.
Optionally, display module 11 can provide part number using SSD1351 module as human-computer interaction part for user
According to displaying, the functions such as cloud platform connection status is shown, whether installation may be selected.
Separating treatment is carried out to data with microprocessor 10, process is mainly calculated with improved empirical mode decomposition
Method carries out both the assertive evidence Frequency extraction of heartbeat, breathing, separation, and extracts average amplitude in individually separated signal, in short-term
Variance, short-term spectrum form the characteristic vector space of respective signal mode identification, finally carry out sentencing for the two using clustering
Not and count.
Specifically, as shown in figure 4, empirical mode decomposition algorithm flow is as follows:
(1) all maximum points for finding original signal x (t) go out maximum envelope e by Cubic Spline Functions Fitting+
(t)；Similarly fit the minimum envelope e of signal-(t).The mean value of upper and lower envelope is m1(t)。
(2) original signal is subtracted into m1(t), it can be obtained the new signal h for removing low frequency1 1(t)。
(3) general h1 1(t) it is not a stationary signal, is unsatisfactory for the condition of assertive evidence modal definition, repeats the above process, it is false
Surely after passing through k times, h1 k(t) meet the condition of assertive evidence modal definition.Then h1 k(t) the single order assertive evidence modal components for being x (t).Weight
It can get the multistage assertive evidence modal components of x (t) again.The independent element of i.e. various signals.
(4) the multistage assertive evidence modal components of available x (t) are repeated.The independent element of i.e. various signals.
As shown in fig. 6, the 1st small figure is former acquisition signal, the 2nd small figure is the normalizing signal after trending operation, the 3rd, 4
Small figure is the map decomposed after basic experience mode decomposition algorithm.
Respiratory model identifying processing is carried out to data with microprocessor, main process is cluster algorithm, process
It is as follows:
(1) breath signal after separation is extracted into average amplitude, variance, frequency spectrum, with three data characteristics composition breathing letters
Number feature vector.
(2) after obtaining above three feature vector, the identification of respiratory model is carried out using the classifying method of clustering.
(3) according to the data of respiratory model, breath data is carried out according in apnea deeper into ground, shallow sleep-respiratory,
The classifications such as deep sleep breathing are classified.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (8)
1. a kind of monitoring device of non-invasive long-range apnea syndrome, which is characterized in that the monitoring device includes:
Sensor array is fitted in the sheet plastic of a plurality of pressure sensitivity sensing zone two sides including a plurality of pressure sensitivity sensing zone and interval, uses
Resistance value variation signal is generated in the variation moved according to sleeper's body and is transmitted to Acquisition Circuit；
Acquisition Circuit collects resistance value and changes signal and be transmitted to pretreatment circuit；
Circuit is pre-processed, resistance value is changed after signal carries out noise filtering and is transmitted to microprocessor；
Acceleration sensor module, the body movement signal that acquisition sleeper turns in sleep procedure, number and frequency including turn
Rate, and it is transmitted to microprocessor；
Microprocessor, separation resistance value change breathing and heartbeat signal in signal, differentiate and obtain after counting breathing classification respectively
Cloud platform is transmitted to palmic rate and by Internet of Things communication module；
Cloud platform carries out Time alignment to the breathing classification uploaded, judges the Depth of sleep of people in bed whithin a period of time,
And period when record apnea, and the number turned over and frequency, palmic rate is combined to draw out sleep quality time diagram,
And these information are uploaded to client.
2. the monitoring device of non-invasive long-range apnea syndrome according to claim 1, which is characterized in that described
Sheet plastic includes square plastic thin plate and thin elliptical plate, and the thin elliptical plate is located at the center of a plurality of pressure sensitivity sensing zone
The area at place, the thin elliptical plate is greater than square plastic thin plate.
3. the monitoring device of non-invasive long-range apnea syndrome according to claim 2, which is characterized in that described
Between square plastic thin plate or the spacing distance of square plastic thin plate and thin elliptical plate is 8-12 centimetres.
4. according to the monitoring device of non-invasive long-range apnea syndrome described in right 2, which is characterized in that the pressure sensitivity
Sensing zone is two, is fitted at 1/4 and 3/4 position of sheet plastic longitudinal direction respectively.
5. the monitoring device of non-invasive long-range apnea syndrome according to claim 1, which is characterized in that described
Acquisition Circuit is there are the damping conversion circuit and analog to digital conversion circuit of certain proportion amplification, and the pretreatment circuit is fertile for Bart
This low-pass filter circuit.
6. the monitoring device of non-invasive long-range apnea syndrome according to claim 1, which is characterized in that described
Upper back position when sensing zone array is installed on mattress close to sleeper's ortho, the acceleration sensor module are mounted on
Bed side or bed back.
The acceleration sensor module is mounted on the position for being not easy to be touched by sleeper, prevents from influencing sleep environment.
7. the monitoring device of non-invasive long-range apnea syndrome according to claim 1, which is characterized in that described
The method that microprocessor separates breathing and heartbeat signal that resistance value changes in signal are as follows: the heart is carried out by empirical mode decomposition algorithm
It jumps, the assertive evidence Frequency extraction of breathing, both separation obtain signal independent, and extraction is average in signal independent
Amplitude, variance and short-term spectrum form the characteristic vector space of respective independent signal model identification, finally using clustering into
The differentiation and counting of both row difference.
8. the monitoring device of non-invasive long-range apnea syndrome according to claim 7, which is characterized in that described
When acceleration transducer collects the body movement signal of turn, it is interference letter that the resistance value that sensor array generates at this time, which changes signal,
Number, microprocessor carries out breathing and heartbeat signal in separation resistance value variation signal again after removing interference signal.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111035367A (en) * | 2019-12-31 | 2020-04-21 | 华南师范大学 | Signal detection method and system for judging sleep apnea |
| CN111568388A (en) * | 2020-04-30 | 2020-08-25 | 清华大学 | Non-contact mouth respiration detection device and method and storage medium |
| CN112245740A (en) * | 2020-11-04 | 2021-01-22 | 湖南万脉医疗科技有限公司 | Multifunctional respirator based on cloud platform self-checking |
| CN113080849A (en) * | 2021-03-25 | 2021-07-09 | 浙江大学 | Intelligent mattress and sleep monitoring method thereof |
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