CN105877749B - A kind of automatic alarm help-seeking equipment and its detection method based on breath signal - Google Patents
A kind of automatic alarm help-seeking equipment and its detection method based on breath signal Download PDFInfo
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- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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- A61B5/74—Details of notification to user or communication with user or patient ; user input means
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Abstract
The invention belongs to life security, biomedical engineering and wearable device fields, and in particular to a kind of automatic alarm help-seeking equipment and its detection method based on breath signal.The present invention is set to a kind of specific respiratory state sequence in advance eupnea, the permutation and combination of rapid three kinds of respiratory states progress n >=1 respiratory states that breathe and hold one's breath by detection respiratory state, i.e. user.When an emergency situation is encountered just changes itself breath state according to this specific respiratory state being previously set by user, and then equipment is made to generate and send alarm help signal.Whether apparatus of the present invention there is the specific respiratory state set to which whether clear user is in emergency in the respiratory by detection user.Equipment of the invention have many advantages, such as hidden, rate of false alarm is low, safely and effectively flash appeal, reduce user's emergency under the controllability of negative emotions and condition of seeking help set.
Description
Technical field
The invention belongs to life security, biomedical engineering and wearable device fields, and in particular to one kind is based on exhaling
Inhale the automatic alarm help-seeking equipment and its detection method of signal.
Technical background
As public security environment situation locating for social progress people is become better and better, but some severe events are still even to be had
Occur, such as children are abducted, night race women is robbed and kills.If the injured party can in time, snugly report in these events
It is alert, then many malignant events can be stopped in time.
Although having there is some equipment that can play the role of emergency alarm on the market.For example, entitled " a kind of urgent
The utility model patent (204440608 U of Authorization Notice No. CN) of alarm ".It can be by thereon when user faces a danger
The key in face sends emergency message.For another example, the utility model of entitled " a kind of SOS button structure and its older mobile phone " is special
Sharp (202617219 U of Authorization Notice No. CN).It can be sent out by the emergency button above it when the elderly faces a danger
Send SOS signal.But these warning devices require user and go by some or certain special keys.This mode was both not hidden enough
It covers, these special actions is made when encountering ruffian and are possible to that ruffian can be enraged event is more deteriorated；This mode again not
It is enough safely and effectively, tied up under the equal situation for seriously limiting own activity when the injured party is in, be difficult effectively to trigger these equipment
Warning function may touch, to the case where wrong report occur and since user is under moving condition.
Therefore develop it is a kind of it is hidden, do not report by mistake and safely and effectively flash appeal and the device and method of alarm have it is important
Meaning.
Summary of the invention
The purpose of the present invention is to solve above-mentioned technical problem, provides a kind of automatic alarm based on breath signal and ask
Help equipment and its detection method.Fig. 1, Fig. 2 shows equipment of the invention and its detection method schematic diagrames.
A kind of automatic alarm help-seeking equipment based on breath signal, including power module, breath signal acquisition module, motor
Micro-vibration module, GPS module, wireless blue tooth module, gsm module and MCU central processing module；
The power module includes that lithium battery, voltage conversion circuit and management of charging and discharging protect circuit；It is mentioned for whole equipment
Power supply source defencive function and required various operating voltages；
Lithium battery provides the energy for whole equipment；Management of charging and discharging protection circuit is used to manage and protect charging and discharging lithium battery
Process prevents over-voltage, overcurrent and under-voltage phenomenon damage lithium battery working performance；What voltage conversion circuit was used to lithium battery to provide
Voltage is converted into operating voltage to supply other modules and use；
The breath signal acquisition module is used to acquire the breath signal of user and respiratory signal data is delivered in MCU
Entreat processing module；
The motor micro-vibration module gives the effect of user's touch feedback；When equipment detects that user makes the spy of setting
When determining respiratory state or when equipment is successfully alarmed, carried out by MCU central processing module control motor micro-vibration module a series of
Vibration reminds the user that equipment has been detected by or complete the requirement of user；
The GPS module provides the geographical location of user for equipment；When equipment detects that user makes specific respiratory state
When, MCU central processing module opens GPS module, the geographical location of GPS module real-time monitoring user, and is passed along the center MCU
Processing module；
The wireless blue tooth module for user by external smart phone or computer and MCU central processing module into
Row communication；
The gsm module is inserted with phonecard for dialing 110, kith and kin's number and sending what MCU central processing module provided
Real-time geographical locations information, and an information is fed back to MCU central processing module after the completion of making a phone call；
The MCU central processing module controls the modules outside except power module, passes through wireless blue tooth module and hand
Machine or compunlcation simultaneously make it carry out the setting of specific respiratory state and kith and kin's number, and to the respiratory signal data received
It handled, analyzed, and confirm whether breath signal is the specific respiratory state set；It is to be dialed and sought help by gsm module
Phone, and GPS module is opened simultaneously, the geographical location of user is monitored in real time, and is continuously sent out by gsm module；It has sought help
The feedback information of gsm module is received at rear MCU central processing module, then it is anti-to give user's tactile for control motor micro-vibration module
Feedback；Otherwise continue to monitor breath signal.
