CN106228751A - Intelligent alarm system and the method for falling based on Android platform MEMS/ Magnetic Sensor/GPS - Google Patents

Abstract

The invention discloses a kind of intelligent alarm system and method for falling based on Android platform MEMS/ Magnetic Sensor/GPS, this system includes: 3-axis acceleration sensor, for gathering the 3-axis acceleration data of mobile phone；Magnetic Sensor, for gathering the geomagnetic field intensity data of mobile phone position；Gyroscope, for gathering the tri-axis angular rate data of mobile phone；GPS is for obtaining the positional information of carrier；Data analysis module, for trying to achieve the attitude of mobile phone and real-time attitude spin matrix according to the data of 3-axis acceleration sensor, gyroscope and Magnetic Sensor；First falls judge module, for tentatively judging whether to fall；Whether second falls judge module, for final for falling；Alarm module, for sending carrier position and condition to medical institutions and relatives.The present invention is on the basis of traditional attitude algorithm algorithm, for this Special use occasion of fall detection, it is proposed that new self adaptation adjusts ginseng attitude algorithm algorithm, it is achieved that the accurate detection fallen.

Description

Based on Android platform MEMS/ Magnetic Sensor/GPS fall intelligent alarm system with Method

Technical field

The present invention relates to sensor detecting field, particularly relate to a kind of based on Android platform MEMS/ Magnetic Sensor/ Fall intelligent alarm system and the method for GPS.

Background technology

From the point of view of achievement in research the most both domestic and external, of a great variety about the method carrying out during Falls in Old People reporting to the police, have The matured product of a little companies the most commercially occurs in that.In research and development and use, the shape of the information of falling is obtained according to every product Formula is different with source, and most crucial method can be divided into following three classes:

1. the warning device of falling that old people independently enables: old people carries with independent of report of falling outside mobile phone Alert equipment.After falling, old man independently presses the button realization and reports to the police, and realizes turning alarm signal by professional on backstage Send out and management, inform kith and kin or the doctor etc. of warning old people the most at once.Existing warning system such as Philip individual is anxious Rescue warning system.

2. warning system of falling based on image information detection: when routine use, old people can be arranged on and easily send out The raw place fallen, when the health under old people occurs abnormal condition in image information moves or position and attitude changes, Detect the generation of behavior of falling, it is achieved automatic alarm.The such as British scholar research detection to improper motor behavior.

3. air bag class passive security protection device: inspired, early by safe automobile air bag function when meeting with a street accident The scholars such as the aboveground prosperous man of rice field university utilize acceleration transducer, through statistics and test repeatedly, it is determined that old people Acceleration when falling reduces to fall and brings to old people more than the most automatically starting air bag when of a certain specific threshold Various injuries.

All there is certain weak point in any of the above mode, wherein mode 1 must carry an independent warning device And require that old man's button that independently pushes for emergency can not realize automatic alarm；Mode 2 needs relevant video detecting device cost relatively Height, and use limited by time and space；Mode 3 only utilizes accelerometer one sensor, and acquired data are the most limited, False alarm rate is high.

Therefore, for the present situation of society Falls in Old People problem, combined with intelligent mobile phone, inertial technology attitude detection should Development, the application proposes inertial technology is applied to fall detection, develops and a kind of (adds based on the built-in MEMS of smart mobile phone Velometer, gyroscope), magnetometer and the fall detection warning system of GPS sensor.

Summary of the invention

The technical problem to be solved in the present invention is for defect of the prior art, it is provided that a kind of based on Android platform Fall intelligent alarm system and the method for MEMS/ Magnetic Sensor/GPS.

The technical solution adopted for the present invention to solve the technical problems is: a kind of based on Android platform MEMS/ Magnetic Sensor/ The intelligent alarm system of falling of GPS, including:

3-axis acceleration sensor, for gathering the 3-axis acceleration data of mobile phone；

Magnetic Sensor, for gathering the geomagnetic field intensity data of mobile phone position；

Gyroscope, for gathering the tri-axis angular rate data of mobile phone；

GPS, gathers carrier position data；

Data analysis module, for trying to achieve carrier according to the data of 3-axis acceleration sensor, gyroscope and Magnetic Sensor Attitude and real-time attitude spin matrix

