CN104000596B - A kind of fall detection method based on mobile terminal - Google Patents
A kind of fall detection method based on mobile terminal Download PDFInfo
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Abstract
The invention discloses a kind of fall detection methods based on mobile terminal, comprise the following steps: detection resultant acceleration SVM1, judge whether resultant acceleration SVM1 has been more than to set weightless threshold value A min；As SVM1 < Amin, compound direction signal Ω 1 is detected, judges whether direction signal Ω 1 is more than setting tilt angle threshold value Ω min；As Ω 1 < Ω min, close angle speed omega is detected, judges whether the close angle speed omega is more than set angle threshold speed ω min；Work as ω > ω min, detects resultant acceleration SVM2；In setting detection time t1, as resultant acceleration SVM2 > setting impact acceleration threshold value A max, compound direction signal Ω 2 is detected, judges whether direction signal Ω 2 is more than the human body tumble gradient threshold value Ω max set；As Ω 2 < Ω max, illustrate that people has fallen；The signal processing that will be deemed as human body tumble forms voice prompting signal, image display signal.Characteristic acceleration during the present invention falls with reference to human body, human body heeling condition, angular speed etc. obtain the parameter needed using sensor built-in in mobile phone, analyze and determine whether human body falls.
Description
Technical field
The present invention relates to identification human body tumble situations, and in particular to a kind of fall detection method based on mobile terminal.
Background technique
As China human mortality aging gradually rises, social Empty nest elderly is more and more.And Old Men is weaker, usually
Meeting accidentally tumble, falls and itself has caused great damage to the elderly, but will bring cause to the elderly without rescuing in time
The danger of life.Therefore, various effective identification human body tumble situations, and and alarm method, be of great importance to society.Wherein
It separately includes: judging whether human body falls by being monitored in real time and being analyzed to human body based on Video Analysis Technology；It is based on
Sound signal analytical technology, frequency when tumble situation hits ground by analysis people such as judge at a variety of judgment methods.
One of equipment is carried as smart phone becomes the people, identification human body tumble shape is realized based on smart phone
Condition becomes a kind of more convenient, effective method, cannot obtain succouring bring in time after capable of reducing Falls in Old People well
Injury.
Summary of the invention
The purpose of the present invention is to provide a kind of fall detection methods based on mobile terminal.The daily exercise behavior master of people
To include walking, stand up, sit down, running etc..Walking and when standing up without weightless feature, the conjunction for brief acceleration sensor of sitting down adds
Speed is far smaller than acceleration when hitting, and body inclination angle change less and does not have angular speed when running.Therefore it is above-mentioned this
Human body can be fallen well for a little features and daily other motor behaviors distinguish.By the present invention in that with intelligent sliding is built in
The various kinds of sensors of dynamic terminal is being confirmed whether judgement just by mobile terminal touch display to detect whether human body falls
Really, while tumble people position can be positioned by the GPS module in mobile terminal, and is sought help by short message, phone；
It can quickly and effectively avoid due to that cannot obtain succouring bring human injury in time after falling.
In order to achieve the above object, the invention is realized by the following technical scheme:
A kind of fall detection method based on mobile terminal, its main feature is that, this method comprises the following steps:
Step S1 detects resultant acceleration SVM1, judges whether resultant acceleration SVM1 has been more than the weightless threshold value set
Amin；As SVM1 < Amin, step S2 is executed.
Step S2 detects compound direction signal Ω 1, judges whether direction signal Ω 1 is more than the human body set and ground
Tilt angle threshold value Ω min execute step 3 as Ω 1 < Ω min.
Step S3, detect close angle speed omega, judge the close angle speed omega whether be more than setting angular speed threshold value ω min；
Work as ω > ω min, executes step S4.
Step S4 detects resultant acceleration SVM2, in the detection time t1 of setting, when resultant acceleration SVM2 is more than setting
Impact acceleration threshold value A max when, execute step 5.
Step S5 detects compound direction signal Ω 2, and judges whether direction signal Ω 2 is more than that the human body set is fallen
Gradient threshold value Ω max；As Ω 2 < Ω max, illustrate that people has fallen, executes step S6.
Step S6, the signal processing that will be deemed as human body tumble are respectively formed voice prompting signal, image display signal.