The specific respiratory state is that n >=1 respiratory state carries out permutation and combination；Respiratory state are as follows: eupnea, rapid
It breathes or holds one's breath, include number and time in each respiratory state, and by being previously set.
The voltage conversion circuit is+3.3V&+1.8V generative circuit.
The breath signal acquisition module includes breath signal sensor, high-frequency current signal generation circuit, electric piezo-resistive
Conversion circuit and analog/digital conversion circuit；High-frequency current signal generation circuit is injected by breath signal sensor to human body high
Frequency current signal, while the voltage of breath signal sensor measurement human body convert thereof into chest by electric piezo-resistive conversion circuit
Thoracic impedance value is converted into digital signal and is delivered to MCU central processing module by cavity impedance value, analog/digital conversion circuit.
The detection method of the above-mentioned automatic alarm help-seeking equipment based on breath signal, comprising the following steps:
Step 1, based on prior information or whether Fast Fourier Transform (FFT) FFT clearly requires and contain in the breath signal of detection
There is flip-flop；
The prior information refers to whether have come the clear required breath signal detected according to breath signal measurement method
Flip-flop；
The Fast Fourier Transform (FFT), which refers to, carries out time domain to the conversion of frequency domain and then the size of analysis 0Hz ingredient to signal
To which whether the clear required breath signal detected has flip-flop；
Step 2 is converted into containing only -1,1 two kinds by the breath signal that thresholding algorithm or characteristics algorithm detect needs
The square-wave signal of value；For the breath signal first choice thresholding algorithm without containing flip-flop as conversion method, for containing straight
The breath signal preferred features algorithm of ingredient is flowed as conversion method；
The thresholding algorithm refers to: by every in the breath signal of required detection according to Special Mapping f1(n) threshold is carried out
Value compares to obtain one group of square-wave signal for containing only -1,1 two kind value isometric with input data；If certain point value is greater than
X value, f1(n) it is set as 1；If certain point value is less than-X value, f1(n) it is set as -1；If certain point value is between-X and X, f1
(n) f is kept1(n-1) value；
Wherein, n is certain point in the breath signal of required detection；x(n)For the value of n point in the breath signal of required detection；f1
It (n-1) is the square-wave signal value of n-1 point；X value size depend on prior information, numerical value is adjustable；f1It (n) is the side of this step output
Wave signal；
The characteristics algorithm refers to: firstly, maximum and minimum in the breath signal detected needed for finding；Specifically such as
Under:
1. every in the breath signal of required detection is made the difference with its next point, one group of difference data diff is obtained1(n)；
diff1(n)=x(n+1)-x(n)(n=0,1 ...)