Then according to attitude spin matrix(i.e. accelerometer records to try to achieve (b system) acceleration under carrier system Acceleration) projection of (n system) under referential

First falls judge module, is used for calculatingThe absolute value poor with gravitational constant g, ifAnd when continuing Between more than or equal to t₁, the most tentatively it is judged as falling, wherein C is decision threshold of falling；

Second falls judge module, is used for judging t₂After time, at time t₃If interior Δ γ > 10 ° or Δ θ > 10 °, i.e. judging For falling, wherein Δ γ is carrier angle of pitch changing value, and Δ θ is carrier roll angle changing value, is otherwise considered as interference；

Alarm module, if being judged as falling for the second judge module of falling, sends carrier to medical institutions and relatives Position and condition.

A kind of intelligent alarm method of falling based on Android platform MEMS/ Magnetic Sensor/GPS, comprises the following steps:

1) data acquisition: by the 3-axis acceleration data of sensor acquisition human body, the earth magnetism field intensity of human body position Degrees of data, tri-axis angular rate data；

2) data analysis: try to achieve the attitude of carrier according to the data of 3-axis acceleration sensor, gyroscope and Magnetic Sensor With real-time attitude spin matrix

Specific as follows:

2.1) calculate according to 3-axis acceleration sensor For acceleration modulus value, if meetingProceed to step 2.2), ifOrProceed to step 2.5)；

2.2) data of 3-axis acceleration sensor and Magnetic Sensor are normalized；

2.3) utilize the data of 3-axis acceleration sensor and Magnetic Sensor, gyro data be corrected:

errorp_ω|_k=k_p1accerror|_k+k_p2magerror|_k

errorInt_ω|_k=errorInt_ω|_k-1+(k_i1accerror|_k+k_i2magerror|_k)t

${\widehat{\mathrm{\ω}}}^b{|}_k={\mathrm{\ω}}^b{|}_k+{\mathrm{errorp}}_{\mathrm{\ω}}{|}_k+{\mathrm{errorInt}}_{\mathrm{\ω}}{|}_k$

errorp_ω|_kAnd errorInt_ω|_kBeing respectively error rate item and integral term, t is sensor sample interval, ω^bFor The output data of gyroscope；Data after correcting for gyroscope；

2.4) bring the gyro data after correction into quaternion differential equation, update quaternary number, carrier pitching Angle, roll angle and course angle；

2.5) attitude is resolved by gyroscope integration；

3) according to attitude spin matrix(what i.e. accelerometer recorded adds to try to achieve (b system) acceleration under carrier system Speed) acceleration of (n system) under referential

4) calculateThe absolute value poor with gravitational constant g, ifAnd the persistent period is more than or equal to t₁, the most tentatively Being judged as falling, wherein C is decision threshold of falling；

5) t that fallen tentatively it is judged as₂After time, at time t₃If interior Δ γ > 10 ° or Δ θ > 10 °, being i.e. judged as falling, Otherwise it is considered as interference.

By such scheme, described step 2.3) the middle method using fuzzy control, ask for according to carrier different motion state Parameter accerror be automatically adjusted k_p1And k_i1。

By such scheme, described step 2.3) in, automatic according to parameter accerror that carrier different motion state is asked for Regulation k_p1And k_i1, concrete formula is as follows:

Wherein c₁、c₂、c₃、c₄、c₅、c₆For coefficient constant.

The beneficial effect comprise that:

1. the present invention is on the basis of traditional attitude algorithm algorithm, for this Special use occasion of fall detection, carries Go out fuzzy self-adaption and adjusted ginseng attitude algorithm algorithm, it is achieved that the accurate detection fallen；

2. because carrier movement epidemic situation comparison is complicated, if accelerometer to be arranged fixing proportional gain and integration increasing Benefit, Attitude estimation effect is the most bad；The present invention proposes the error of the gyroscope X/Y axle tried to achieve with accelerometer for according to adjusting The proportional gain of complementary filter and storage gain, thus reach self_adaptive adjusting device parameter acquiring more exact posture Purpose；

3. the sensor that the present invention uses can depend on smart mobile phone, decreases hardware and puts into, and improves present invention application Popularization, it is achieved Falls Among Old People report to the police, quickly call for help, it is ensured that succoured in time.

