CN108903951A - A method of micro- deformation real-time monitoring assessment based on WiFi signal - Google Patents
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 24
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- 230000001186 cumulative effect Effects 0.000 claims description 12
- 230000029058 respiratory gaseous exchange Effects 0.000 claims description 10
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- 210000001015 abdomen Anatomy 0.000 claims description 4
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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
- A61B5/113—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb occurring during breathing
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- A—HUMAN NECESSITIES
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- H04B17/30—Monitoring; Testing of propagation channels
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- H—ELECTRICITY
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- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract
Micro- deformation real-time monitoring appraisal procedure based on WiFi signal that the present invention relates to a kind of, this method is monitored the step of environment first, the detection network to be formed a whole with several pairs of antennas, emit and receive signal by antenna, signal data is pre-processed, and it is analyzed based on IRFE algorithm, decomposite the frequency of each concrete behavior movement and calculating action, finally according to information such as the operating frequencies of algorithm detection, assessment action state in real time, the present invention is combined with the theoretical analysis of, overcoming previous methods parameter cannot clearly fix, model is incomplete, the disadvantages of constraint is more and monitoring result is unstable.
Description
Technical field
The invention belongs to artificial intelligence and medical treatment & health field, specifically a kind of micro- deformation based on WiFi signal is real
When monitoring and assessing method.
Background technique
With the development in the fields such as smart home, intelligent medical, movement monitoring becomes a burning hot topic, but wearable
The problem of the equal existing inconvenience of detection devices has the problem of privacy again, is different from conventional action identification, is detected with wireless signal
The research of human action obtains certain achievement already, but existing research is to fine granularity movement monitoring and inaccurate, and influences
Factor is more, the stable theory standard not quantified, below by taking detection sleep as an example.
Mental health, cardiovascular and cerebrovascular health, metabolism etc. of the quality of sleep quality concerning human body.Existing use
WiFi signal carry out the determination method for parameter such as the scheme of breathing detection and undeclared antenna distance height and whether pervasive reason
By foundation, it is unstable to often lead to testing result.
Summary of the invention
Based on this, it is necessary in view of the above-mentioned problems, providing a kind of micro- deformation real-time monitoring assessment side based on WiFi signal
Method, to solve the problems, such as the inaccurate of fine granularity movement monitoring.
Purpose according to the present invention provides a kind of method of micro- deformation real-time monitoring assessment based on WiFi signal, including
Following steps：
Step 1: setting network detects environment, detection signal is sent based on network detection environment；
Step 2: receiving the detection signal of feedback, each in the detection signal of the feedback specifically act simultaneously is decomposited
And the frequency of calculating action；
Step 3: assessing action state in real time, and carry out real-time display according to the operating frequency information.
Preferably, the setting network detects environment, specifically, the detection net to be formed a whole with several pairs of antennas
Network, wherein transmitting antenna is A1, A2, A3 ... An, receiving antenna B1, B2, B3 ... Bn, to every a pair of of monitoring aerial for,
Abdomen deformation caused by breathing is set to be located at the X-axis of antenna pair and between the biggish internal layer Fresnel region of energy, antenna pair
Distance be set as 20-25cm, the sample frequency of data is set as 20-100HZ.
Preferably, the detection signal for receiving feedback decomposites each specific dynamic in the detection signal of the feedback
The frequency of work and calculating action further includes pre-processing to received feedback detection signal, specifically, calculating data sequence
Data item X in columniThe average value Avg of neighbouring N number of data itemi, by AvgiAs XiOr the new value including M-1 data item thereafter,
After moving distance M, aforementioned calculating process is repeated, until being moved to sequence end.