Wherein, n is certain point in the breath signal of required detection；N+1 is the next of n point in the breath signal of required detection
Point；x(n)For the value of n point in the breath signal of required detection；x(n+1)For the value of n+1 point in the breath signal of required detection；diff1
It (n) is the difference data of output；
2. finding diff1(n) meet diff in data1And diff (n) >=01Or diff (n-1)≤01And diff (n)≤01
(n-1) >=0 the point of condition；The maximum and minimum in breath signal that these points are looked for needed for being；
Then, all extreme points in signal are analyzed；Detailed process is as follows:
1. each pole and its next pole are made the difference, one group of difference data diff is obtained2(m)；
diff2(m)=x(m+1)-x(m)
Wherein, m is certain extreme point coordinate in breath signal；M+1 is next extreme point coordinate after m point；x(m)For required inspection
The corresponding value of extreme point m in the breath signal of survey；x(m+1)For the corresponding value of extreme point m+1 in the breath signal of required detection；
diff2It (m) is the difference data of output；
2. to diff2(m) data are analyzed, by every in the breath signal of required detection according to Special Mapping f2(n)
Conversion is carried out to obtain one group of square-wave signal for containing only -1,1 two kind value isometric with input data；If diff2(m) value
Greater than D and the time interval of extreme point m and extreme point m+1 are greater than T, then all f within extreme point m and extreme point m+12
(n) it is set as 1；If diff2(m) value is less than-D and the time interval of extreme point m and extreme point m+1 are greater than T, then extreme point m
With all f within extreme point m+12(n) it is set as -1；Remaining f2(n) a upper f is kept2(n-1) value；
Wherein, n is certain point in the breath signal of required detection, and m is certain extreme point coordinate in breath signal, and m+1 is after m point
Next extreme point coordinate, diff2It (m) is the corresponding difference data of extreme point m, tmAt the time of correspondence for extreme point m, tm+1For pole
At the time of value point m+1 is corresponded to；D value size depend on prior information, numerical value is adjustable；0.0 T≤1.5 second < depend on priori and believe
Breath；f2It (n) is the square-wave signal of this step output；
Step 3, searched out by trip point extraction algorithm step 2 generation square-wave signal in trip point and these points
Constitute jump point sequence；
The trip point extraction algorithm refers to:
1. every in square-wave signal that step 2 generates is made the difference with its next point, one group of difference signal diff is obtained3(n)
diff3(n)=y(n+1)-y(n)(n=0,1 ...)
Wherein, n is certain point in the square-wave signal of required detection, y(n)For the value of n point in the square-wave signal of required detection,
y(n+1)For the value of n+1 point in the square-wave signal of required detection, diff3It (n) is the difference data of output；
2. to diff3(n) data are analyzed；Work as diff3(n) be 0 when, then represent square-wave signal and jumped at n point
Become, i.e. n point and n+1 point are the trip point to be found to which jump point sequence be added；Work as diff3(n) when being 0, then the side of representative
There is no jumps at n point for wave signal, i.e. n point and n+1 point are not the trip point to be found to be added without trip point sequence
Column；
Step 4 calculates the time interval jumped in point sequence between adjacent two o'clock in step 3, then removes those intervals
For the interval in a sampling period, remaining time interval is sequentially constituted into time interval sequence；
Time interval sequence obtained in step 4 is carried out Special Mapping f by step 53(n) one group is obtained by 0,1,2 3 kinds
It is worth the sequence constituted；If certain in time interval sequence obtained in step 4, which puts corresponding time interval, is less than T0, then f3(n)
It is set as 1；If certain in time interval sequence obtained in step 4, which puts corresponding time interval, is greater than T1, then f3(n) 2 are set as；
Remaining f3(n) it is set as 0:
Wherein, n is some point in the time interval sequence generated in step 4, t(n)For time interval corresponding to n point,
0 < T0≤ 1.5 seconds, value size depended on prior information, 3 seconds < T1, value size is depending on prior information, f3It (n) is output
The sequence being made of 0,1,2 3 kinds of values；
The combination whether constituted containing 0,1 and 2 according to particular order in sequence obtained in step 6, judgment step 5, i.e.,
Meet the specific respiratory state of setting；When discovery meets, MCU central processing module control motor microseismic activity module gives user
First time touch feedback, it is believed that user, which is in emergency and carries out alarm, to seek help, and executes alarm and seeks help, while in MCU
It entreats processing module to open GPS module, passes through GPS module real-time monitoring customer position information；When not meeting, that is, think at user
In normal condition, monitoring is kept；
Step 7, alarm are sought help after execution, that is, after the feedback information for receiving gsm module, the control of MCU central processing module
Motor microseismic activity module gives user second of touch feedback, and MCU central processing module in real time obtains GPS module
Customer position information is persistently sent on user's kith and kin's mobile phone by gsm module.
The alarm, which is sought help, refers to that MCU central processing module dials 110 and kith and kin's number by gsm module.
The present invention is by the artificial respiratory variations actively generated of detection, i.e., user (including normally exhales eupnea in advance
The number of suction and time), rapid breathing (including the number hurriedly breathed and time) and hold one's breath (including the number held one's breath and when
Between) three kinds of respiratory states carry out the permutation and combination of n >=1 respiratory state, and are set to a kind of specific respiratory state.When user meets
Just change itself breath state according to this specific respiratory state being previously set to emergency, and then equipment is made to generate and send out
It delivers newspaper alert help signal.Whether apparatus of the present invention there is the specific breathing shape of this setting in the respiratory by detection user
Whether state is in emergency to clear user.It is controllable down to what is do not reported by mistake to realize rate of false alarm, help mode is hidden simultaneously
And safely and effectively.And when detect specific respiratory state and alarm seek help complete when, equipment give user's touch feedback to
Reduce negative emotions under user's emergency.