Accompanying drawing explanation

Below in conjunction with drawings and Examples, the invention will be further described, in accompanying drawing:

Fig. 1 is the method flow diagram of the embodiment of the present invention；

Fig. 2 is the algorithm flow chart of the embodiment of the present invention；

Fig. 3 is the fuzzy self-adaption complementary filter structured flowchart of the improvement of the embodiment of the present invention；

Fig. 4 is the membership function figure of the embodiment of the present invention | accerrorx |；

Fig. 5 is the embodiment of the present inventionMembership function figure；

Fig. 6 is the embodiment of the present inventionMembership function figure.

Detailed description of the invention

In order to make the purpose of the present invention, technical scheme and advantage clearer, below in conjunction with embodiment, to the present invention It is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not used to limit Determine the present invention.

As it is shown in figure 1, one intelligent alarm method of falling based on Android platform MEMS/ Magnetic Sensor/GPS, including with Lower step:

1) data acquisition: by the 3-axis acceleration data of sensor acquisition mobile phone, geomagnetic field intensity data, three shaft angle speed Rate data and position data；

2) data analysis: try to achieve the attitude of carrier according to the data of 3-axis acceleration sensor, gyroscope and Magnetic Sensor With real-time attitude spin matrix

The present invention uses fuzzy self-adaption to adjust ginseng attitude algorithm algorithm specific as follows to the attitude trying to achieve carrier: such as Fig. 2 institute Show,

2.1) calculate according to 3-axis acceleration sensor For acceleration modulus value, if meetingProceed to step 2.2), ifOrProceed to step 2.5)；

2.2) data of 3-axis acceleration sensor and Magnetic Sensor are normalized；

2.3) utilize the data of 3-axis acceleration sensor and Magnetic Sensor, gyro data be corrected:

errorp_ω|_k=k_p1accerror|_k+k_p2magerror|_k

errorInt_ω|_k=errorInt_ω|_k-1+(k_i1accerror|_k+k_i2magerror|_k)t

${\widehat{\mathrm{\ω}}}^b{|}_k={\mathrm{\ω}}^b{|}_k+{\mathrm{errorp}}_{\mathrm{\ω}}{|}_k+{\mathrm{errorInt}}_{\mathrm{\ω}}{|}_k$

errorp_ω|_kAnd errorInt_ω|_kBeing respectively error rate item and integral term, t is sensor sample interval, ω^bFor The output data of gyroscope；Data after correcting for gyroscope；

Owing to the magnetic environment of general carrier is more stable, therefore k_p2And k_i2It is set to fixed value and course is resolved impact not quite.

And accelerometer is relatively big by extraneous factor interference, can be to the complementary filter raw considerable influence of output ginseng, simple depends on By acceleration measuring value modulus value, i.e.It is bigger that size is optimized still error to attitude algorithm.k_pDetermine complementary filter The cut-off frequency of device, when cut-off frequency is less, complementary filter output attitude depends primarily on the resolving value of gyroscope；When cutting When only frequency is bigger, complementary filter output attitude depends primarily on the resolving value of accelerometer and Magnetic Sensor.Because carrier Kinestate is more complicated, if arranging fixing proportional gain k_p1With storage gain k_i1, Attitude estimation effect is the most bad.

On this basis, in order to obtain attitude information more accurately, major part scholar is basis at presentWith gravity The difference of acceleration modulus value, i.e. withSize be that condition directly carries out relevant tune to the output of PI controller Whole, or the proportional gain k according to Aerror regulation complementary filter_p1With storage gain k_i1.Owing to this processing method does not has Input quantity accerror in view of PI controller, it is impossible to quantitative adjustment k_p1And k_i1Control output, therefore attitude of carrier is estimated Count the most accurate.