Preferably, the frequency of each specific movement and calculating action in the detection signal for decompositing the feedback
Rate, specifically,
Input：Subcarrier sequence I1..., In, sample frequency f；
Output：Instantaneous respiratory rate sequence F1..., Fn；
(1) it initializes any selection kth subcarrier and carries out difference processing, generate difference sequence
(2) merge monotony interval and enable t=1, P=0, Q=0；By the numerical value with being positive or with being negative adjacent in difference sequence
It is merged into a section, with section accumulated value Δ miAnd merge numerical value number Δ niIndicate the i-th section, can must add up value sequence
Δm1..., Δ mrWith counting sequence Δ n1..., Δ nr；
(3) if t is less than r, since the t of position, first is found in cumulative value sequence and is greater than given threshold value A1Δ maMake
For expiratory phase initial position；Otherwise it moves back；
(4) since s=a, cumulative Δ m is attemptedsWith Δ nsIf s is equal to r, exit；If there is Δ m at bsAccumulated value
Greater than M1, and Δ nsAccumulated value be not more than N1, then it is assumed that expiratory phase is found, t=b+1, Q=b are updated；Otherwise P=0, t=
T+1 turns (3)；
(5) if t is less than r, since the t of position, first is found in cumulative value sequence and is less than given threshold value A2Δ mcMake
For expiration phase initial position；Otherwise it exits；
(6) since s=c, cumulative Δ m is attemptedsWith Δ nsIf s is equal to r, exit；If there is Δ m at dsAccumulated value
Less than M2, and Δ nsAccumulated value be not more than N2, then it is assumed that expiration phase is found, t=d+1 is updated；Otherwise P=0, t=t+1 turn
(3)；
(7) if P is 0, P=Q, turn (3)；
(8) add up Δ nPTo Δ nQ-1, it is denoted as S, then has instantaneous respiratory rate Fv=60f/S updates P=Q, turns (3).
Beneficial effects of the present invention：
Micro- deformation real-time monitoring appraisal procedure based on WiFi signal of the invention overcomes previous methods parameter cannot be bright
The disadvantages of really fixed, model is incomplete, and constraint is more and monitoring result is unstable.The present invention is combined with the theoretical analysis of, can be quick
Aerial position is adjusted, obtains stabilization signal convenient for monitoring and analysis.
Detailed description of the invention
Fig. 1 is micro- deformation position schematic diagram of the invention
Fig. 2 is aerial position of the invention and Fresnel region schematic diagram
Fig. 3 is overhaul flow chart of the invention
Fig. 4 a is the signal detection schematic diagram lieed down under sleeping position in the present invention
Fig. 4 b is the signal detection schematic diagram in the present invention under lateral sleeping position
Fig. 4 c is the signal detection schematic diagram in the present invention under prostrate sleeping position
Fig. 5 is the signal detection operation result display diagram in the present invention under three kinds of sleeping positions
Fig. 6 is that breathing product assess figure in real time in the present invention
Specific embodiment
The application is described in further detail with reference to the accompanying drawing, it is necessary to it is indicated herein to be, implement in detail below
Mode is served only for that the application is further detailed, and should not be understood as the limitation to the application protection scope, the field
Technical staff can make some nonessential modifications and adaptations to the application according to above-mentioned application content.
Purpose according to the present invention, as shown in figure 3, provide it is a kind of based on WiFi signal micro- deformation real-time monitoring assessment
Method includes the following steps：
Step 1: setting network detects environment, detection signal is sent based on network detection environment；
Fresnel region theoretical analysis and calculation, as shown in Fig. 2, O indicates the middle position of A and B, for quantitative analysis each side
The characteristic distributions of upward Fresnel region radius, (note that the direction x as described herein and y by taking the most special direction x and the direction y as an example
Direction includes positive direction and negative direction).Point A (or point B) is denoted as r to each elliptical shortest distancei x, O to it is each it is elliptical away from
From being denoted as ri y, λ indicates the wavelength of used wireless signal, the distance of L1 expression AB point, and corresponding calculation formula is：
Fresnel region radius size is unrelated with AB point distance L1 in X-direction known to then.
Sleep feature quantitative analysis, slight change, about 5-10mm can occur for the abdomen profile of people in respiratory.It is existing
Theoretical proof goes for the detection effect of stable and consistent, and breathing displacement should be fully located in single Fresnel region.And WIFI
The center operating frequency of antenna is about 2.4GHz and 5.35-5.8GHz, and wavelength respectively may be about 12.5cm and 5.6-5.2cm, can be obtained
Corresponding most short Fresnel region radius size is respectively 3.125cm and 1.4-1.3cm.Obvious abdominal respiration displacement completely can position
In any Fresnel region of 2.4GHz and 5.35-5.8GHz carrier wave.