At 3-6 seconds, (inspiratory duration was not less than 1.5 not less than 1.5 seconds, expiratory duration to each breathing time of normal adult
Second), each eupnea of normal person can all generate a length of 3-6 seconds at one of the breath signal with fluctuation in other words.Separately
Outside, it can produce breathing letter with fluctuation of the duration less than 3 seconds (generally 1 second or so) when people's actively rapid breathing
Number, and can produce the breath signal almost without fluctuation of several seconds or even tens of seconds when people actively holds one's breath.
In conclusion equipment of the invention realize seek help hidden, rate of false alarm is low, safely and effectively flash appeal, reduce
The controllability of negative emotions and condition of seeking help setting under user's emergency.
Detailed description of the invention
Fig. 1 is detection method schematic diagram of the invention；
Fig. 2 is device structure schematic block diagram of the invention；
Fig. 3 is the specific respiratory state schematic diagram of embodiment setting；
Fig. 4 is the result figure using thresholding algorithm with specific respiratory state sequence；
Fig. 5 is the result figure using thresholding algorithm without specific respiratory state sequence；
Fig. 6 is the result figure using characteristics algorithm with specific respiratory state sequence；
Fig. 7 is the result figure using characteristics algorithm without specific respiratory state sequence.
Specific embodiment
The present invention is further elaborated for implementation with reference to the accompanying drawing and specifically.
Selection voltage conversion circuit is+3.3V&+1.8V generative circuit.Fig. 3 is the specific respiratory state of the present embodiment setting
Schematic diagram is previously set rapid breathing 3 times and is used as specific respiratory state then followed by holding one's breath 4 seconds or more.When discovery user goes out
Now 3 phenomenons then held one's breath 4 seconds or more of rapid breathing think that user is in emergency to help user's alarm to seek help.
For specific respiratory state shown in Fig. 3, the detection side of the above-mentioned automatic alarm help-seeking equipment based on breath signal
Method, comprising the following steps:
Step 1, based on prior information or whether Fast Fourier Transform (FFT) FFT clearly requires and contain in the breath signal of detection
There is flip-flop；
The prior information refers to whether have come the clear required breath signal detected according to breath signal measurement method
Flip-flop；
The Fast Fourier Transform (FFT), which refers to, carries out time domain to the conversion of frequency domain and then the size of analysis 0Hz ingredient to signal
To which whether the clear required breath signal detected has flip-flop；
Step 2 is converted into containing only -1,1 two kinds by the breath signal that thresholding algorithm or characteristics algorithm detect needs
The square-wave signal of value；For the breath signal first choice thresholding algorithm without containing flip-flop as conversion method, for containing straight
The breath signal preferred features algorithm of ingredient is flowed as conversion method；
The thresholding algorithm refers to: by every in the breath signal of required detection according to Special Mapping f1(n) it carries out
Threshold value comparison is to obtain one group of square-wave signal for containing only -1,1 two kind value isometric with input data；If certain point value is big
In X value, f1(n) it is set as 1；If certain point value is less than-X value, f1(n) it is set as -1；If certain point value is between-X and X,
f1(n) f is kept1(n-1) value；
Wherein, n is certain point in the breath signal of required detection；x(n)For the value of n point in the breath signal of required detection；f1
It (n-1) is the square-wave signal value of n-1 point；X value takes 0.00005；f1It (n) is the square-wave signal of this step output；
The characteristics algorithm refers to: firstly, maximum and minimum in the breath signal detected needed for finding；Specifically
Process is as follows:
1. every in the breath signal of required detection is made the difference with its next point, one group of difference data diff is obtained1(n)；
diff1(n)=x(n+1)-x(n)(n=0,1 ...)