This patent is for this problem, it is proposed that fuzzy self-adaption complementary filter, i.e. according to the accerror (3 asked for × 1 matrix) in accerrorx, accerroy (element in accerror) absolute value (| accerrorx | and | Accerrory |) the real-time proportional gain k adjusting complementary filter_p1With storage gain k_i1.The fuzzy self-adaption complementation filter improved Ripple device structured flowchart is as shown in Figure 3:

In order to reach preferably to control effect, native system separately designs two groups of fuzzy controllers for X/Y axle, note| accerrorx |, | accerrory | are as the input quantity of fuzzy controller, output For

Gather sensing data, use Matlab instrument that attitude complementary filter carries out a large amount of measured data off-line Process, | accerrorx |, the actual range of | accerrory | are [0,0.06], be quantified as 7 grades, then have | accerrrox |=0,1,2,3,4,5,6}, | accerrory |={ 0,1,2,3,4,5,6}；Scope be [0, 20],Scope is [0,8], output is in like manner quantified as 7 grades, then has

Input quantity is divided into five fuzzy subsets: { N, Z, SP, P, LP}, wherein N=is little；Z=is normal；SP=is bigger；P =big；LP=is the biggest；Output is divided into five fuzzy subsets: { N, Z, SP, P, LP}, wherein N=is little；Z=is normal；SP= Bigger；P=is big；LP=is the biggest；In engineer applied, it is not unique to reach control effect membership function, is subordinate to Degree function is broadly divided into three classes: the Z-type function from left to right successively decreased according to coordinate axes；The S type being from left to right incremented by according to coordinate axes Function；According to coordinate axes symmetrical Π type function.Need in systems in practice to consider that microprocessor realizes obfuscation, ambiguity solution Time, and save the memory headroom shared by rule query table as far as possible, control effect can be met again, owing to calculating simultaneously Simply, conventional membership function is triangle, and native system also uses Triangleshape grade of membership function.Because the Fuzzy Control of X/Y axle Device processed design is similar, as a example by X-axis, | accerrorx |,WithMembership function as shown in Figs. 4-6:

As a example by X-axis, when carrier is along X-axis accelerated motion, accelerometer output valve comprises carrier movement acceleration, can make | accerrorx | increases, and the angle error now resolved by accelerometer is relatively big, and complementary filter output should depend primarily on gyro The attitude angle that instrument resolves, thenWithShould reduce；When carrier is in static or uniform speed motion state, | accerrorx | compares Little, accelerometer the attitude error resolved is less, and complementary filter output should depend primarily on the appearance that accelerometer resolves State angle, nowWithShould increase.In like manner, should reduce when | accerrory | is biggerWithWhen | accerrory | is less Time should increaseWithFuzzy reasoning table can be obtained, as shown in Table 1 and Table 2 according to above analysis:

Table 1WithFuzzy rule

Table 2WithFuzzy rule

Following fuzzy rule can be formulated by table 1:

(1)If(||accerrorx||is N)then(kp1x is LP)(ki1x is LP)

(2)If(||accerrorx||is Z)then(kp1x is P)(ki1x is P)

(3)If(||accerrorx||is SP)then(kp1x is SP)(ki1x is SP)

(4)If(||accerrorx||is P)then(kp1x is Z)(ki1x is Z)

(5)If(||accerrorx||is LP)then(kp1x is N)(ki1x is N)

In like manner, table 2 following fuzzy rule can be formulated:

(1)If(||accerrory||is N)then(kp1y is LP)(ki1y is LP)

(2)If(||accerrory||is Z)then(kp1y is P)(ki1y is P)

(3)If(||accerrory||is SP)then(kp1y is SP)(ki1y is SP)

(4)If(||accerrory||is P)then(kp1y is Z)(ki1y is Z)

(5)If(||accerrory||is LP)then(kp1y is N)(ki1y is N)。

In step 2.3) for proportional gain k_p1With storage gain k_i1, this patent additionally provides a kind of computational methods, specifically As follows:

Wherein c₁、c₂、c₃、c₄、c₅、c₆For coefficient empirical value constant, can obtain according to experiment.

2.4) bring the gyro data after correction into quaternion differential equation, update quaternary number, carrier pitching Angle, roll angle and course angle；Proceed to step 2.6)；

2.5) attitude is resolved by gyroscope integration, i.e.WhereinIt is to gyro after correction Instrument dataMatrixing,

2.6) real-time attitude spin matrix is obtained

3) according to attitude spin matrix(what i.e. accelerometer recorded adds to try to achieve (b system) acceleration under carrier system Speed) acceleration of (n system) under referential

4) calculateThe absolute value poor with gravitational constant g, ifAnd the persistent period is more than or equal to t₁, the most tentatively Being judged as falling, wherein C is decision threshold of falling；

5) t that fallen tentatively it is judged as₂After time, Δ γ > 10 ° or Δ θ > 10 °, being i.e. judged as falling, wherein Δ γ is Carrier angle of pitch changing value, Δ θ is carrier roll angle changing value；Otherwise it is considered as interference, abandons data.