The above-mentioned fall detection method based on mobile terminal, its main feature is that, above-mentioned steps S1 specifically executes as follows: three axis add
Velocity sensor detects resultant acceleration SVM1, and the result that will test is transmitted to CPU, and above-mentioned CPU judges the resultant acceleration
Whether SVM1 has been more than the weightless threshold value A min set；When resultant acceleration SVM1 is less than weightlessness threshold value A min, step is executed
Rapid S2；Otherwise above-mentioned 3-axis acceleration sensor detects resultant acceleration SVM1 again.
The above-mentioned fall detection method based on mobile terminal, its main feature is that, above-mentioned steps S2, above-mentioned CPU start above-mentioned
3-axis acceleration sensor and magnetometric sensor obtains respectively and detects signal and be transmitted to above-mentioned CPU, the CPU is by above-mentioned two
The detection signal compound direction signal Ω 1 that a sensor obtains, and judge direction signal Ω 1 whether be more than setting human body with
The tilt angle threshold value Ω min on ground executes step 3 as Ω 1 < Ω min；As Ω 1 >=Ω min, go to step S1.
The above-mentioned fall detection method based on mobile terminal, its main feature is that, above-mentioned steps S3, above-mentioned CPU start gyro
Instrument sensor detects close angle speed omega, and the close angle speed omega is transmitted to above-mentioned CPU, which judges the close angle speed omega
It whether is more than the angular speed threshold value ω min set；Work as ω > ω min, executes step S4；Otherwise go to step S1.
The above-mentioned fall detection method based on mobile terminal, its main feature is that, above-mentioned steps S4, above-mentioned CPU start above-mentioned
3-axis acceleration sensor detect resultant acceleration SVM2, the CPU setting detection time t1 in, as resultant acceleration SVM2
When the impact acceleration threshold value A max of > setting, step 5 is executed；Otherwise go to step S1.
The above-mentioned fall detection method based on mobile terminal, its main feature is that, above-mentioned steps S5, above-mentioned CPU are again started up
Above-mentioned 3-axis acceleration sensor, magnetometric sensor are detected respectively, which synthesizes above-mentioned two detection signal processing
Direction signal Ω 2, and judge whether direction signal Ω 2 is more than the human body tumble gradient threshold value Ω max set；As 2 < Ω of Ω
Max illustrates that people has fallen, and executes step S6；Otherwise go to step S1.
The above-mentioned fall detection method based on mobile terminal, its main feature is that, above-mentioned steps S6, above-mentioned CPU will be deemed as
The signal processing that human body is fallen is respectively formed voice prompting signal, image display signal, and is transmitted separately to loudspeaker, mobile terminal
Touch display.
The above-mentioned fall detection method based on mobile terminal, its main feature is that, in mobile terminal sleep, above-mentioned CPU is opened
Whether there is barrier in front of dynamic range sensor detection mobile terminal；When above-mentioned range sensor detects obstacle signal
When, it is judged as that human body carries the mobile terminal, then the signal is transmitted to the CPU, so that the CPU starts three above-mentioned axis and accelerates
Degree sensor carries out above-mentioned step S1；When obstacle signal is not detected in the range sensor, mobile terminal and people are judged
Body separation, without starting the 3-axis acceleration sensor.
The above-mentioned fall detection method based on mobile terminal, its main feature is that, starting or operating status are in mobile terminal
When, above-mentioned 3-axis acceleration sensor automatically begins to carry out detection resultant acceleration SVM1.
The above-mentioned fall detection method based on mobile terminal, its main feature is that, above-mentioned step S6 is also comprised the following steps:
Step S6.1, in the response time t2 of setting, above-mentioned mobile terminal touch display is not passed to above-mentioned CPU
When defeated confirmation information is wrong report, which starts GPS module and carries out human body positioning, which receives determining for above-mentioned GPS module
Position signal is sought help to and by short message or phone；
Step S6.2, in the response time t2 of setting, which transmits to the CPU confirms the letter
When breath is reports by mistake, terminate this operation.
Compared with the prior art, the present invention has the following advantages:
1, the feature of motion change state during being fallen by analysis human body, and find out these features and daily life fortune
The difference of dynamic feature.The feature of Primary Reference is acceleration, human body heeling condition, angular speed etc. in the present invention.