A series of antenna detection effective range measurement, by rigorous confirmatory experiments, it was demonstrated that when between dual-mode antenna A and B
When distance is greater than 10cm, the range that is disturbed of the vertical and horizontal of antenna will be very big, otherwise works as transmitting antenna and reception
Antenna is closer apart, and it is more controlled effectively to monitor region, therefore needs to adjust the distance between transmitting antenna A and receiving antenna B L1, makes
The intensity S, i.e. F-S of direct signal can effectively be interfered by obtaining reflected signal strength F caused by fine motion is made>0.5dB.
Signal energy loss calculation, if signal is propagated in an accessible free space, signal is because propagating road
Path loss (Path Loss, PL) coincidence formula that electrical path length variation occurs：
Wherein, GrIndicate the gain of receiving end antenna, GtIndicate the gain of sending and receiving sending end antenna, GrAnd GtIt is constant, d
Indicate signal propagation distance, λ indicates signal carrier wavelength, and electromagnetic wave propagation speed is light velocity c, can obtain formula λ=c/f, f
For signal(-) carrier frequency.Formula is substituted into, formula can be obtained after simplifying：
PL=p+20lg (d)+20lg (f)
Wherein, p=-Gr-Gt+ 20lg (4 π d/c) is constant.For specific WIFI signal carrier wave, f is a constant.
Thus, it can be known that propagation distance d is bigger, the value PL of path loss is bigger.By calculating, the propagation distance of about signal turns over one
Times, signal energy intensity can decay about 6dB.
Detect environment arrangement, the detection network to be formed a whole with several pairs of antennas, wherein transmitting antenna be A1, A2,
A3 ... An, receiving antenna B1, B2, B3 ... Bn.To every a pair of of monitoring aerial for, make abdomen deformation caused by breathing as far as possible
Positioned at antenna pair X-axis and by through the biggish internal layer Fresnel region of energy, antenna to the distance between generally 20-
The sample frequency of 25cm, data are generally 20-100HZ.As deformation occurs in the X-axis side of transmitting antenna A1 and receiving antenna B1
To practical operation can at most have the direction at positive and negative 90 ° of angles to deviate.Specifically as shown in figure 4, being directed to three kinds of different sleeping positions of human body,
There is corresponding antenna position to illustrate.
Data source carrier frequency selection, when the displacement of deformation is m-n, wherein m<N then selects suitable sub-carrier frequencies P
It is monitored, so that the corresponding wavelength of P is greater than 4 times of n, but less than 12 times n.
Step 2: receiving the detection signal of feedback, each in the detection signal of the feedback specifically act simultaneously is decomposited
And the frequency of calculating action；
Signal data collected by signal receiver is the binary data of .dat format, and signal receiver is passed through net
Line and data processor establish data connection, and the data sending terminal program voluntarily write then is run on signal receiver, supervise
Depending on the growth of .dat file, and data and monitoring information will be increased and connect by the data on data connection to data processor
Receiving end program, the data transmitted can voluntarily be write by being written on interim " .dat " file data processor to run at once
Data processing and display software, constantly parse ephemeral data file, and interacted with MATLAB runtime environment MCR, will
Treated, and data are shown in time, as shown in Fig. 5 a- Fig. 5 c.
Signal acquisition part uses external antenna and software tool collecting signal data, adjusts transmitting antenna A and receives day
The distance between line B L1, reflected signal strength F caused by fine motion is made effectively interfere the intensity S of direct signal, so that
The Overlay of F and S, the i.e. average value of CSI are greater than 0.5dB.
The detection signal for receiving feedback, decomposites in the detection signal of the feedback and each specifically acts and count
The frequency of calculation movement further includes pre-processing to received feedback detection signal, specifically, calculating data in data sequence
Item XiThe average value Avg of neighbouring N number of data itemi, by AvgiAs XiOr the new value including M-1 data item thereafter, moving distance
After M, aforementioned calculating process is repeated, until being moved to sequence end.
