CN107146378A - A kind of human body tumble decision method and device - Google Patents
A kind of human body tumble decision method and device Download PDFInfo
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- CN107146378A CN107146378A CN201710417383.6A CN201710417383A CN107146378A CN 107146378 A CN107146378 A CN 107146378A CN 201710417383 A CN201710417383 A CN 201710417383A CN 107146378 A CN107146378 A CN 107146378A
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- 238000000034 method Methods 0.000 title claims abstract description 34
- 230000001133 acceleration Effects 0.000 claims abstract description 87
- 238000001914 filtration Methods 0.000 claims description 14
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims description 8
- 229910052744 lithium Inorganic materials 0.000 claims description 8
- 125000006850 spacer group Chemical group 0.000 claims description 2
- 238000001514 detection method Methods 0.000 abstract description 14
- 230000009471 action Effects 0.000 abstract description 7
- 230000008859 change Effects 0.000 description 11
- 238000002474 experimental method Methods 0.000 description 5
- 230000007613 environmental effect Effects 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 241000283216 Phocidae Species 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 239000011521 glass Substances 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 241000446313 Lamella Species 0.000 description 1
- 206010033799 Paralysis Diseases 0.000 description 1
- 208000027418 Wounds and injury Diseases 0.000 description 1
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- 230000004886 head movement Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 239000000725 suspension Substances 0.000 description 1
- 230000035899 viability Effects 0.000 description 1
Classifications
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
- G08B21/0407—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis
- G08B21/043—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis detecting an emergency event, e.g. a fall
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
- G08B21/0438—Sensor means for detecting
- G08B21/0446—Sensor means for detecting worn on the body to detect changes of posture, e.g. a fall, inclination, acceleration, gait
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
- G08B29/18—Prevention or correction of operating errors
- G08B29/185—Signal analysis techniques for reducing or preventing false alarms or for enhancing the reliability of the system
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- Psychology (AREA)
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Abstract
A kind of human body tumble decision method, its specific steps include：(1) acceleration in the x-axis of human body, y-axis, z-axis direction is acquired, and x-axis, y-axis, the acceleration rate threshold in z-axis direction is set respectively；(2) when collecting x-axis, the acceleration in y-axis direction is uprushed, and when exceeding corresponding acceleration rate threshold respectively, the acceleration and the acceleration rate threshold in z-axis direction in z-axis direction are compared；(3) when the acceleration in z-axis direction is less than the acceleration rate threshold in z-axis direction, it is determined as tumble behavior.Detection algorithm of the invention based on 3-axis acceleration threshold value, by the action of 3-axis acceleration, judges whether to fall, and judges more directly simple, while the high and low false alarm rate of judging nicety rate.
Description
Technical field
Fall and judge the invention belongs to intelligence wearing technical field, more particularly to a kind of human body tumble decision method and human body
Device.
Background technology
Tumble is to endanger one of the elderly and the key factor of other special populations.Tumble has become old man's injury scope
Number one killer.Timely fall detection and relief can be that the quality time is won in treatment and rescue, the independence to improving old man
Viability, ensure its health and improve medical monitoring level that all there is very important effect.
Intelligent object in the market carries out the algorithm of human body tumble, is to be based on being worn on body waist or more portion mostly
Position, determines whether to fall using acceleration change when falling.Small part intelligent object is placed in sole, and what judgement tumble was taken is
Anticipation mode, i.e., can increase process by acceleration, the probability of this judgement erroneous judgement is larger for some time according to before tumble.
Current existing fall detection method can be roughly divided into three classes：One class is the detection method based on video.The party
Method detects that user falls using image processing techniques by laying colored or depth camera in the environment.The method is not required to
Want user's wearable device and there is more ripe algorithm to support, but monitoring range is limited, easily by such environmental effects such as light, and not
Beneficial to protection privacy of user.Another kind of is the method based on environmental variance.Method based on environmental variance passes through cloth in the environment
If the senser elements such as pressure, vibrations and sound carry out the tumble of comprehensive descision user.The method principle is simple and by environmental factor shadow
Sound is smaller, but deployment cost is high and monitoring range is limited.An also class is the motion sensor gathered based on Wearable device
The detection method of (such as accelerometer, gyroscope) data.In the prior art, the dress of motion sensor will be generally integrated with
Put, be fixed on user's particular body portion (such as front, waist, leg), by recognize privileged site motion and posture come
Judge that user falls.The method scope limitation not monitored, it is possible to achieve continuous detection, but due to requiring specific in body in real time
The awareness apparatus of position wearing more inconvenience, very big interference is brought to user's daily life, the reality of such method is limited
Apply and promote in border.
