CN107595274A - Back cushion based on HRV non-contact detection emotional stress - Google Patents
Back cushion based on HRV non-contact detection emotional stress Download PDFInfo
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Abstract
The invention provides a kind of back cushion based on HRV non-contact detection emotional stress, including：Back cushion body, the data operation box in back cushion body, and the piezoelectric transducer contacted in back cushion body and with data operation box.Back cushion structure based on HRV non-contact detection emotional stress is simple, it is easy to use, pass through the cooperation between the piezoelectric transducer and data operation box that are arranged in back cushion, can be on the premise of non-direct contact be kept with user, gather the body shake conducted signal of user, and the pressure signal that is gathered by data operation box to piezoelectric transducer and pressure signal is handled, calculate the HRV parameters included in pressure signal, matched by HRV parameters with exponential model, realize to tester emotional stress, anti-pressure ability, the analysis of fatigue exponent, so as to monitor the emotional stress of user and condition at any time, it is easy to make intervention in time, prevent user's state from continuing to deteriorate.
Description
Technical field
The present invention relates to emotional stress monitoring device, and in particular to one kind is based on HRV non-contact detection mood
The back cushion of pressure.
Background technology
HRV (Heart rate variability HRV) refers to what heart rate rhythm speed was occurred with the time
Change.HRV is the trickle time change and its rule for analyzing cardiac cycle one by one.The conventional heart of this change in body surface record
Often it is difficult to measure or because small and not significant on electrograph, is accustomed to the regular sinus rhythm of description on routine electrocardiogram never etc.
Do not made a variation in heart rate.HRV research object is the time difference of gradually cardiac cycle, is enumerated between human body each cardiac cycle
Difference can show that a lot of unordered parameters seemingly reflect the continuous momentary fluctuation of heart rate.The fluctuation of heart rate is not accidental
But by internal neurohumoral regulation and control, for the reaction for adapting to different physiological status or some pathological states are made.
The heart caused by the modulating action that HRV HF compositions reflection respiratory activity is conducted finally by cardiac vagus nerve fiber
Rate fluctuating change, in document also referred to as " hennig-Lommel sign " (respiratory arrhythmia, RSA).Respiratory activity leads to
Crossing central mechanism and mechanicalness influences two approach to heart rate generation modulating action, and HRV HF peak height is walked to spread out of with heart fan lives
The dynamic degree of modulation to heart rate is related in conspicuousness.
Spectrum analysis finds that HRV generallys include high frequency (HF) composition and low frequency (LF) composition, and some scholars are by LF
It is further divided into two kinds of ultralow frequency and low frequency.Wherein, radio-frequency component and respiratory movement are synchronous, therefore the respiratory component that is otherwise known as,
Occur once within about 3 seconds, scholars think that radio-frequency component therein reflects parasympathetic function, and low-frequency component and high frequency into
The ratio (LF/HF) divided has reacted sympathetic activity.
Existing HRV measuring methods include short distance test and long-range test.Although long-range test accuracy is higher,
The in general testing time needs 24 hours or so, and measured patient needs whole day wear Holter patient monitor, user's
Many action can be all restricted, thus have in many cases user short distance can be selected to test.Short distance test referred in the short time
Interior (such as 5 minutes) are measured by task equipment, and although this method possesses time of measuring short, it is easy to use a little, but
It is that the result data fluctuation measured is big, poor repeatability, and resultant error and larger, often only research field can just use
This method measures to HRV.
According to above-mentioned principle, a series of method and product, such as Publication No. are also developed both at home and abroad at present：
CN106859625A Chinese patent application, " a kind of HRV measuring methods and device " is disclosed, the measuring method is obtaining
After original RR interval datas collection, a filtering process is first done to original RR interval datas collection, it is corresponding to obtain sinus rhythm
RR interval data collection, then again to RR interval datas collection by FFT and/or wavelet transformation, to RR interval datas
Collection carries out the processing of error, removes the error caused by the circadian changes such as breathing, obtains standard RR interval data collection,
Then HRV time domain indexes are calculated further according to standard RR interval datas collection, during this, can very limits the removal external world because
Influence of the element to RR interval datas, even if the time of measurement is shorter, RR interval datas are smaller, can also obtain more accurate meter
Calculate result, and after the HRV time domain indexes of short distance are obtained, can according to short distance HRV time domain indexes, using computation model,
24 hours HRV time domain indexes are calculated, thus, on the premise of computational accuracy is ensured, reduce measurement needs the HRV computational methods
The time to be used, meanwhile, it is capable to finally obtain accurate 24 hours HRV data.But carry out data acquisition using this method
When need and human contact, i.e., still need wearable device to aid in, consequently, it is possible to which measured patient needs to wear dynamic electrocardiogram
Figure patient monitor or other proprietary measuring apparatus, many action of user can be all restricted.