In an embodiment of the present invention, IREE algorithm is proposed, for decompositing each specific movement and calculating
The probability of movement：
Input：Subcarrier sequence I1..., In, sample frequency f；
Output：Instantaneous respiratory rate sequence F1..., Fn；
(1) it initializes any selection kth subcarrier and carries out difference processing, generate difference sequence
(2) merge monotony interval and enable t=1, P=0, Q=0；By the numerical value with being positive or with being negative adjacent in difference sequence
It is merged into a section, with section accumulated value Δ miAnd merge numerical value number Δ niIndicate the i-th section, can must add up value sequence
Δm1..., Δ mrWith counting sequence Δ n1..., Δ nr；
(3) if t is less than r, since the t of position, first is found in cumulative value sequence and is greater than given threshold value A1Δ maMake
For expiratory phase initial position；Otherwise it moves back；
(4) since s=a, cumulative Δ m is attemptedsWith Δ nsIf s is equal to r, exit；If there is Δ m at bsAccumulated value
Greater than M1, and Δ nsAccumulated value be not more than N1, then it is assumed that expiratory phase is found, t=b+1, Q=b are updated；Otherwise P=0, t=
T+1 turns (3)；
(5) if t is less than r, since the t of position, first is found in cumulative value sequence and is less than given threshold value A2Δ mcMake
For expiration phase initial position；Otherwise it exits；
(6) since s=c, cumulative Δ m is attemptedsWith Δ nsIf s is equal to r, exit；If there is Δ m at dsAccumulated value
Less than M2, and Δ nsAccumulated value be not more than N2, then it is assumed that expiration phase is found, t=d+1 is updated；Otherwise P=0, t=t+1 turn
(3)；
(7) if P is 0, P=Q, turn (3)；
(8) add up Δ nPTo Δ nQ-1, it is denoted as S, then has instantaneous respiratory rate Fv=60f/S updates P=Q, turns (3).
Step 3: assessing action state in real time, and carry out real-time display according to the operating frequency information.
In an embodiment of the present invention, real-time system evaluation part, according to information such as the operating frequencies of algorithm detection, in real time
Assess action state.In the example of breathing detection, Fig. 6 is the respiratory rate of the different personnel of real-time monitoring, it can be seen that
The respiratory rate of experimenter A is mainly 10-16/min, and the respiratory rate of experimenter B is mainly 8-12/min, meets year
The respiratory rate 8-24.8/min of light people.And it can be seen that the respiratory rate mean value of personnel B significantly lower than people by real-time monitoring
The respiratory rate mean value of member A, this illustrates that personnel B may be in certain and it is allowed to breathe slower state.It learns, detected through linking up
Cheng Zhong, personnel A compare when breathing naturally, personnel B is somewhat nervous, and the latter's breathing pattern is biased to deeply breathe, this and assessment result one
It causes.Additionally its physiological status can be assessed in the variation of the respiratory rate of different time by comparing same personnel.
The embodiments described above only express several embodiments of the present invention, and the description thereof is more specific and detailed, but simultaneously
Limitations on the scope of the patent of the present invention therefore cannot be interpreted as.It should be pointed out that for those of ordinary skill in the art
For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to guarantor of the invention
Protect range.Therefore, the scope of protection of the patent of the invention shall be subject to the appended claims.
Claims (4)
1. a kind of method of micro- deformation real-time monitoring assessment based on WiFi signal, which is characterized in that the method includes as follows
Step：
Step 1: setting network detects environment, detection signal is sent based on network detection environment；
Step 2: receiving the detection signal of feedback, decomposites in the detection signal of the feedback and each specifically act and count
The frequency of calculation movement；
Step 3: assessing action state in real time, and carry out real-time display according to the operating frequency information.
2. the method for micro- deformation real-time monitoring assessment according to claim 1 based on WiFi signal, which is characterized in that institute
It states setting network and detects environment, specifically, the detection network to be formed a whole with several pairs of antennas, wherein transmitting antenna is
A1, A2, A3 ... An, receiving antenna B1, B2, B3 ... Bn make abdomen shape caused by breathing to every a pair of of monitoring aerial for
Conjugate the X-axis in antenna pair and close to the biggish internal layer Fresnel region of energy, antenna to the distance between be set as 20-
The sample frequency of 25cm, data are set as 20-100HZ.
3. the method for micro- deformation real-time monitoring assessment according to claim 1 based on WiFi signal, which is characterized in that institute
The detection signal for receiving feedback is stated, the frequency of each specific movement and calculating action in the detection signal of the feedback is decomposited
Rate further includes pre-processing to received feedback detection signal, specifically, calculating data item X in data sequenceiNeighbouring N
The average value Avg of a data itemi, by AvgiAs XiOr the new value including M-1 data item thereafter, after moving distance M, repeat
Aforementioned calculating process is executed, until being moved to sequence end.