Wherein, n is certain point in the breath signal of required detection；N+1 is the next of n point in the breath signal of required detection
Point；x(n)For the value of n point in the breath signal of required detection；x(n+1)For the value of n+1 point in the breath signal of required detection；diff1
It (n) is the difference data of output；
2. finding diff1(n) meet diff in data1And diff (n) >=01Or diff (n-1)≤01And diff (n)≤01
(n-1) >=0 the point of condition；The maximum and minimum in breath signal that these points are looked for needed for being；
Then, all extreme points in signal are analyzed；Detailed process is as follows:
1. each pole and its next pole are made the difference, one group of difference data diff is obtained2(m)；
diff2(m)=x(m+1)-x(m)
Wherein, m is certain extreme point coordinate in breath signal；M+1 is next extreme point coordinate after m point；x(m)For required inspection
The corresponding value of extreme point m in the breath signal of survey；x(m+1)For the corresponding value of extreme point m+1 in the breath signal of required detection；
diff2It (m) is the difference data of output；
2. to diff2(m) data are analyzed, by every in the breath signal of required detection according to Special Mapping f2(n)
Conversion is carried out to obtain one group of square-wave signal for containing only -1,1 two kind value isometric with input data；If diff2(m) value
Greater than D and the time interval of extreme point m and extreme point m+1 are greater than T, then all f within extreme point m and extreme point m+12
(n) it is set as 1；If diff2(m) value is less than-D and the time interval of extreme point m and extreme point m+1 are greater than T, then extreme point m
With all f within extreme point m+12(n) it is set as -1；Remaining f2(n) a upper f is kept2(n-1) value；
Wherein, n is certain point in the breath signal of required detection, and m is certain extreme point coordinate in breath signal, and m+1 is after m point
Next extreme point coordinate, diff2It (m) is the corresponding difference data of extreme point m, tmAt the time of correspondence for extreme point m, tm+1For pole
At the time of value point m+1 is corresponded to；D value takes 0.00005；T value takes 0.3；f2It (n) is the square-wave signal of this step output；
Step 3, searched out by trip point extraction algorithm step 2 generation square-wave signal in trip point and these points
Constitute jump point sequence；
The trip point extraction algorithm refers to:
1. every in square-wave signal that step 2 generates is made the difference with its next point, one group of difference signal diff is obtained3(n)
diff3(n)=y(n+1)-y(n)(n=0,1 ...)
Wherein, n is certain point in the square-wave signal of required detection, y(n)For the value of n point in the square-wave signal of required detection,
y(n+1)For the value of n+1 point in the square-wave signal of required detection, diff3It (n) is the difference data of output；
2. to diff3(n) data are analyzed；Work as diff3(n) be 0 when, then represent square-wave signal and jumped at n point
Become, i.e. n point and n+1 point are the trip point to be found to which jump point sequence be added；Work as diff3(n) when being 0, then the side of representative
There is no jumps at n point for wave signal, i.e. n point and n+1 point are not the trip point to be found to be added without trip point sequence
Column；
Step 4 calculates the time interval jumped in point sequence between adjacent two o'clock in step 3, then removes those intervals
For the interval in a sampling period, remaining time interval is sequentially constituted into time interval sequence；
Time interval sequence obtained in step 4 is carried out Special Mapping f by step 53(n) one group is obtained by 0,1,2 3 kinds
It is worth the sequence constituted；If certain in time interval sequence obtained in step 4, which puts corresponding time interval, is less than T0, then f3(n)
It is set as 1；If certain in time interval sequence obtained in step 4, which puts corresponding time interval, is greater than T1, then f3(n) 2 are set as；
Remaining f3(n) it is set as 0:
Wherein, n is some point in the time interval sequence generated in step 4, t(n)For time interval corresponding to n point,
T0Value takes 1.25, T1Value takes 4, f3It (n) is the sequence of output being made of 0,1,2 3 kinds of values；
The combination whether constituted containing 0,1 and 2 according to particular order in sequence obtained in step 6, judgment step 5, i.e.,
Meet the specific respiratory state of setting, needs to detect whether under specific respiratory state as shown in Figure 3 to there are " 1111112 " this
Combination；When discovery meets, MCU central processing module control motor microseismic activity module gives user's first time touch feedback, it is believed that
User, which is in emergency and carries out alarm, to seek help, and executes alarm and seeks help, while MCU central processing module opens GPS mould
Block passes through GPS module real-time monitoring customer position information；When not meeting, that is, thinks that user is in normal condition, keep prison
It surveys；
Step 7, alarm are sought help after execution, that is, after the feedback information for receiving gsm module, the control of MCU central processing module
Motor microseismic activity module gives user second of touch feedback, and MCU central processing module in real time obtains GPS module
Customer position information is persistently sent on user's kith and kin's mobile phone by gsm module.