Also some scientific researches proposed to obtain HRV signals using contactless piezoelectric sensing method, such as：Publication number
A kind of " fatigue driving knowledge based on HRV non-contact measurement is disclosed for CN103824420A Chinese patent application
Other system ", including image collecting device, image processing apparatus and warning device, described image harvester are used to obtain in real time
Driver's face-image, and by driver's image transmitting of collection to image processing apparatus；Described image processing unit is used for root
The HRV of driver is obtained according to driver's image, and it is tired according to the driving of the HRV of driver acquisition driver
Labor state；The warning device carries for carrying out alarm when image processing apparatus judges that driver is in driving fatigue state
Show.The system obtains human body face image in real time using image collecting device, by driver's image transmitting of collection to image at
Device is managed, obtains the HRV of driver, and the driving fatigue shape of driver is obtained according to the HRV of driver
State.But the system uses the image recognition technology of complexity and algorithm, whole system cost is high, is not easy to promote.And due to
Ballistocardiography (BCG) physiological signal of piezoelectric sensing collection perceives to be passive, therefore acquisition signal is heterogeneous difficult, at present not
There is a kind of good processing method, it is all and the nothing because heterogeneous ballistocardiography (BCG) signal can not be handled that many researchs are final
Method obtains accurate HRV signals, and then can not realize industrialization.
The content of the invention
In view of the shortcomings of the prior art, the present invention proposes one kind and is based on HRV non-contact detection emotional stress
Back cushion, by placing piezoelectric transducer in back cushion, the heart rate and HRV data of user can be obtained, can be monitored at any time
The emotional stress and condition of user, it is easy to make intervention in time, prevents user's state from continuing to deteriorate, cause danger.
To realize above-mentioned technical proposal, the invention provides one kind to be based on HRV non-contact detection emotional stress
Back cushion, including：
Back cushion body, set in the back cushion body it is fluted, the back cushion body can be by sponge, memory sponge or
Some soft clothes are made；
Data operation box, the data operation box are placed in the groove of back cushion body and fixed by bonnet, the number
Include cooperating according to computing box and the computing box cover and computing box lower cover of detachable connection, master control borad are arranged on computing box
Between lid and computing box lower cover, the battery for master control borad power supply is also equipped between computing box cover and computing box lower cover, wirelessly
Communication module and center processor are installed on master control borad, and data operation box is the core component of whole back cushion, for data
Lump and computing；
Piezoelectric transducer, the piezoelectric transducer are fixed on computing box cover by cap, the cap and pressure
Position corresponding to electric transducer is provided with projection, and computing box cover is provided with the position limiting structure of limitation cap movement, the encapsulation
Lid be arranged in parallel with piezoelectric transducer, and after cap stress, raised stress oppresses piezoelectric transducer, and piezoelectric sensors are defeated
Go out signal, cap is kept in the center when the power that disappears or static state are to power, signal output part and the data operation box of the piezoelectric transducer
The signal input part of master control borad connects, and the master control borad in data operation box receives the pressure signal of piezoelectric transducer collection and to pressure
Force signal is handled, and is calculated the HRV parameters included in pressure signal, is matched by HRV parameters with exponential model, is realized
Analysis to tester emotional stress, anti-pressure ability, fatigue exponent.
Preferably, the data operation box handles the pressure signal of piezoelectric transducer reception as follows：
Step 1, body jolt-squeeze force signal is collected by piezoelectric transducer and pressure signal is converted into analog electrical signal, then
Transmit to computing box master control borad；
Step 2, center processor are sampled using sample frequency 1000Hz to analog electrical signal, by the data after sampling
Carry out discrete processes and preserved with stack, the design stack buffer time is 6s, then carries out 50Hz limits to signal in storehouse
Ripple and 1Hz second order IIR low-pass filtering treatments, separate BCG signals；
Step 3, the baseline interference merged in BCG signals is deleted using 0.02Hz high-pass filters, completed to BCG signals
Pretreatment；
Step 4, definition BCG signal transacting cycles are 30~120 beats/min, the preferable BCG of presetting main lobe width 100
Signal waveform, preferable BCG signals and storehouse signal covariance are solved, extract envelope；
The BCG signal J peaks of step 5, identification after noise reduction process, and solve phase Interval_JJ between BCG signals J-J
(i) the average value Mean_JJ of phase between all J-J in the range of detection time, is then solved, the BCG finally obtained according to solving believes
Between number J-J between phase Interval_JJ (i) and all J-J the average value Mean_JJ of phase calculate HRV time domain parameter SDNN and
PNN50；
Step 6, using Fast Lomb-Scargle periodogram compose analytic function to acquisition time model in step 5
HRV time domain parameters in enclosing carry out frequency domain power spectrum analysis, obtain HRV power spectrum, and it is total according to HRV power spectrum to solve heart
Performance number TP, high frequency power value HF, low frequency power value LF, and LF/HF ratios；
Step 7, establish emotional stress index LF/HF models, fatigue exponent PNN50 models and resistance to compression index SDNN models；
Step 8, the HRV time domain parameters of acquisition and frequency domain parameter matched with the model established in step 7, realized pair
The analysis of tester emotional stress, anti-pressure ability, fatigue exponent.