In recent years, emerge increasing new wearable device, for example intelligent glasses, intelligent spire lamella, intelligent watch,
Intelligent shoe etc., these new wearable devices reduce the limitation to equipment wearing position, therefore, it can consider to fall to examine
Device is surveyed to be dissolved into new wearable device to reduce the interference that detection means lives to user.However, these are new wearable
The kinematic dexterity of the corresponding wearing position of equipment is higher, and this human body movement data for causing motion sensor to be gathered has more
High complexity and diversity, is difficult to using traditional detection method while obtaining high detection rate and low false alarm rate.
Therefore, currently in the urgent need to one kind is suitable for be based on having high complexity and multifarious exercise data
(such as head movement data) realize the fall detection solution of high detection rate and low false alarm rate.
Intelligent object is placed in sole in the present invention, is based on the substantial amounts of analysis to human body tumble action process, to falling
The state of very short time afterwards and before is analyzed, and is judged whether after the acceleration change of comprehensive analysis laterally, longitudinally
Fall.This algorithm avoids a large amount of wrong reports, the accuracy fallen and judged is improved.
The content of the invention
The present invention proposes a kind of human body tumble decision method of the high and low false alarm rate of judging nicety rate.
Present invention also offers a kind of human body tumble decision maker of the high and low false alarm rate of judging nicety rate.
The technical solution adopted by the present invention is：
A kind of human body tumble decision method, its specific steps include：
(1) acceleration in the x-axis of human body, y-axis, z-axis direction is acquired, and x-axis, y-axis, z-axis direction is set respectively
Acceleration rate threshold；
(2) when collecting x-axis, the acceleration in y-axis direction is uprushed, and when exceeding corresponding acceleration rate threshold respectively, to z-axis
The acceleration in direction and the acceleration rate threshold in z-axis direction are compared；
(3) when the acceleration in z-axis direction is less than the acceleration rate threshold in z-axis direction, it is determined as tumble behavior.Base of the present invention
In the detection algorithm of 3-axis acceleration threshold value, by the action of 3-axis acceleration, judge whether to fall, judge more directly simple,
While the high and low false alarm rate of judging nicety rate.
Further, in addition to step (4) occur tumble behavior after send tumble alarm signal and notify guardian in time.
Further, the acceleration of collection carries out data filtering in step (1).
Further, data filtering uses kalman filter method.
A kind of human body tumble decision maker, is horizontally mounted and seals inside plant sole, including housing, it is characterised in that：Institute
State and circuit board, charge coil, chargeable lithium cell are installed in housing, be provided with and isolate between the charge coil and circuit board
Piece, the chargeable lithium cell is connected with circuit board, and human body tumble determination module is integrated with the circuit board, and the human body falls
Determination module is used to compare to determine whether to exist tumble behavior according to 3-axis acceleration and predetermined acceleration threshold value.The present invention
Device is arranged at sole and judges tumble behavior by human body tumble determination module, and False Rate is low；And entered by charge coil
Row wireless charging mode charges to chargeable lithium cell, therefore need not pull down human body tumble decision maker and charged, and makes
With conveniently.
Further, the human body tumble determination module includes being connected with use on primary processor and coprocessor, coprocessor
In the 3-axis acceleration sensor of collection 3-axis acceleration, the coprocessor is connected with primary processor, on the primary processor
It is connected with the eSIM cards that guardian is notified for call voice.
Further, bluetooth 2.4G antennas are also associated with the coprocessor.
Further, GSM antenna, gps antenna, WiFi antennas, Flash modules are also associated with the primary processor.
Further, it is also associated with alarm module on the primary processor.
The beneficial effects of the invention are as follows：The high and low false alarm rate of human body tumble determination rate of accuracy, it is easy to use.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of the inventive method.