The artificial respiratory variations actively generated of this method detection have very high accuracy, and specific effect is as follows:
As shown in result figure using thresholding algorithm of the Fig. 4 with specific respiratory state sequence, first waveform is in figure
The breath signal waveform of required detection；Second waveform is the square-wave waveform converted by thresholding algorithm, and wherein stain is to pass through
The trip point that trip point extraction algorithm is found；Third waveform is subsequent step processing as a result, wherein dotted line is to detect not
Part containing specific respiratory state sequence, solid line are the part containing specific respiratory state sequence detected.This method is quasi-
Really find the specific respiratory state being previously set in this detection with certain, i.e., it is rapid to breathe 3 times, hold one's breath 4 seconds.
As shown in result figure using thresholding algorithm of the Fig. 5 without specific respiratory state sequence, first waveform in figure
For the breath signal waveform of required detection；Second waveform is the square-wave waveform converted by thresholding algorithm, and wherein stain is warp
Cross the trip point that trip point extraction algorithm is found；Third waveform is subsequent step processing as a result, dotted line is to detect to be free of
There is the part of specific respiratory state sequence.This method accurately finds specific to exhale in this detection without what certain was previously set
Suction state.
As shown in result figure using characteristics algorithm of the Fig. 6 with specific respiratory state sequence, first waveform is in figure
The breath signal waveform of required detection, wherein stain is to look for each extreme point by characteristics algorithm；Second waveform is warp
The square-wave waveform of characteristics algorithm conversion is crossed, wherein stain is the trip point found by trip point extraction algorithm；Third waveform
It is subsequent step processing as a result, wherein dotted line is to detect the part without containing specific respiratory state sequence, solid line is detection
The part containing specific respiratory state sequence arrived.This method accurately finds the spy being previously set in this detection with certain
Determine respiratory state, i.e., it is rapid to breathe 3 times, hold one's breath 4 seconds.
As shown in result figure using thresholding algorithm of the Fig. 7 without specific respiratory state sequence, first waveform in figure
For the breath signal waveform of required detection, wherein stain is to look for each extreme point by characteristics algorithm；Second waveform be
By the square-wave waveform that characteristics algorithm is converted, wherein stain is the trip point found by trip point extraction algorithm；Third wave
Shape is subsequent step processing as a result, dotted line is to detect the part without containing specific respiratory state sequence.This method is accurately
It was found that the specific respiratory state being previously set in this detection without certain.
Claims (6)
1. a kind of automatic alarm help-seeking equipment based on breath signal, it is characterised in that: acquired including power module, breath signal
Module, motor micro-vibration module, GPS module, wireless blue tooth module, gsm module and MCU central processing module；
The power module includes that lithium battery, voltage conversion circuit and management of charging and discharging protect circuit；Electricity is provided for whole equipment
Source protection function and required various operating voltages；
Lithium battery provides the energy for whole equipment；Management of charging and discharging protection circuit is used to manage and protect charging and discharging lithium battery mistake
Journey prevents over-voltage, overcurrent and under-voltage phenomenon damage lithium battery working performance；Voltage conversion circuit is used to the electricity that lithium battery is provided
Pressure is converted into operating voltage to supply other modules and use；
The breath signal acquisition module is used to acquire the breath signal of user and respiratory signal data is delivered to MCU centre
Manage module；
The motor micro-vibration module gives the effect of user's touch feedback；When equipment detects that user makes the specific of setting and exhales
When suction state or when equipment is successfully alarmed, a series of vibration is carried out by MCU central processing module control motor micro-vibration module
Remind the user that equipment has been detected by or complete the requirement of user；The specific respiratory state is when user encounters urgent feelings
The respiratory state being previously set realized when condition by actively changing itself breath state；
The GPS module provides the geographical location of user for equipment；When equipment detects that user makes specific respiratory state,
MCU central processing module opens GPS module, the geographical location of GPS module real-time monitoring user, and is passed along MCU centre
Manage module；
The wireless blue tooth module is led to by external smart phone or computer with MCU central processing module for user
Letter；
The gsm module is inserted with phonecard for dialing 110, kith and kin's number and sending the real-time of MCU central processing module offer
Geographical location information, and an information is fed back to MCU central processing module after the completion of making a phone call；
MCU central processing module control except power module outside modules, by wireless blue tooth module and mobile phone or
Compunlcation carries out the setting of specific respiratory state and kith and kin's number, and the respiratory signal data received is handled,
Analysis, and confirm whether breath signal is the specific respiratory state set；It is call for help to be dialed by gsm module, and same
When open GPS module, monitor the geographical location of user in real time, and continuously sent out by gsm module；After the completion of seeking help in MCU
It entreats processing module to receive the feedback information of gsm module, then controls motor micro-vibration module and give user's touch feedback；Otherwise after
Continuous monitoring breath signal.