Preferably, the detailed process that envelope is extracted in the step 4 is as follows：
Step 41：It is 30~120 beats/min to define the BCG signal transacting cycles, and no body moves disturbed condition push-down stack signal and is
X (t), t=1 ..., 6000, preferable BCG signals are constructed, be defined as y (t), t=1 ..., 6000, t and counted for time-domain sampling；
Step 42：Setting BCG signal main lobe widths are set as 100, and remaining secondary lobe vector mends 0, BCG peak values max (y (t))
=max (x (t)), solves x (t) and y (t) covariance functions, and specific formula is as follows：
Z (t)=Cov { x (t), y (t) } formula 1
Wherein：Z (t) is x (t) and y (t) covariance functions, and x (t) is collection and is stored in the sign in storehouse, y
(t) it is the preferable BCG signals of construction；
Step 43：Handled by covariance, using the strong correlation of signal in storehouse and BCG signals, pressed down to the full extent
Interference of the Gaussian noise processed to BCG signals；
Step 44：Z (t) Hilbert transform Z (f) is solved, specific formula is as follows：
Z (f)=Hilbert { z (t) } formula 2
Wherein Z (f) represents z (t) Hilbert transform, takes Z (f) modulus value, so as to obtain Z (f) signal characteristic envelopes,
And using length as 5 time window function smoothing processing, eliminate High-frequency Interference.
Preferably, the detailed process that HRV time domain parameter SDNN and PNN50 are calculated in the step 5 is as follows：
Center processor in step 51, master control borad identifies the peak point J peaks of the BCG signals after noise reduction process, so
Service life is 1s time slip-window afterwards, and maximal peak point is J peaks in selection time window, i.e. Peak (i)=max { Z (f) }；
Phase between step 52, solution J-J, specific formula for calculation are as follows：
Interval_JJ (i)=Peak (i+1)-Peak (i) formula 3
Wherein：Interval_JJ (i) time values between BCG signals J-J；Peak (i+1) represents i+1 BCG signal J peaks
Value, Peak (i) represent i-th of BCG signal J peak value；
Phase between step 53, the irrational J-J of rejecting, kick-out condition are as follows：
Condition 1)：As Interval_JJ (i)=Peak (i+1)-Peak (i)<0.5s；
Condition 2)：As Interval_JJ (i)=Peak (i+1)-Peak (i)>2.0s；
Condition 3)：Exceed average J-J when phase between adjacent J-J, such as Interval_JJ (i), Interval_JJ (i+1) fluctuation
Between the phase 30%；
After step 54, rejecting abnormalities J-J interval datas, the average value of phase between all J-J in the range of detection time is solved
Mean_JJ,
Step 55, according to solving between obtained BCG signals J-J being averaged for phase between phase Interval_JJ (i) and all J-J
Value Mean_JJ and the time domain parameter SDNN and PNN50 for calculating HRV respectively according to formula 4 to formula 5, specific formula for calculation are as follows：
Wherein：The standard deviation of SDNN phases between whole sinus property heartbeat RR, it is HRV time domain parameter；Interval_JJ(i)
The time value between BCG signals J-J；The average value of Mean_JJ phases between all J-J；T phases between effectively J-J in the range of detection time
Number；
HRV time domain parameter PNN50 calculation formula are as follows：
N{JJ>Mean_JJ}The phase is more than 50ms number, N between phase and average JJ between expression JJtotalThe phase is total between representing JJ.
Preferably, emotional stress index LF/HF models, fatigue exponent PNN50 models and resistance to compression are established in the step 7 to refer to
The detailed process of number SDNN models is as follows：
Step 71, establish emotional stress index LF/HF models：Mainly determined, be defined as follows by endocrine index LF/HF：
When LF/HF scopes are in (0-0.4) ＆ (3.46-4), 0~30 point of stress ability score；When LF/HF scopes are in (0.4-1) ＆
(2.92-3.46), 30~60 points of stress ability score；When LF/HF scopes are in (1-1.6) ＆ (2.56-2.92), stress ability
60~80 points of score；When LF/HF scopes are in (1.6-2.2) ＆ (2.2-2.56), 80~100 points of stress ability score；
Step 72, establish fatigue exponent PNN50 models：Determined, be defined as follows by time domain HRV parameters PNN50：Work as PNN50>
=49, fatigue exponent score 0~30；When PNN50 is in scope (1-2) ＆ (12-49), fatigue exponent score 30~60；When
PNN50 is in scope (3-4) ＆ (8-12), fatigue exponent score 60~80；When PNN50 is in scope (5-8), fatigue exponent obtains
Divide 80~100；
Step 73, establish resistance to compression index SDNN models：Determined, be defined as follows by time domain HRV parameters SDNN：When SDNN is in
Scope (0-25) ＆ (960+), resistance to compression index score 0~30；When SDNN is in scope (25-50) ＆ (240-960), resistance to compression index
Score 30~60；When SDNN is in scope (50-100), resistance to compression index score 60~80；When SDNN is in scope (100-160),
Fatigue exponent score 80~100.
When the HRV time domain parameters and frequency domain parameter being calculated in computing box according to requirement in step 7 respectively with being loaded in
Emotional stress index LF/HF models, fatigue exponent PNN50 models and resistance to compression index SDNN models in computing box carry out automatic
Match somebody with somebody, so as to quickly realize the analysis to tester emotional stress, anti-pressure ability, fatigue exponent, so as to which monitoring makes at any time
The emotional stress and condition of user, it is easy to make intervention in time, prevents user's state from continuing to deteriorate, cause danger.
Preferably, the present apparatus also includes alarm, and the alarm is connected with the master control borad on data operation box, works as data
When the data that computing box calculates are higher than setting value, alarm automatic alarm, it is easy to user to pinpoint the problems in time.
Preferably, charging head is additionally provided with the back cushion body, the charging head is by lid, charging core on charging head and fills
Dateline lower cover is formed, and charging core is arranged on charging head between lid and charging head lower cover, and charging core passes through wire and data operation
Battery connection in box, can realize the quick charge to battery in data capsule by charging head, facilitate the use of this back cushion.