2, according to the analysis of front, the parameter needed is obtained using sensor built-in in mobile phone respectively, and analyse whether
It is consistent with the situation of tumble.
3, finally judge whether to fall, if fallen, by GPS positioning information, and information is issued thing by mobile phone
First specified personnel wait emergency.
Detailed description of the invention
Fig. 1 is a kind of overall flow figure of the fall detection method based on mobile terminal of the present invention.
Fig. 2 is a kind of system structure diagram of the fall detection method based on mobile terminal of the present invention.
Specific embodiment
The present invention is further elaborated by the way that a preferable specific embodiment is described in detail below in conjunction with attached drawing.
As shown in Fig. 2, the fall detection system based on mobile terminal includes: CPU 10 and three axis connected to it accelerate
Spend sensor 20, gyro sensor 30, range sensor 40, magnetometric sensor 50, GPS module 60, loudspeaker 70 and movement eventually
Hold touch display 80.CPU 10 carries out both-way communication with above-mentioned module respectively.The detection system is built in intelligent mobile terminal.
In real life, mobile phone is generally placed in trousers or the pocket of coat two sides by people, close to loins,
It can be good at reflecting the motion state of human body, the position that the present invention defaults mobile phone is put in the position.
There are four types of the common tumble modes of human body, is preceding respectively to tumble, backward to fall, left side is fallen, and right side is fallen.?
In these types of tumble mode, have several important features: weightless, human body can be from uprightly to sloping up to ground close to flat
Row hits ground.The present invention is to pass through the above-mentioned fall detection system being arranged in intelligent mobile terminal according to several features as above
System is realized to human body fall detection.
As shown in Figure 1, a kind of fall detection method based on mobile terminal, this method comprise the following steps:
Step S1,3-axis acceleration sensor 20 detects resultant acceleration SVM1, and the result that will test is transmitted to CPU
10, above-mentioned CPU 10 judge whether resultant acceleration SVM1 has been more than the weightless threshold value A min set；As resultant acceleration SVM1
When being less than weightlessness threshold value A min, step S2 is executed；Otherwise above-mentioned 3-axis acceleration sensor 20 detects conjunction again and accelerates
Spend SVM1.
In the present embodiment, weightlessness threshold value A min=0.4g(g is set as acceleration of gravity).
Under normal circumstances, the resultant acceleration that 3-axis acceleration sensor 20 detects accelerates mobile terminal close to gravity
Spend g；During tumble, human body will appear weightlessness.Then during tumble, 3-axis acceleration sensor 20 is detected
Resultant acceleration be significantly less than gravity acceleration g.Wherein, the algorithm of resultant acceleration is as follows:
It is acceleration of the 3-axis acceleration sensor 20 in x-axis, y-axis and z-axis respectively.
Step S2, CPU 10 starts above-mentioned 3-axis acceleration sensor 20 and magnetometric sensor 50 and obtains detection respectively
Signal is simultaneously transmitted to above-mentioned CPU 10, the detection signal compound direction signal Ω which obtains above-mentioned two sensor
1, and judge whether direction signal Ω 1 is more than the human body of setting and the tilt angle threshold value Ω min on ground, as Ω 1 < Ω min,
Execute step 3；As Ω 1 >=Ω min, go to step S1.
For human body when standing, the angle on human body and ground is about 90 °；When tumble, the angle on human body and ground is persistently reduced,
When falling over, angle is about 0 °.In the present invention, the inspection that is generated respectively by 3-axis acceleration sensor 20, magnetometric sensor 50
The processing that signal passes through CPU 10 is surveyed, direction signal Ω 1 is formed, can also obtain the angle Ω 1 on human body and ground.
In the present embodiment, the value of Ω min is。
Step S3, CPU 10 starts gyro sensor 30 and detects close angle speed omega, and the close angle speed omega is transmitted to
CPU 10, the CPU 10 judge the close angle speed omega whether be more than setting angular speed threshold value ω min；Work as ω > ω min, executes
Step S4；Otherwise go to step S1.