When mobile phone is tossed conveniently, because acceleration of motion is relatively big, thereforeCondition is set up, and sentences and can be triggered at the beginning of system, But mobile phone is tossed after stablizing conveniently, and attitude angle will not change, and method is judged as finally not triggering warning of falling.

When under the feelings row that carrying mobile phone is run or quickly walked about, because carrier movement acceleration is less, thereforeBar Part is false, and this method is judged as not triggering warning of falling.

The false alarm produced for can independently stand after minimizing is fallen further, devising warning and cancelling mechanism: reporting to the police tactile If without cancelling operation in 30s after sending out, then system sends alarming short message.Alarming short message sends carrier position to medical institutions and relatives Putting and condition information, wherein contact method and condition information can pre-set.

Sum up: native system can accurately judge whether old man falls, and takes measure of reporting to the police accordingly so that Lao Ren simultaneously Obtain Emergency Assistance in the very first time, at utmost reduce because of the harm that old man's life is caused of falling；Native system appearance simultaneously State computation and application software, for the erroneous judgement that may cause of kinestate such as running or quickly walk about, take accordingly Process means, thus reduce False Rate.

On the basis of the method, we are formed systems soft ware, can be cured as mobile phone A PP software or be individually System, as follows:

A kind of intelligent alarm system of falling based on Android platform MEMS/ Magnetic Sensor/GPS, including:

3-axis acceleration sensor, for gathering the 3-axis acceleration data of mobile phone；

Magnetic Sensor, for locality magnetic field strength date；

Gyroscope, for gathering the tri-axis angular rate data of mobile phone；

Data analysis module, for trying to achieve carrier according to the data of 3-axis acceleration sensor, gyroscope and Magnetic Sensor Attitude and real-time attitude spin matrix

Then according to attitude spin matrix(i.e. accelerometer records to try to achieve (b system) acceleration under carrier system Acceleration) acceleration of (n system) under referential

First falls judge module, is used for calculatingThe absolute value poor with gravitational constant g, ifAnd when continuing Between more than or equal to t₁, the most tentatively it is judged as falling, wherein C is decision threshold of falling；

Second falls judge module, is used for judging t₂After time, at time t₃If interior Δ γ > 10 ° or Δ θ > 10 °, i.e. judging For falling, wherein Δ γ is carrier angle of pitch changing value, and Δ θ is carrier roll angle changing value；Otherwise it is considered as interference；

Alarm module, if being judged as falling for the second judge module of falling, sends carrier to medical institutions and relatives Position and condition.

When mobile phone is tossed conveniently, because acceleration of motion is relatively big, thereforeCondition is set up, and sentences and can be triggered at the beginning of system, But mobile phone is tossed after stablizing conveniently, and attitude angle will not change, and systems soft ware does not finally trigger warning of falling.

When under the feelings row that carrying mobile phone is run or quickly walked about, because carrier movement acceleration is less, thereforeBar Part is false, and native system software does not triggers warning of falling.

It should be appreciated that for those of ordinary skills, can be improved according to the above description or be converted, And all these modifications and variations all should belong to the protection domain of claims of the present invention.

Claims (5)

1. an intelligent alarm system of falling based on Android platform MEMS/ Magnetic Sensor/GPS, it is characterised in that including:

3-axis acceleration sensor, for gathering the 3-axis acceleration data of mobile phone；

Magnetic Sensor, for gathering the geomagnetic field intensity data of mobile phone position；

Gyroscope, for gathering the tri-axis angular rate data of mobile phone；

GPS, gathers carrier position data；

Data analysis module, for trying to achieve the appearance of carrier according to the data of 3-axis acceleration sensor, gyroscope and Magnetic Sensor State and real-time attitude spin matrix

Then 3-axis acceleration projection under referential under carrier system is tried to achieve according to attitude spin matrix Described Carrier system is mobile phone transverse axis, the longitudinal axis and the orthogonal coordinate system axially constituted of vertical mobile phone plane, and described referential is sat for navigation Mark system, takes geographic coordinate system here as navigational coordinate system；