Preferably, fin is also equipped with lid under the computing box, the fin is bonded in master control by heat-conducting glue
The lower section of plate, because data operation box workload great Yi generates heat, master control borad in data operation box can be accelerated by heat-conducting glue
Transmission of the heat to fin, then avoid master control borad from overheating the rapid heat dissipation in master control borad using fin.
Preferably, the wireless communication module is WIFI communication modules or bluetooth communication, is communicated mould by WIFI
Block or bluetooth communication can realize the connection of the terminal device such as this back cushion and mobile phone, PC, PAD.
Preferably, the rear cap surface offers equally distributed heat emission hole, beneficial to the radiating of data operation box.
A kind of back cushion and application based on HRV non-contact detection emotional stress provided by the invention it is beneficial
Effect is：
1) back cushion structure based on HRV non-contact detection emotional stress is simple, easy to use, by setting
The cooperation between the piezoelectric transducer in back cushion and data operation box is put, can be before non-direct contact be kept with user
Put, gather the body shake conducted signal of user, and the pressure signal that is gathered by data operation box to piezoelectric transducer and right
Pressure signal is handled, and is calculated the HRV parameters included in pressure signal, is matched by HRV parameters with exponential model, real
Now to the analysis of tester emotional stress, anti-pressure ability, fatigue exponent, so as to monitor the emotional stress of user at any time
And condition, it is easy to make intervention in time, prevents user's state from continuing to deteriorate, cause danger；
2) back cushion based on HRV non-contact detection emotional stress is keeping indirect using with tester
On the premise of contact, acquisition volume shakes excitation of the conducted signal to piezoelectricity, obtains continuous ballistocardiography BCG signals, and pass through data
The modes such as discrete processes, storehouse preservation, the processing of second order IIR low-pass filtering treatments, differential filtering, covariance processing are realized to BCG
The accurate extraction of signal and noise reduction process, eventually through the average value of phase is accurately asked between phase and J-J between solution BCG signals J-J
HRV time domain parameter and frequency domain parameter.Need to be direct to test object consequently, it is possible to solve existing wearable product collection signal
The problem of contacting and limiting test object action and bring inconvenience, and signal is taken by piezoelectric transducer, can completely it protect
Whole physical features of BCG signals are stayed, more accurately to support based on the analysis such as BCG signal cardiac cycles and HRV；This back cushion
Realize and heterogeneous BCG signals are accurately extracted, and obtain high-precision HRV information, and pass through the emotional stress with foundation
Index LF/HF models, fatigue exponent PNN50 models and resistance to compression index SDNN models are matched, and realization monitors user at any time
Emotional stress and condition, be easy to make intervention in time, convenient and swift and accuracy rate is high, usage scenario can be family,
In office or automobile, industrialization and popularization are easy to implement.
Brief description of the drawings
Fig. 1 is the stereochemical structure top view of the back cushion based on HRV non-contact detection emotional stress in invention.
Fig. 2 is the stereochemical structure upward view of the back cushion based on HRV non-contact detection emotional stress in invention.
Fig. 3 is the explosive view I of the back cushion based on HRV non-contact detection emotional stress in invention.
Fig. 4 is the explosive view II of the back cushion based on HRV non-contact detection emotional stress in invention.
Fig. 5 is DevCenter impact figure BCG signal temporal envelope figures.
In figure：1st, back cushion body；11st, installation groove；2nd, charging head；21st, covered on charging head；22nd, charging chip；23rd, fill
Dateline lower cover；3rd, bonnet；4th, data operation box；41st, computing box cover；42nd, pressure-ray film；43rd, battery；44th, master control borad；45th, dissipate
Backing；46th, wireless communication module；47th, computing box lower cover；48th, heat-conducting glue；5th, piezoelectric transducer；6th, cap.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Whole description, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.Ability
The every other embodiment that domain ordinary person is obtained under the premise of creative work is not made, belong to the protection of the present invention
Scope.
Embodiment：A kind of back cushion based on HRV non-contact detection emotional stress.