During human body is fallen, a biggish close angle speed omega can be generated, close angle speed omega is gyro sensor
The conjunction speed of 30 angular speed generated in three directions of x-axis, y-axis and z-axis, algorithm are as follows:
It is the angular speed that gyro sensor 30 generates in three directions of x-axis, y-axis and z-axis respectively.
In the present embodiment, ω min is set as the rad/s of π/6.
Step S4, CPU 10 starts 3-axis acceleration sensor 20 and detects resultant acceleration SVM2, in the CPU 10 setting
In detection time t1, when resultant acceleration SVM2 is more than the impact acceleration threshold value A max of setting, step 5 is executed；Otherwise it jumps
Go to step S1.
During human body and ground struck, a very big resultant acceleration SVM2, test discovery, in the mistake can be generated
The gravity acceleration g (i.e. 12.9g) that the maximum resultant acceleration SVM2 generated in journey is 12.9 times, minimum resultant acceleration SVM2 are
4.9g averagely reaches 6.1g.Therefore, in the present invention, CPU 10 is again started up 3-axis acceleration sensor 20 and detects resultant acceleration
SVM2, in the present embodiment, Amax=4.9g in the detection time t1 in setting, when SVM2 > 4.9g, determines that human body and ground are sent out
Shock is given birth to；Otherwise, S1 is returned to step, detection is re-started.
Step S5, above-mentioned CPU 10 is again started up above-mentioned 3-axis acceleration sensor 20, magnetometric sensor 50 is distinguished
It is detected, which judges that direction signal Ω 2 is for above-mentioned two detection signal processing compound direction signal Ω 2
No is more than the human body tumble gradient threshold value Ω max of setting；As Ω 2 < Ω max, illustrate that people has fallen, executes step S6；Otherwise
Go to step S1.
In the present embodiment, Ω max value is。
Step S6, the signal processing that above-mentioned CPU 10 will be deemed as human body tumble are respectively formed voice prompting signal, figure
As display signal, and it is transmitted separately to loudspeaker 70, mobile terminal touch display 80.The step comprises the following steps:
Step S6.1, in the response time t2 of setting, mobile terminal touch display 80, which is not transmitted to CPU 10, to be confirmed
When the information is wrong report, which starts GPS module 60 and carries out human body positioning, which receives the positioning of GPS module 60
Signal is sought help to and by short message or phone；
Step S6.2, in the response time t2 of setting, which transmits really to the CPU 10
When recognizing the information to report by mistake, terminate this operation.
Above-mentioned steps S6 can reduce rate of false alarm, so as to avoid the subsequent action generated due to wrong report.
A kind of fall detection method based on mobile terminal provided by the invention, before executing step S1, when mobile whole
When holding suspend mode, CPU 10 starts range sensor 40 and detects in front of mobile terminal whether have barrier；When range sensor 40 is examined
When measuring obstacle signal, it is judged as that human body carries the mobile terminal, then the signal is transmitted to the CPU 10, so that the CPU
10 starting 3-axis acceleration sensors 20 carry out above-mentioned step S1；When obstacle signal is not detected in the range sensor 40
When, judge that mobile terminal is separated with human body, without starting the 3-axis acceleration sensor 20.
Before executing step S1, when mobile terminal is in starting or operating status, above-mentioned 3-axis acceleration sensing
Device 20 carries out above-mentioned steps S1, automatically begins to carry out detection resultant acceleration SVM1.
By above-mentioned setting, this method can reduce the consumption to battery of mobile terminal.
It is discussed in detail although the contents of the present invention have passed through above preferred embodiment, but it should be appreciated that above-mentioned
Description is not considered as limitation of the present invention.After those skilled in the art have read above content, for of the invention
A variety of modifications and substitutions all will be apparent.Therefore, protection scope of the present invention should be limited to the appended claims.