First falls judge module, is used for calculatingThe absolute value poor with gravitational constant g, ifAnd the persistent period is big In equal to t₁, the most tentatively it is judged as falling, wherein C is decision threshold of falling；

Second falls judge module, is used for judging t₂After time, at time t₃If interior Δ γ > 10 ° or Δ θ > 10 °, being i.e. judged as falling Falling, wherein Δ γ is carrier angle of pitch changing value, and Δ θ is carrier roll angle changing value, is otherwise considered as interference；

Alarm module, if being judged as falling for the second judge module of falling, sends carrier position to medical institutions and relatives Information and condition.

2. an intelligent alarm method of falling based on Android platform MEMS/ Magnetic Sensor/GPS, it is characterised in that include following Step:

1) data acquisition: by the 3-axis acceleration data of sensor acquisition mobile phone, the geomagnetic field intensity data of position, three Shaft angle speed data；

2) data analysis: try to achieve attitude and the reality of carrier according to the data of 3-axis acceleration sensor, gyroscope and Magnetic Sensor Time attitude spin matrix

Specific as follows:

2.1) calculate according to 3-axis acceleration sensor output valveWhereinFor acceleration modulus value, if meetingProceed to step 2.2), ifOrProceed to step 2.5)；

2.2) data of 3-axis acceleration sensor and Magnetic Sensor are normalized；

2.3) utilize the data of 3-axis acceleration sensor and Magnetic Sensor, gyro data be corrected:

errorp_ω|_k=k_p1accerror|_k+k_p2magerror|_k

errorInt_ω|_k=errorInt_ω|_k-1+(k_i1accerror|_k+k_i2magerror|_k)t

${\widehat{\mathrm{\ω}}}^b{|}_k={\mathrm{\ω}}^b{|}_k+{\mathrm{errorp}}_{\mathrm{\ω}}{|}_k+{\mathrm{errorInt}}_{\mathrm{\ω}}{|}_k$

errorp_ω|_kAnd errorInt_ω|_kBeing respectively error rate item and integral term, t is sensor sample interval, ω^bFor gyro The output data of instrument；Data after correcting for gyroscope, k_p1、k_p2It is respectively accelerometer and Magnetic Sensor calibration gyroscope Time proportional term gain, k_i1、k_i2It is respectively integral term gain when accelerometer and Magnetic Sensor calibration gyroscope； Accerror is the gyroscope X-axis asked for according to accelerometer output valve and Y-axis drift, and magerror is defeated according to Magnetic Sensor Go out the gyroscope Z axis drift that value is asked for；

2.4) bring the gyro data after correction into quaternion differential equation, update quaternary number, the carrier angle of pitch, horizontal stroke Roll angle and course angle；

2.5) attitude is resolved by gyroscope integration；

3) according to attitude spin matrixTry to achieve 3-axis acceleration projection under referential under carrier systemDescribed carrier system is mobile phone transverse axis, the longitudinal axis and the orthogonal coordinate system axially constituted of vertical mobile phone plane, institute Stating referential is navigational coordinate system, takes geographic coordinate system here as navigational coordinate system；

4) calculateThe absolute value poor with gravitational constant g, ifAnd the persistent period is more than or equal to t₁, the most tentatively judge For falling, wherein C is decision threshold of falling；

5) t that fallen tentatively it is judged as₂After time, at time t₃If interior Δ γ > 10 ° or Δ θ > 10 °, being i.e. judged as falling, otherwise Being considered as interference, abandon data, wherein Δ γ is carrier angle of pitch changing value, and Δ θ is carrier roll angle changing value.

Method the most according to claim 2, it is characterised in that described step 2.3) in k_p2And k_i2It is set to fixed value.

Method the most according to claim 2, it is characterised in that described step 2.3) the middle method using fuzzy control, root Parameter accerror asked for according to carrier different motion state is automatically adjusted k_p1And k_i1。

Method the most according to claim 2, it is characterised in that described step 2.3) in, according to carrier different motion state Parameter accerror asked for is automatically adjusted k_p1And k_i1, concrete formula is as follows:

Wherein c₁、c₂、c₃、c₄、c₅、c₆For coefficient constant.