Referring to figs. 1 to shown in Fig. 5, a kind of back cushion based on HRV non-contact detection emotional stress includes：
The back cushion body 1 being fabricated by memory sponge, fluted 11 is set in back cushion body 1, data operation box 4 is placed on
Fixed in the groove 11 of back cushion body 1 and by bonnet 3, the surface of bonnet 3 offers equally distributed heat emission hole, is transported beneficial to data
The radiating of box 4 is calculated, the data operation box 4 includes cooperating and the computing box cover 41 and computing box lower cover of detachable connection
47, master control borad 44 is arranged between computing box cover 41 and computing box lower cover 47, computing box cover 41 and computing box lower cover 47 it
Between be also equipped with for master control borad 44 power battery 43, WIFI wireless communication modules 46 and center processor are installed in master control borad
On 44, the connection of the terminal device such as this back cushion and mobile phone, PC, PAD, center processor can be realized by WIFI communication modules 46
For signal transacting and the Auto-matching of follow-up exponential model, fin 45, the radiating are also equipped with computing box lower cover 47
Piece 45 is bonded in the lower section of master control borad 44 by heat-conducting glue 48, because data operation box workload great Yi generates heat, passes through heat-conducting glue
48 can accelerate transmission of the heat of master control borad 44 in data operation box 4 to fin 45, then using fin 45 by master control
Rapid heat dissipation in plate 44, master control borad 44 is avoided to overheat, data operation box 4 is the core component of whole back cushion, for counting
According to lump and computing；
Also include piezoelectric transducer 5, the piezoelectric transducer 5 is fixed on computing box cover 41 by cap 6, described
Cap 6 is provided with projection with 5 corresponding position of piezoelectric transducer, and computing box cover 41 is provided with the limit that limitation cap 6 moves
Position groove, cap 6 be arranged in parallel with piezoelectric transducer 5, and after 6 stress of cap, raised stress oppresses piezoelectric transducer 5, pressure
Cap is kept in the center when the compression output signal of electric transducer 5, the power that disappears or static state are to power, and the signal of the piezoelectric transducer 5 is defeated
Go out end to be connected and fix by pressure-ray film 42, the master in data operation box 4 with the signal input part of data operation box master control borad 44
Control plate 44 receives the pressure signal that piezoelectric transducer 5 gathers and pressure signal is handled, and calculates what is included in pressure signal
HRV parameters, matched by HRV parameters with exponential model, realize and tester emotional stress, anti-pressure ability, fatigue are referred to
Several analyses；
Also include alarm, the alarm is connected with the master control borad 44 on data operation box 4, when data operation box 4 is counted
When the data of calculation are higher than setting value, alarm automatic alarm, it is easy to user to pinpoint the problems in time；
Charging head 2 is additionally provided with the back cushion body 1, the charging head 2 is by lid on charging head 21, charging core 22 and fills
Dateline lower cover 23 is formed, and charging core 22 is arranged on charging head between lid 21 and charging head lower cover 23, and charging core 22 passes through wire
It is connected with the battery 43 in data operation box 4, the quick charge to battery 43 in data capsule 4 can be realized by charging head 2, with
Facilitate the use of this back cushion.
In the present embodiment, when specifically used, after human contact's back cushion, cap 6 in back cushion body 1 by
After power, raised stress oppresses piezoelectric transducer 5, the compression output signal of piezoelectric transducer 5, and piezoelectric transducer 5 is converted to body shake
Analog electrical signal, piezoelectric transducer 5 are handled the center processor that analog electrical signal is delivered in data operation box 4, number
Handle the pressure signal of the reception of piezoelectric transducer 5 as follows according to computing box 4：
Step 1, piezoelectric transducer 5 collect the body jolt-squeeze force signal of human body and body shake are converted into analog electrical signal, then
Transmit to computing box master control borad 44, due to being gathered by the non-contact type signal of piezoelectric transducer 5, therefore only need human body and back cushion
Contact, you can realize the collection of the body jolt-squeeze force signal of human body, solving existing wearable product collection signal need to be to test pair
The problem of being brought inconvenience as directly contacting and limiting test object action；
Center processor in step 2, master control borad 44 is sampled using sample frequency for 1000Hz to analog electrical signal, sampling
Discrete data is 1000 points per second afterwards；Then, it is contemplated that the real-time detection of signal is recalled with error correction, and design cache-time window is 6s
(6000 points), are preserved with stack, and it is 1s (1000 points) to read with memory gap；Then, it is contemplated that discrete data be comprising
There are BCG, breathing, body dynamic and the aliasing signal of noise, aliasing signal pre-processed using second order IIR low-pass filtering treatments,
BCG signal behaviors low pass is 1Hz by frequency, and it by frequency be 0.2Hz that breath signal, which selects low pass, thus by BCG signals from
By being precisely separated out in BCG, breathing, the aliasing signal that body moves and noise forms；
Step 3, center processor ignore collection original state aliasing body and move strongly disturbing BCG signals, and are filtered using difference
Ripple removes Baseline Survey, i.e., the baseline interference merged in BCG signals is deleted using 0.02Hz high-pass filters, completes to believe BCG
Number pretreatment；
Step 4, definition BCG signal transacting cycles are 30~120 beats/min, the preferable BCG of presetting main lobe width 100
Signal waveform, preferable BCG signals and storehouse signal covariance are solved, extract envelope；
Its specific process is：Signal transacting scheme is embedded in center processor, for the signal pre-processed after filtering,
Specific aim noise reduction process is carried out,
First, it is x (t), t=1 ..., 6000 to define no body and move disturbed condition push-down stack signal；Then, construction is preferable
BCG signals (as shown in Figure 5), it is defined as y (t), t=1 ..., 6000；In view of conventional sign BCG signals cycle for 30~
120 beats/min, BCG signal main lobe widths are set as 100, remaining secondary lobe vector benefit 0, meanwhile, define BCG peak value max (y