2. the automatic alarm help-seeking equipment based on breath signal as described in claim 1, it is characterised in that: the specific breathing shape
State is that 1 respiratory state of n > carries out permutation and combination；Respiratory state are as follows: eupnea hurriedly breathes or holds one's breath, each breathing shape
It include number and time in state, and specific respiratory state is by being previously set.
3. the automatic alarm help-seeking equipment based on breath signal as described in claim 1, it is characterised in that: the voltage conversion electricity
Road is+3.3V and+1.8V generative circuit.
4. the automatic alarm help-seeking equipment based on breath signal as described in claim 1, it is characterised in that: the breath signal is adopted
Collection module includes breath signal sensor, high-frequency current signal generation circuit, electric piezo-resistive conversion circuit and analog/digital conversion
Circuit；High-frequency current signal generation circuit injects high-frequency current signal to human body by breath signal sensor, while breathing letter
The voltage of number sensor measurement human body converts thereof into thoracic impedance value, analog/digital conversion electricity by electric piezo-resistive conversion circuit
Thoracic impedance value is converted into digital signal and is delivered to MCU central processing module by road.
5. the detection method of the automatic alarm help-seeking equipment based on breath signal as described in claim 1, comprising the following steps:
Step 1, based on prior information or whether Fast Fourier Transform (FFT) FFT clearly requires in the breath signal of detection containing straight
Flow ingredient；
The prior information refers to whether have direct current come the clear required breath signal detected according to breath signal measurement method
Ingredient；
The Fast Fourier Transform (FFT) refer to signal carry out time domain to frequency domain conversion then analysis 0Hz ingredient size thus
Whether the breath signal detected needed for clear has flip-flop；
Step 2 is converted into containing only -1,1 two kinds of values by the breath signal that thresholding algorithm or characteristics algorithm detect needs
Square-wave signal；Select thresholding algorithm as conversion method the breath signal without containing flip-flop, for contain direct current at
The breath signal divided selects characteristics algorithm as conversion method；
The thresholding algorithm refers to: by every in the breath signal of required detection according to Special Mapping f1(n) threshold value ratio is carried out
Compared with to obtain one group of square-wave signal for containing only -1,1 two kind value isometric with input data；If certain point value is greater than X value,
f1(n) it is set as 1；If certain point value is less than-X value, f1(n) it is set as -1；If certain point value is between-X and X, f1(n)
Keep f1(n-1) value；
Wherein, n is certain point in the breath signal of required detection；x(n)For the value of n point in the breath signal of required detection；f1(n-1)
For the square-wave signal value of n-1 point；X value size depend on prior information, numerical value is adjustable；f1It (n) is the square wave letter of this step output
Number；
The characteristics algorithm refers to: firstly, maximum and minimum in the breath signal detected needed for finding；Detailed process
It is as follows:
1. every in the breath signal of required detection is made the difference with its next point, one group of difference data diff is obtained1(n)；
diff1(n)=x(n+1)-x(n)(n=0,1 ...)