Fig. 2 is the scheme of installation of apparatus of the present invention.
Fig. 3 is the Structure explosion diagram of apparatus of the present invention.
Fig. 4 is the hardware circuit diagram of the present invention.
Embodiment
The present invention is further described with reference to specific embodiment, but does not limit the invention to these tools
Body embodiment.One skilled in the art would recognize that present invention encompasses potentially included in Claims scope
All alternatives, improvement project and equivalents.
Embodiment one
Referring to Fig. 1, a kind of human body tumble decision method, its specific steps include：
(1) acceleration in the x-axis of human body, y-axis, z-axis direction is acquired, and x-axis, y-axis, z-axis direction is set respectively
Acceleration rate threshold；
(2) when collecting x-axis, the acceleration in y-axis direction is uprushed, and when exceeding corresponding acceleration rate threshold respectively, to z-axis
The acceleration in direction and the acceleration rate threshold in z-axis direction are compared；
(3) when the acceleration in z-axis direction is less than the acceleration rate threshold in z-axis direction, it is determined as tumble behavior；
(4) occur to send tumble alarm signal after tumble behavior and notify guardian in time.
Detection algorithm of the invention based on 3-axis acceleration threshold value, by the action of 3-axis acceleration, judges whether to fall,
Judge more directly simple, while the high and low false alarm rate of judging nicety rate.
The acceleration of collection carries out data filtering using kalman filter method in the present embodiment step (1).Acceleration
Measured value often has noise at any time, judges there is extreme influence to falling, it is necessary to carry out data filtering, removal is made an uproar
Sound reduces True Data.Kalman filtering (Kalman filtering) one kind utilizes linear system state equation, passes through system
Data are observed in input and output, and the algorithm of optimal estimation is carried out to system mode, the data of collection in worksite can be carried out real-time
Update and handle.Because observation data include the noise in system and the influence of interference, so optimal estimation is also considered as
Filtering.Using the multidate information of target, try to remove the influence of noise, obtain a preferable number on desired value
Value.
When the present embodiment principle is that human normal is stood, the angle at heel and ground is 0 degree, is walked, running includes
During going up or down stairway, heel of a shoe has a certain degree with ground meeting shape, and at this moment the acceleration magnitude in human body z-axis direction can become with angle
Change and change, the critical point of this state to tumble state has an acceleration threshold values.When static, z-axis directional acceleration value
It is maximum under horizontality, angle is bigger, acceleration magnitude is smaller.When this acceleration magnitude is less than acceleration threshold values, just
It can determine whether to be in tumble state.
Only judge to fall by the change of z-axis directional acceleration value during static state, substantial amounts of erroneous judgement can be caused.Such as rest
When leg is positioned on chair, sole and ground-angle are close to 90 degree, and the acceleration in z-axis direction is very small, less than acceleration bottom valve
Value, will be mistaken for falling.In order to reduce erroneous judgement, x, the change of the acceleration magnitude in y-axis direction during tumble are also analyzed
Situation.During standing, this two to acceleration magnitude be essentially 0, walk, run and during going up or down stairway, x-axis direction is still essentially 0,
Y-axis directional acceleration value can change with the angle change on heel and ground, to fall (fore-and-aft direction) when, y-axis direction
Acceleration have one and uprush, when laterally falling, x-axis directional acceleration value can be uprushed, and an acceleration is set in this critical point
Bottom valve value, more than this acceleration threshold values, the condition judged as falling adds with reference to z-axis directional acceleration value with corresponding
Whether the comparison of speed threshold, comprehensive descision falls, the high and low false alarm rate of judging nicety rate.
Embodiment two
Referring to Fig. 2-4, a kind of human body tumble decision maker 10 is horizontally mounted and sealed inside plant sole, including housing 1,
Circuit board 2, charge coil 4, chargeable lithium cell 5 are installed in the housing 1, set between the charge coil 4 and circuit board 2
There is spacer 3, the chargeable lithium cell 5 is connected with circuit board 2, and human body tumble determination module is integrated with the circuit board 2,
The human body tumble determination module is used to be compared according to 3-axis acceleration and predetermined acceleration threshold value falls to determine whether to exist
Behavior.Apparatus of the present invention are arranged at sole and judge tumble behavior by human body tumble determination module, and False Rate is low；And pass through
Charge coil carries out wireless charging mode and chargeable lithium cell is charged, therefore need not pull down human body tumble decision maker and enter
Row charging, it is easy to use.