Claims (9)
1. a kind of fall detection method based on mobile terminal, which is characterized in that this method comprises the following steps:
Step S1 detects resultant acceleration SVM1, judges whether resultant acceleration SVM1 has been more than the weightless threshold value A min set；When
When SVM1 < Amin, step S2 is executed；
Step S2 detects compound direction signal Ω 1, judges whether direction signal Ω 1 is more than the human body of setting and inclining for ground
Rake angle threshold value Ω min executes step S3 as Ω 1 < Ω min；
Step S3, detect close angle speed omega, judge the close angle speed omega whether be more than setting angular speed threshold value ω min；Work as ω >
When ω min, step S4 is executed；
Step S4 detects resultant acceleration SVM2, in the detection time t1 of setting, when resultant acceleration SVM2 is more than hitting for setting
When hitting acceleration rate threshold Amax, step S5 is executed；
Step S5 detects compound direction signal Ω 2, and judges whether direction signal Ω 2 is more than the human body tumble inclination set
Spend threshold value Ω max；As Ω 2 < Ω max, illustrate that people has fallen, executes step S6；
Step S6, the signal processing that will be deemed as human body tumble are respectively formed voice prompting signal, image display signal；
Before executing the step S1, when mobile terminal sleep, it is mobile eventually that CPU (10) starts range sensor (40) detection
Whether end front has barrier；When the range sensor (40) detects obstacle signal, it is judged as that human body carries and is somebody's turn to do
The signal is then transmitted to the CPU (10) by mobile terminal, so that the CPU (10) starting 3-axis acceleration sensor (20) carries out
The step S1；When obstacle signal is not detected in the range sensor (40), judge that mobile terminal is separated with human body, nothing
The 3-axis acceleration sensor (20) need to be started.
2. as described in claim 1 based on the fall detection method of mobile terminal, which is characterized in that the step S1 is specific
It executes as follows:
3-axis acceleration sensor (20) detects resultant acceleration SVM1, and the result that will test is transmitted to CPU (10), described
CPU (10) judges whether resultant acceleration SVM1 has been more than the weightless threshold value A min set；When resultant acceleration SVM1 is less than this
When weightless threshold value A min, step S2 is executed；Otherwise the 3-axis acceleration sensor (20) detects resultant acceleration SVM1 again.
3. as claimed in claim 2 based on the fall detection method of mobile terminal, which is characterized in that the step S2 is specific
It executes as follows:
CPU (10) starting 3-axis acceleration sensor (20) and magnetometric sensor (50) obtain detection letter respectively
Number and be transmitted to the CPU (10), which obtains 3-axis acceleration sensor (20) and magnetometric sensor (50)
Signal compound direction signal Ω 1 is detected, and judges whether direction signal Ω 1 is more than the human body of setting and the tilt angle on ground
Threshold value Ω min executes step S3 as Ω 1 < Ω min；As Ω 1 >=Ω min, go to step S1.
4. as claimed in claim 3 based on the fall detection method of mobile terminal, which is characterized in that the step S3 is specific
It executes as follows:
CPU (10) starting gyro sensor (30) detects close angle speed omega, and the close angle speed omega is transmitted to institute
The CPU (10) stated, the CPU (10) judge the close angle speed omega whether be more than setting angular speed threshold value ω min；Work as ω > ω min
When, execute step S4；Otherwise go to step S1.
5. as claimed in claim 4 based on the fall detection method of mobile terminal, which is characterized in that the step S4 is specific
It executes as follows:
CPU (10) starting 3-axis acceleration sensor (20) detects resultant acceleration SVM2, sets in the CPU (10)
In fixed detection time t1, as resultant acceleration SVM2 > setting impact acceleration threshold value A max, step S5 is executed；Otherwise
Go to step S1.
6. as claimed in claim 5 based on the fall detection method of mobile terminal, which is characterized in that the step S5 is specific
It executes as follows:
The CPU (10) is again started up the 3-axis acceleration sensor (20), magnetometric sensor (50) is examined respectively
It surveys, which believes the detection signal processing compound direction that 3-axis acceleration sensor (20), magnetometric sensor (50) obtain
Number Ω 2, and judge direction signal Ω 2 whether be more than setting human body tumble gradient threshold value Ω max；As Ω 2 < Ω max,
Illustrate that people has fallen, executes step S6；Otherwise go to step S1.
7. as claimed in claim 6 based on the fall detection method of mobile terminal, which is characterized in that the step S6 is specific
It executes as follows:
It is aobvious that the signal processing that step S6, the CPU (10) will be deemed as human body tumble is respectively formed voice prompting signal, image
Show signal, and is transmitted separately to loudspeaker (70), mobile terminal touch display (80).