(t))=max (x (t)), x (t) and y (t) covariance functions are solved, it is as follows：
Z (t)=Cov { x (t), y (t) }
Wherein：Z (t) is x (t) and y (t) covariance functions, and x (t) is collection and is stored in the sign in storehouse, y
(t) it is the preferable BCG signals of construction；
Then handled by covariance, using the strong correlation of signal in storehouse and BCG signals, inhibited to the full extent
Interference of the Gaussian noise to BCG signals；
Finally, it is contemplated that high fdrequency component caused by the otherness between construction BCG signals and actual acquisition BCG signals is done
Disturb, solve z (t) Hilbert transform Z (f)=Hilbert { z (t) } and Modulus of access, so as to obtain Z (f) signal characteristic envelopes,
Using length as 5 time window function smoothing processing, High-frequency Interference is eliminated；
It is complete to retain BCG signal physical features by the processing of step 2, step 3 and step 4 to BCG signals, and realize
Heterogeneous BCG signals are accurately extracted, to support based on the analysis such as BCG signal cardiac cycles and HRV, for follow-up high accuracy
The acquisition of HRV information provides strong support；
Step 5, signal envelope peak point is solved by center processor, the peak point of BCG signals after identification pretreatment, i.e.,
J peaks, it is contemplated that BCG is in conventional 30~120 beats/min scope under collection environment, and delimiting period is 1s (1000 points) cunning
Time window is moved, maximal peak point is J peaks in selection time window, i.e.,
Peak (i)=max { Z (f) }
And solve the phase between J-J：
Interval_JJ (i)=Peak (i+1)-Peak (i)
Wherein：Interval_JJ (i) time values between BCG signals J-J；Peak (i+1) represents i+1 BCG signal J peaks
Value, Peak (i) represent i-th of BCG signal J peak value；
The constraints being in view of heart rate in the range of 30~120 correspond to the phase between J-J should be 0.5s~2s (500 points~
2000 points), and heart rate do not possess the characteristic of mutation in a short time, rejects the phase between irrational J-J first, kick-out condition is such as
Under：
Condition 1)：As Interval_JJ (i)=Peak (i+1)-Peak (i)<0.5s；
Condition 2)：As Interval_JJ (i)=Peak (i+1)-Peak (i)>2.0s；
Condition 3)：Exceed average J-J when phase between adjacent J-J, such as Interval_JJ (i), Interval_JJ (i+1) fluctuation
Between the phase 30%；
After rejecting abnormalities J-J interval datas, the average value of phase between all limited J-J in the range of detection time, definition are solved
For Mean_JJ, then HRV time domain charactreristic parameter includes the standard of phase (being based on the phase between BCG signals J-J) between whole sinus property heartbeat RR
Poor (SDNN, standard diviation of NN intervals), is defined as follows：
Wherein：The standard deviation of SDNN phases between whole sinus property heartbeat RR, it is HRV time domain parameter；Interval_JJ(i)
The time value between BCG signals J-J；The average value of Mean_JJ phases between all J-J；T phases between effectively J-J in the range of detection time
Number；
Time domain HRV is based on simultaneously, the characteristic parameters such as PNN50, DC can be solved, be defined as follows：
HRV time domain parameter PNN50 calculation formula are as follows：
N{JJ>Mean_JJ}The phase is more than 50ms number, N between phase and average JJ between expression JJtotalThe phase is total between representing JJ；
Step 6, carry out frequency-domain analysis and the application based on time frequency analysis to time domain HRV parameters and JJ interval datas, use
Fast Lomb-Scargle periodogram spectrum analytic functions enter to the HRV time domain parameters in step 5 in the range of acquisition time
Line frequency domain power spectrumanalysis, obtains HRV power spectrum, and center processor can go out heart general power according to HRV power spectrum automatic calculations
Value TP, high frequency power value HF, low frequency power value LF, and LF/HF ratios；
Realized by step 5 and step 6 and the high accuracy of frequency domain HRV parameters and time domain HRV parameters is obtained, so as to for after
Continuous Model Matching provides accurate correction data；
Step 7, emotional stress index LF/HF models, fatigue exponent PNN50 models and resistance to compression index SDNN models are established,
Its detailed process is as follows：
Step 71, establish emotional stress index LF/HF models：Mainly determined, be defined as follows by endocrine index LF/HF：
When LF/HF scopes are in (0-0.4) ＆ (3.46-4), 0~30 point of stress ability score；When LF/HF scopes are in (0.4-1) ＆
(2.92-3.46), 30~60 points of stress ability score；When LF/HF scopes are in (1-1.6) ＆ (2.56-2.92), stress ability
60~80 points of score；When LF/HF scopes are in (1.6-2.2) ＆ (2.2-2.56), 80~100 points of stress ability score；
Step 72, establish fatigue exponent PNN50 models：Determined, be defined as follows by time domain HRV parameters PNN50：Work as PNN50>
=49, fatigue exponent score 0~30；When PNN50 is in scope (1-2) ＆ (12-49), fatigue exponent score 30~60；When
PNN50 is in scope (3-4) ＆ (8-12), fatigue exponent score 60~80；When PNN50 is in scope (5-8), fatigue exponent obtains
Divide 80~100；
Step 73, establish resistance to compression index SDNN models：Determined, be defined as follows by time domain HRV parameters SDNN：When SDNN is in
Scope (0-25) ＆ (960+), resistance to compression index score 0~30；When SDNN is in scope (25-50) ＆ (240-960), resistance to compression index
Score 30~60；When SDNN is in scope (50-100), resistance to compression index score 60~80；When SDNN is in scope (100-160),
Fatigue exponent score 80~100；
It is above-mentioned establish above-mentioned model after, can be stored directly in the center processor of data operation box 4, and each
Corresponding alarm limit value is set in exponential model, once the HRV time domain parameters or frequency domain that are calculated in data operation box 4
Parameter is higher than the alarm limit value of setting, alarm automatic alarm；
Step 8, by the HRV time domain parameters and frequency domain parameter that are calculated in computing box respectively with being required according in step 7
Emotional stress index LF/HF models, fatigue exponent PNN50 models and the resistance to compression index SDNN models being loaded in computing box are carried out
Auto-matching, shown, can be quickly realized to tester emotional stress, anti-pressure ability, fatigue exponent by different numerical value
Analysis, once the HRV time domain parameters or frequency domain parameter that are calculated in data operation box 4 higher than setting alarm limit value
When, alarm automatic alarm, so as to monitor the emotional stress and condition of user at any time, it is easy to make intervention in time, prevents
Only user's state continues to deteriorate, and causes danger.