Wherein, n is certain point in the breath signal of required detection；N+1 is the next point of n point in the breath signal of required detection；x(n)
For the value of n point in the breath signal of required detection；x(n+1)For the value of n+1 point in the breath signal of required detection；diff1(n) it is
The difference data of output；
2. finding diff1(n) meet diff in data1And diff (n) >=01Or diff (n-1)≤01And diff (n)≤01(n-1)
The point of >=0 condition；The minimum or maximum in breath signal that these points are looked for needed for being；
Then, all extreme points in signal are analyzed；Detailed process is as follows:
1. each pole and its next pole are made the difference, one group of difference data diff is obtained2(m)；
diff2(m)=x(m+1)-x(m)
Wherein, m is certain extreme point coordinate in breath signal；M+1 is next extreme point coordinate after m point；x(m)For required detection
The corresponding value of extreme point m in breath signal；x(m+1)For the corresponding value of extreme point m+1 in the breath signal of required detection；diff2
It (m) is the difference data of output；
2. to diff2(m) data are analyzed, by every in the breath signal of required detection according to Special Mapping f2(n) it carries out
Conversion is to obtain one group of square-wave signal for containing only -1,1 two kind value isometric with input data；If diff2(m) value is greater than
D and the time interval of extreme point m and extreme point m+1 are greater than T, then all f within extreme point m and extreme point m+12(n) it sets
It is 1；If diff2(m) value is less than-D and the time interval of extreme point m and extreme point m+1 are greater than T, then extreme point m and extreme value
All f within point m+12(n) it is set as -1；Remaining f2(n) a upper f is kept2(n-1) value；
Wherein, n is certain point in the breath signal of required detection, and m is certain extreme point coordinate in breath signal, and m+1 is next after m point
A extreme point coordinate, diff2It (m) is the corresponding difference data of extreme point m, tmAt the time of correspondence for extreme point m, tm+1For extreme point
At the time of m+1 is corresponded to；D value size depend on prior information, numerical value is adjustable；0.0 T≤1.5 second < depend on prior information；f2
It (n) is the square-wave signal of this step output；
Step 3 is searched out the trip point in the square-wave signal of step 2 generation by trip point extraction algorithm and these points is constituted
Jump point sequence；
The trip point extraction algorithm refers to:
1. every in square-wave signal that step 2 generates is made the difference with its next point, one group of difference signal diff is obtained3(n)
diff3(n)=y(n+1)-y(n)(n=0,1 ...)
Wherein, n is certain point in the square-wave signal of required detection, y(n)For the value of n point in the square-wave signal of required detection, y(n+1)For
The value of n+1 point, diff in the square-wave signal of required detection3It (n) is the difference data of output；
2. to diff3(n) data are analyzed；Work as diff3(n) be 0 when, then represent square-wave signal and jumped at n point,
That is n point and n+1 point are the trip point to be found to which jump point sequence be added；Work as diff3(n) be 0 when, then represent square wave letter
There is no jumps number at n point, i.e. n point and n+1 point are not the trip point to be found to be added without jump point sequence；
Step 4 calculates the time interval jumped in point sequence between adjacent two o'clock in step 3, then removes those and is divided into one
Remaining time interval is sequentially constituted time interval sequence by the interval in a sampling period；
Time interval sequence obtained in step 4 is carried out Special Mapping f by step 53(n) one group is obtained by 0,1,2 3 kinds of value structures
At sequence；If certain in time interval sequence obtained in step 4, which puts corresponding time interval, is less than T0, then f3(n) it is set as
1；If certain in time interval sequence obtained in step 4, which puts corresponding time interval, is greater than T1, then f3(n) 2 are set as；Remaining
f3(n) it is set as 0:
Wherein, n is some point in the time interval sequence generated in step 4, t(n)For time interval corresponding to n point, 0 < T0
≤ 1.5 seconds, value size depended on prior information, 3 seconds < T1, value size is depending on prior information, f3(n) for output by
The sequence that 0,1,2 3 kinds of values are constituted；
The combination whether constituted containing 0,1 and 2 according to particular order in sequence obtained in step 6, judgment step 5, that is, meet
The specific respiratory state of setting；When discovery meets, MCU central processing module control motor microseismic activity module gives user first
Secondary touch feedback, it is believed that user, which is in emergency and carries out alarm, to seek help, and executes alarm and seeks help, while MCU centre
It manages module and opens GPS module, pass through GPS module real-time monitoring customer position information；When not meeting, that is, think that user is in just
Normal state keeps monitoring；
Step 7, alarm are sought help after execution, that is, after the feedback information for receiving gsm module, MCU central processing module controls motor
Microseismic activity module gives user second of touch feedback, and the user that MCU central processing module in real time obtains GPS module
Location information is persistently sent on user's kith and kin's mobile phone by gsm module.
6. the detection method of the automatic alarm help-seeking equipment based on breath signal as claimed in claim 5, it is characterised in that: described
Alarm, which is sought help, refers to that MCU central processing module dials 110 and kith and kin's number by gsm module.
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| CN101620649A (en) * | 2009-08-07 | 2010-01-06 | 四川长虹电器股份有限公司 | Real-time monitoring method for human health based on network communication |
| CN202904817U (en) * | 2012-10-18 | 2013-04-24 | 华北电力大学（保定） | Soundless sleep apnea prompting system |
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