4. the method for micro- deformation real-time monitoring assessment according to claim 1 based on WiFi signal, which is characterized in that institute
The frequency of each specific movement and calculating action in the detection signal for decomposite the feedback is stated, specifically,
Input：Subcarrier sequence I1..., In, sample frequency f；
Output：Instantaneous respiratory rate sequence F1..., Fn；
(1) it initializes any selection kth subcarrier and carries out difference processing, generate difference sequence
(2) merge monotony interval and enable t=1, P=0, Q=0；By the numerical value merging with being positive or with being negative adjacent in difference sequence
At a section, with section accumulated value Δ miAnd merge numerical value number Δ niIndicate the i-th section, can must add up value sequence Δ
m1..., Δ mrWith counting sequence Δ n1..., Δ nr；
(3) if t is less than r, since the t of position, first is found in cumulative value sequence and is greater than given threshold value A1Δ maAs suction
Gas stage initial position；Otherwise it moves back；
(4) since s=a, cumulative Δ m is attemptedsWith Δ nsIf s is equal to r, exit；If there is Δ m at bsAccumulated value be greater than
M1, and Δ nsAccumulated value be not more than N1, then it is assumed that expiratory phase is found, t=b+1, Q=b are updated；Otherwise P=0, t=t+1,
Turn (3)；
(5) if t is less than r, since the t of position, first is found in cumulative value sequence and is less than given threshold value A2Δ mcAs exhaling
Gas stage initial position；Otherwise it exits；
(6) since s=c, cumulative Δ m is attemptedsWith Δ nsIf s is equal to r, exit；If there is Δ m at dsAccumulated value be less than
M2, and Δ nsAccumulated value be not more than N2, then it is assumed that expiration phase is found, t=d+1 is updated；Otherwise P=0, t=t+1 turn (3)；
(7) if P is 0, P=Q, turn (3)；
(8) add up Δ nPTo Δ nQ-1, it is denoted as S, then has instantaneous respiratory rate Fv=60f/S updates P=Q, turns (3).
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113203754A (en) * | 2021-05-13 | 2021-08-03 | 合肥工业大学 | Material inspection method based on wireless commercial equipment |
| CN113325008A (en) * | 2021-06-02 | 2021-08-31 | 合肥工业大学 | Non-contact material identification system and method based on WIFI equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130072764A1 (en) * | 2011-09-15 | 2013-03-21 | Haim Shtalryd | Systems and Methods of Movement Sensing Based Monitoring |
| CN105997086A (en) * | 2016-06-20 | 2016-10-12 | 北京大学 | Respiration detection method |
| CN106725488A (en) * | 2016-12-27 | 2017-05-31 | 深圳大学 | A kind of wireless field density breathing detection method, device and breathing detection instrument |
-
2018
- 2018-05-28 CN CN201810519221.8A patent/CN108903951B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130072764A1 (en) * | 2011-09-15 | 2013-03-21 | Haim Shtalryd | Systems and Methods of Movement Sensing Based Monitoring |
| CN105997086A (en) * | 2016-06-20 | 2016-10-12 | 北京大学 | Respiration detection method |
| CN106725488A (en) * | 2016-12-27 | 2017-05-31 | 深圳大学 | A kind of wireless field density breathing detection method, device and breathing detection instrument |
Non-Patent Citations (1)
| Title |
|---|
| JIAN LIU ,YAN WANG,ET AL.: "Tracking Vital Signs During Sleep Leveraging Off-the-shelf WiFi", 《IN PROCEEDINGS OF THE 16TH ACM INTERNATIONAL SYMPOSIUM ON MOBILE AD HOC NETWORKING AND COMPUTING》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113203754A (en) * | 2021-05-13 | 2021-08-03 | 合肥工业大学 | Material inspection method based on wireless commercial equipment |
| CN113325008A (en) * | 2021-06-02 | 2021-08-31 | 合肥工业大学 | Non-contact material identification system and method based on WIFI equipment |
| CN113325008B (en) * | 2021-06-02 | 2022-09-20 | 合肥工业大学 | Non-contact material identification system and method based on WIFI equipment |
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