Human body tumble determination module described in the present embodiment includes being connected with use on primary processor and coprocessor, coprocessor
In the 3-axis acceleration sensor of collection 3-axis acceleration, the coprocessor is connected with primary processor, on the primary processor
It is connected with the eSIM cards that guardian is notified for call voice, the coprocessor and is also associated with bluetooth 2.4G antennas, it is described
GSM antenna, gps antenna, WiFi antennas, Flash modules, alarm module are also associated with primary processor.
The human body tumble decision method of human body tumble determination module described in the present embodiment, specific steps include：
(1) acceleration in the x-axis of human body, y-axis, z-axis direction is acquired, and x-axis, y-axis, z-axis direction is set respectively
Acceleration rate threshold；
(2) when collecting x-axis, the acceleration in y-axis direction is uprushed, and when exceeding corresponding acceleration rate threshold respectively, to z-axis
The acceleration in direction and the acceleration rate threshold in z-axis direction are compared；
(3) when the acceleration in z-axis direction is less than the acceleration rate threshold in z-axis direction, it is determined as tumble behavior；
(4) occur to send tumble alarm signal after tumble behavior and notify guardian in time.
The acceleration of collection carries out data filtering using kalman filter method in the present embodiment step (1).Acceleration
Measured value often has noise at any time, judges there is extreme influence to falling, it is necessary to carry out data filtering, removal is made an uproar
Sound reduces True Data.Kalman filtering (Kalman filtering) one kind utilizes linear system state equation, passes through system
Data are observed in input and output, and the algorithm of optimal estimation is carried out to system mode, the data of collection in worksite can be carried out real-time
Update and handle.Because observation data include the noise in system and the influence of interference, so optimal estimation is also considered as
Filtering.Using the multidate information of target, try to remove the influence of noise, obtain a preferable number on desired value
Value.
Human body tumble decision maker 10 in the present embodiment, is to solve the problem of judging of whether being fallen to human body
, from it is other intelligence wearing unlike, the present apparatus be place and seal plant sole inside, be not belonging to additionally increased wearing product
(such as bracelet, glasses, suspension member), as shown in Figure 2.And charged using wireless charging mode, only need to be by shoes on request
Direction, position are positioned on charging panel 20, without pulling down device charging.The device gathers people's row by acceleration transducer
Acceleration when dynamic, tumble behavior is determined whether using the human body tumble decision method of human body tumble determination module, report of falling
Police notifies user by call voice.
Human body tumble decision maker 10 in the present embodiment is placed horizontally at sole, and position is fixed, and will not be walked about with human body
Change home position.For the behavior of normal ambulation, the acceleration information in z-axis direction only need to be analyzed.Sentence carrying out tumble
When disconnected, the data variation of x, y, z direction of principal axis is analyzed respectively, it is more directly, also simpler.Draw human body in tumble according to experimental model
Afterwards, while body contact ground, both feet can change with the angle on ground, more than it is normal walk, run, the behavior such as jump
When the sole and ground angle that is formed, and have phenomenon of soaring in short-term, be based on both tumble features, comprehensive tumble process
In each axial acceleration value change and calculating carries out tumble judgement.
In order to verify the accuracy of human body tumble decision method, and old man is not allowed to participate in but invite for security consideration
10 young men carry out simulations and fall down and (completed on mat).The tumble mode of experiment is divided into：Forward/backward is fallen and not put down
Lie, forward/backward is lain low after falling, left/right side is fallen.Devised according to this several tumble mode a set of as shown in table 1
Action.The experimenter tested each time therefrom selects some and acts and combine combination complete set of really falling at random
Experiment is acted.System carries out the collection of sample with 25Hz sample frequency, and is carried out by the algorithm of design at the analysis of data
Reason.Experimenter randomly selects combination of actions from above-mentioned action and tested, and every experimenter need to carry out 5 groups of experiments, 10
Experimenter need to complete 50 groups of experiments altogether.Experiment statisticses result is as shown in table 1.