Described above is presently preferred embodiments of the present invention, but the present invention should not be limited to the embodiment and accompanying drawing institute is public
The content opened, so every do not depart from the lower equivalent or modification completed of spirit disclosed in this invention, both fall within protection of the present invention
Scope.
Claims (10)
- A kind of 1. back cushion based on HRV non-contact detection emotional stress, it is characterised in that including：Back cushion body, set in the back cushion body fluted；Data operation box, the data operation box are placed in the groove of back cushion body and fixed by bonnet, the data fortune Calculate box include cooperate and detachable connection computing box cover and computing box lower cover, master control borad be arranged on computing box cover and Between computing box lower cover, the battery for master control borad power supply, radio communication are also equipped between computing box cover and computing box lower cover Module and center processor are installed on master control borad；Piezoelectric transducer, the piezoelectric transducer are fixed on computing box cover by cap, and the cap passes with piezoelectricity Position corresponding to sensor be provided with projection, computing box cover be provided with limitation cap movement position limiting structure, the cap with Piezoelectric transducer be arranged in parallel, and after cap stress, raised stress oppresses piezoelectric transducer, piezoelectric sensors output letter Number, cap is kept in the center when the power that disappears or static state are to power, signal output part and the data operation box master control of the piezoelectric transducer The signal input part of plate connects, and the master control borad in data operation box receives the pressure signal of piezoelectric transducer collection and pressure is believed Number handled, calculate the HRV parameters included in pressure signal, matched by HRV parameters with exponential model, realized to survey The analysis of examination person emotional stress, anti-pressure ability, fatigue exponent.
- 2. the back cushion according to claim 1 based on HRV non-contact detection emotional stress, it is characterised in that：Institute State the pressure signal that data operation box handles piezoelectric transducer reception as follows：Step 1, body jolt-squeeze force signal is collected by piezoelectric transducer and pressure signal is converted into analog electrical signal, then transmitted To computing box master control borad；Step 2, center processor are sampled using sample frequency 1000Hz to analog electrical signal, and the data after sampling are carried out Discrete processes are simultaneously preserved with stack, and the design stack buffer time is 6s, then in storehouse signal carry out 50Hz notches and 1Hz second order IIR low-pass filtering treatments, separate BCG signals；Step 3, the baseline interference merged in BCG signals is deleted using 0.02Hz high-pass filters, complete the pre- place to BCG signals Reason；Step 4, definition BCG signal transacting cycles are 30~120 beats/min, the preferable BCG signals of presetting main lobe width 100 Waveform, preferable BCG signals and storehouse signal covariance are solved, extract envelope；The BCG signal J peaks of step 5, identification after noise reduction process, and phase Interval_JJ (i) between BCG signals J-J is solved, Then the average value Mean_JJ of phase between all J-J in the range of detection time, the BCG signals J-J finally obtained according to solution are solved Between between phase Interval_JJ (i) and all J-J the phase average value Mean_JJ calculate HRV time domain parameter SDNN and PNN50；Step 6, analytic function composed in step 5 in the range of acquisition time using Fast Lomb-Scargle periodogram HRV time domain parameters carry out frequency domain power spectrum analysis, obtain HRV power spectrum, and heart general power is solved according to HRV power spectrum Value TP, high frequency power value HF, low frequency power value LF, and LF/HF ratios；Step 7, establish emotional stress index LF/HF models, fatigue exponent PNN50 models and resistance to compression index SDNN models；Step 8, by the emotional stress index LF/HF models established in the HRV time domain parameters and frequency domain parameter of acquisition and step 7, Fatigue exponent PNN50 models and resistance to compression index SDNN models are matched, realize to tester emotional stress, anti-pressure ability, The analysis of fatigue exponent.
- 3. the back cushion according to claim 2 based on HRV non-contact detection emotional stress, it is characterised in that：Institute The detailed process for stating extraction envelope in step 4 is as follows：Step 41：It is 30~120 beats/min to define the BCG signal transacting cycles, and it is x that no body, which moves disturbed condition push-down stack signal, (t), t=1 ..., 6000, preferable BCG signals are constructed, is defined as y (t), t=1 ..., 6000, t and is counted for time-domain sampling；Step 42：Setting BCG signal main lobe widths are set as 100, and remaining secondary lobe vector mends 0, BCG peak values max (y (t))=max (x (t)), solves x (t) and y (t) covariance functions, and specific formula is as follows：Z (t)=Cov { x (t), y (t) } formula 1Wherein：Z (t) is x (t) and y (t) covariance functions, and to gather and being stored in the sign in storehouse, y (t) is x (t) The preferable BCG signals of construction；Step 43：Handled by covariance, using the strong correlation of signal in storehouse and BCG signals, suppressed to the full extent high Interference of this noise to BCG signals；Step 44：Z (t) Hilbert transform Z (f) is solved, specific formula is as follows：Z (f)=Hilbert { z (t) } formula 2Wherein Z (f) represents z (t) Hilbert transform, takes Z (f) modulus value, so as to obtain Z (f) signal characteristic envelopes, and with Length is 5 time window function smoothing processing, eliminates High-frequency Interference.