8. as described in claim 1 based on the fall detection method of mobile terminal, which is characterized in that executing the step
Before S1, when mobile terminal is in starting or operating status, the 3-axis acceleration sensor (20) automatically begins to carry out
The step S1.
9. as claimed in claim 7 based on the fall detection method of mobile terminal, which is characterized in that the step S6 is also wrapped
Containing following steps:
Step S6.1, in the response time t2 of setting, the mobile terminal touch display (80) is not to the CPU
(10) when transmission confirms that the information is wrong report, which starts GPS module (60) and carries out human body positioning, which receives
The positioning signal of the GPS module (60) is sought help to and by short message or phone, terminates this operation；
Step S6.2, in the response time t2 of setting, which transmits to the CPU (10) confirms
When the information is wrong report, terminate this operation.
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| CN104808240A (en) * | 2014-08-29 | 2015-07-29 | 中国航空工业集团公司北京长城计量测试技术研究所 | Identification method for space posture and motion state of earthquake measuring terminal |
| CN104799862B (en) * | 2015-04-02 | 2018-06-19 | 中国海洋大学 | A kind of human body is unbalance method for early warning and system |
| CN106610438B (en) * | 2015-10-22 | 2019-06-25 | 北京金坤科创技术有限公司 | A kind of falling from high altitude detection method based on 3-axis acceleration |
| CN105336102B (en) * | 2015-11-25 | 2017-10-24 | 青岛理工大学 | Fall down detection localization method and device |
| CN105891901A (en) * | 2015-12-21 | 2016-08-24 | 乐视移动智能信息技术（北京）有限公司 | Electronic system and method for preventing mobile terminal from being scratched by metal and mobile terminal |
| CN105448041B (en) * | 2016-01-22 | 2018-04-17 | 苏州望湖房地产开发有限公司 | A kind of falling over of human body intelligence control system and its method |
| CN105654666B (en) * | 2016-02-25 | 2018-03-20 | 福州大学 | Falls in Old People monitoring method based on MEMS sensor |
| CN108353102B (en) * | 2016-11-15 | 2020-10-09 | 华为技术有限公司 | Obstacle prompting method and terminal equipment |
| CN106530616A (en) * | 2016-12-06 | 2017-03-22 | 上海斐讯数据通信技术有限公司 | Automatic alarm method and system |
| CN107633655A (en) * | 2017-09-26 | 2018-01-26 | 深圳市金立通信设备有限公司 | A kind of fall detection method, terminal and computer-readable recording medium |
| CN108175388B (en) * | 2017-12-01 | 2021-01-26 | 中国联合网络通信集团有限公司 | Behavior monitoring method and device based on wearable equipment |
| CN108760214A (en) * | 2018-04-27 | 2018-11-06 | Oppo广东移动通信有限公司 | Projected angle of impact acquisition methods and Related product |
| CN110266884A (en) * | 2019-06-20 | 2019-09-20 | 广东小天才科技有限公司 | A kind of fall protection method, apparatus, equipment and the storage medium of smart machine |
| CN112258785B (en) * | 2019-11-27 | 2022-06-07 | 北京京东尚科信息技术有限公司 | Fall detection method and device and storage medium |
| CN111466903A (en) * | 2020-04-23 | 2020-07-31 | 杭州微萤科技有限公司 | Fall detection method and device |
| CN113450539B (en) * | 2021-07-12 | 2022-05-17 | 杭州电子科技大学 | Fall detection method |
| WO2023092253A1 (en) * | 2021-11-23 | 2023-06-01 | 罗伯特·博世有限公司 | Method for detecting fall, and wearable device |
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| JP5893919B2 (en) * | 2011-12-28 | 2016-03-23 | メタウォーター株式会社 | Human body behavior detection method and system for water treatment facilities |
| US8954135B2 (en) * | 2012-06-22 | 2015-02-10 | Fitbit, Inc. | Portable biometric monitoring devices and methods of operating same |
| CN103142234B (en) * | 2013-01-25 | 2015-04-01 | 中国科学院深圳先进技术研究院 | Method for judging body falldown |
| CN103561144A (en) * | 2013-11-18 | 2014-02-05 | 中国人民解放军信息工程大学 | Tumbling detection method and device based on smart phone |
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