Table 1
Understand that designed fall detection method has higher accuracy rate by experimental data, the overwhelming majority can be differentiated
Tumble event, but fallen for slow paralysis, or with the presence of the certain rate of false alarm of half situation about falling of rest.
Claims (9)
1. a kind of human body tumble decision method, its specific steps include：
(1) acceleration in the x-axis of human body, y-axis, z-axis direction is acquired, and respectively set x-axis, y-axis, z-axis direction plus
Threshold speed；
(2) when collecting x-axis, the acceleration in y-axis direction is uprushed, and when exceeding corresponding acceleration rate threshold respectively, to z-axis direction
Acceleration and the acceleration rate threshold in z-axis direction be compared；
(3) when the acceleration in z-axis direction is less than the acceleration rate threshold in z-axis direction, it is determined as tumble behavior.
2. a kind of human body tumble decision method according to claim 1, it is characterised in that：Also fall including step (4)
Backward sends tumble alarm signal and notifies guardian in time after being.
3. a kind of human body tumble decision method according to claim 1, it is characterised in that：The acceleration of collection in step (1)
Degree carries out data filtering.
4. a kind of human body tumble decision method according to claim 3, it is characterised in that：Data filtering is filtered using Kalman
Wave method.
5. a kind of human body tumble decision maker, is horizontally mounted and seals inside plant sole, including housing, it is characterised in that：It is described
Circuit board, charge coil, chargeable lithium cell are installed in housing, spacer is provided between the charge coil and circuit board,
The chargeable lithium cell is connected with circuit board, and human body tumble determination module is integrated with the circuit board, and the human body is fallen
Determination module is used to compare to determine whether to exist tumble behavior according to 3-axis acceleration and predetermined acceleration threshold value.
6. a kind of human body tumble decision method according to claim 5, it is characterised in that：The human body tumble determination module
Including primary processor and coprocessor, the 3-axis acceleration sensor for gathering 3-axis acceleration is connected with coprocessor,
The coprocessor is connected with primary processor, and the eSIM that guardian is notified for call voice is connected with the primary processor
Card.
7. a kind of human body tumble decision method according to claim 5, it is characterised in that：It is also connected with the coprocessor
There are bluetooth 2.4G antennas.
8. a kind of human body tumble decision method according to one of claim 5-7, it is characterised in that：On the primary processor
It is also associated with GSM antenna, gps antenna, WiFi antennas, Flash modules.
9. a kind of human body tumble decision method according to claim 8, it is characterised in that：It is also connected with the primary processor
There is alarm module.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201710417383.6A CN107146378A (en) | 2017-06-06 | 2017-06-06 | A kind of human body tumble decision method and device |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710417383.6A CN107146378A (en) | 2017-06-06 | 2017-06-06 | A kind of human body tumble decision method and device |
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ID=59780616
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| CN201710417383.6A Pending CN107146378A (en) | 2017-06-06 | 2017-06-06 | A kind of human body tumble decision method and device |
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Cited By (5)
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| CN108777056A (en) * | 2018-06-15 | 2018-11-09 | 深圳市靓工创新应用科技有限公司 | voice alarm method, device, system and computer readable storage medium |
| CN109686051A (en) * | 2018-12-18 | 2019-04-26 | 广东工业大学 | A kind of determination method, device, equipment and the medium of target object tumble behavior |
| CN109866218A (en) * | 2017-12-01 | 2019-06-11 | 优必选教育（深圳）有限公司 | Standing control method and device are fallen down by robot |
| CN109920209A (en) * | 2019-02-22 | 2019-06-21 | 浙江水利水电学院 | Circuit is called for help in tumble based on the narrowband eMTC Internet of Things |
| CN110638459A (en) * | 2019-09-03 | 2020-01-03 | 杭州雄芯物联科技有限公司 | Human motion falling detection device and method based on acceleration sensor |
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| CN110638459A (en) * | 2019-09-03 | 2020-01-03 | 杭州雄芯物联科技有限公司 | Human motion falling detection device and method based on acceleration sensor |
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