- 4. the back cushion according to claim 2 based on HRV non-contact detection emotional stress, it is characterised in that：Institute The detailed process for stating time domain parameter SDNN and PNN50 that HRV is calculated in step 5 is as follows：Center processor in step 51, master control borad identifies the peak point J peaks of the BCG signals after noise reduction process, then makes The time slip-window for being 1s with the cycle, maximal peak point is J peaks in selection time window, i.e. Peak (i)=max { Z (f) }；Phase between step 52, solution J-J, specific formula for calculation are as follows：Interval_JJ (i)=Peak (i+1)-Peak (i) formula 3Wherein：Interval_JJ (i) time values between BCG signals J-J；Peak (i+1) represents i+1 BCG signal J peak values, Peak (i) represents i-th of BCG signal J peak value；Phase between step 53, the irrational J-J of rejecting, kick-out condition are as follows：Condition 1)：As Interval_JJ (i)=Peak (i+1)-Peak (i)<0.5s；Condition 2)：As Interval_JJ (i)=Peak (i+1)-Peak (i)>2.0s；Condition 3)：When the phase between adjacent J-J, if Interval_JJ (i), Interval_JJ (i+1) fluctuation are more than the phase between average J-J 30%；After step 54, rejecting abnormalities J-J interval datas, the average value Mean_ of phase between all J-J in the range of detection time is solved JJ,Step 55, the average value according to the phase between phase Interval_JJ (i) and all J-J between obtained BCG signals J-J that solves Mean_JJ and the time domain parameter SDNN and PNN50 for calculating HRV respectively according to formula 4 to formula 5, specific formula for calculation are as follows：Wherein：The standard deviation of SDNN phases between whole sinus property heartbeat RR, it is HRV time domain parameter；Interval_JJ (i) is BCG Time value between signal J-J；The average value of Mean_JJ phases between all J-J；T issues between effectively J-J in the range of detection time；HRV time domain parameter PNN50 calculation formula are as follows：N{JJ>Mean_JJ}The phase is more than 50ms number, N between phase and average JJ between expression JJtotalThe phase is total between representing JJ.
- 5. the back cushion according to claim 2 based on HRV non-contact detection emotional stress, it is characterised in that：Institute State and the specific of emotional stress index LF/HF models, fatigue exponent PNN50 models and resistance to compression index SDNN models is established in step 7 Process is as follows：Step 71, establish emotional stress index LF/HF models：Mainly determined, be defined as follows by endocrine index LF/HF：Work as LF/ HF scopes are in (0-0.4) ＆ (3.46-4), 0~30 point of stress ability score；When LF/HF scopes are in (0.4-1) ＆ (2.92- 3.46), 30~60 points of stress ability score；When LF/HF scopes are in (1-1.6) ＆ (2.56-2.92), stress ability score 60 ~80 points；When LF/HF scopes are in (1.6-2.2) ＆ (2.2-2.56), 80~100 points of stress ability score；Step 72, establish fatigue exponent PNN50 models：Determined, be defined as follows by time domain HRV parameters PNN50：Work as PNN50>= 49, fatigue exponent score 0~30；When PNN50 is in scope (1-2) ＆ (12-49), fatigue exponent score 30~60；Work as PNN50 In scope (3-4) ＆ (8-12), fatigue exponent score 60~80；When PNN50 is in scope (5-8), fatigue exponent score 80~ 100；Step 73, establish resistance to compression index SDNN models：Determined, be defined as follows by time domain HRV parameters SDNN：When SDNN is in scope (0-25) ＆ (960+), resistance to compression index score 0~30；When SDNN is in scope (25-50) ＆ (240-960), resistance to compression index score 30~60；When SDNN is in scope (50-100), resistance to compression index score 60~80；When SDNN is in scope (100-160), fatigue Index score 80~100.
- 6. the back cushion according to claim 1 based on HRV non-contact detection emotional stress, it is characterised in that：Also Including alarm, the alarm is connected with the master control borad on data operation box, is set when the data that data operation box calculates are higher than During definite value, alarm automatic alarm.
- 7. the back cushion according to claim 1 based on HRV non-contact detection emotional stress, it is characterised in that：Institute State and charging head is additionally provided with back cushion body, the charging head on charging head by covering, charging core and charging head lower cover form, and charges Core is arranged on charging head between lid and charging head lower cover, and charging core is connected by wire with the battery in data operation box.
- 8. the back cushion according to claim 1 based on HRV non-contact detection emotional stress, it is characterised in that：Institute State and be also equipped with fin on lid under computing box, the fin is bonded in the lower section of master control borad by heat-conducting glue.
- 9. the back cushion according to claim 1 based on HRV non-contact detection emotional stress, it is characterised in that：Institute It is WIFI communication modules or bluetooth communication to state wireless communication module.
- 10. the back cushion according to claim 1 based on HRV non-contact detection emotional stress, it is characterised in that： Cap surface offers equally distributed heat emission hole after described.
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