CN107224359A - The wheelchair automatically controlled - Google Patents
The wheelchair automatically controlled Download PDFInfo
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- CN107224359A CN107224359A CN201710593585.6A CN201710593585A CN107224359A CN 107224359 A CN107224359 A CN 107224359A CN 201710593585 A CN201710593585 A CN 201710593585A CN 107224359 A CN107224359 A CN 107224359A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G5/00—Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G5/00—Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs
- A61G5/10—Parts, details or accessories
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2200/00—Information related to the kind of patient or his position
- A61G2200/10—Type of patient
- A61G2200/20—Type of patient with asymmetric abilities, e.g. hemiplegic or missing a limb
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2203/00—General characteristics of devices
- A61G2203/10—General characteristics of devices characterised by specific control means, e.g. for adjustment or steering
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2203/00—General characteristics of devices
- A61G2203/10—General characteristics of devices characterised by specific control means, e.g. for adjustment or steering
- A61G2203/18—General characteristics of devices characterised by specific control means, e.g. for adjustment or steering by patient's head, eyes, facial muscles or voice
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2203/00—General characteristics of devices
- A61G2203/30—General characteristics of devices characterised by sensor means
- A61G2203/42—General characteristics of devices characterised by sensor means for inclination
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2203/00—General characteristics of devices
- A61G2203/70—General characteristics of devices with special adaptations, e.g. for safety or comfort
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- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Image Processing (AREA)
Abstract
The present invention relates to a kind of wheelchair automatically controlled, the wheelchair installs such control mode switch system, and the system includes：Accelerograph, is arranged on wheelchair, is detected for the acceleration magnitude to wheelchair, and when the acceleration magnitude of wheelchair is more than predetermined acceleration threshold value, sends acceleration pre-warning signal；Drift angle detection device, is arranged on wheelchair, is detected for the drift angle value to wheelchair, and when the drift angle value of wheelchair is more than default drift angle threshold value, sends drift angle pre-warning signal；ARM11 processing equipments, for when receiving the acceleration pre-warning signal and receiving the drift angle pre-warning signal, sending and falling down alarm signal；Image capture device, for carrying out high-definition image data acquisition to wheelchair user, to obtain high definition target image；Wherein, the switching to the control model of wheelchair is realized in output of the ARM11 processing equipments based on described image collecting device.
Description
Technical field
The present invention relates to automation field, more particularly to a kind of wheelchair automatically controlled.
Background technology
Selection wheelchair should be noted that problems with：
(1) seat width：Measurement is when sitting down between two sterns or the distance between two strands, and both sides respectively have after adding 5cm to sit down
2.5cm space.Seat is too narrow, and the relatively difficult buttocks of wheelchair and thigh tissue are oppressed up and down；Seat is too wide, is difficult to sit
Surely, wheelchair is manipulated inconvenient, double limb fatiguabilities, turnover gate is also had any problem.
(2) seat length：Buttocks subtracts measurement result to the horizontal range between shank gastrocnemius after when measurement is sat down
6.5cm.If seat is too short, body weight mainly will fall on ischium, easily cause local be easily pressurized excessively；Can Ya Po popliteal if seat is oversize
The local blood circulation of nest portion influence, and easily stimulate portion's skin.It is shorter to thigh or have hip, the patient of knee flexion contrature, then
It is preferable using short seat.
(3) seat height：Measurement heel when sitting down (or heel) is Zhi the distance of popliteal nest, then add 4cm, when placing pedal,
Plate face is at least liftoff 5cm.Seat is too high, and wheelchair can not enter by table；Seat is too low, then to bear weight excessive for ischium.
(4) cushion is in order to comfortable and prevent that on bedsore, the chair of wheelchair cushion should be put.Common cushion has foam rubber pad
(5~10cm is thick) or gel mat.To prevent seat sink from can transfer the thick glued boards of a 0.6cm in cushion.
(5) back height：The chair back is higher, more stable, and the chair back is lower, and the activity of upper body and upper limbs is bigger.The low chair back：Survey
Sitting face is measured to the distance (arm or two-arm are flattened forward) of armpit, this result is subtracted into 10cm.The high chair back：Measure sitting face to shoulder or
The actual height of rear pillow part.
(6) handrail height：When sitting down, upper arm is vertical, and forearm is lain against on handrail, the height of measurement seat to forearm lower edge,
Plus 2.5cm.Appropriate handrail height helps to maintain correct body gesture and balance, and upper limbs can be made to be placed on comfortable position
Put.Handrail is too high, and upper arm is forced upper lift, susceptible fatigue.Handrail is too low, then balance could be maintained by needing to reach forward, not only
Easily fatigue, can also influence breathing.
(7) other auxiliary members of wheelchair：Be in order to meet particular patients ' the need for and design, such as increase handle rubbing surface, car casket
Extension, vibration abatement, handrail installs fupport arm, or facilitate patient to have a meal, the wheelchair table that writes etc..
Wheelchair of the prior art still lacks effective detection in fall detection and extremity disabled personses control aspect and located
Reason pattern, causes the intelligent level of wheelchair not high, it is impossible to higher level service is provided for extremity disabled personses.
The content of the invention
In order to solve the above problems, the invention provides a kind of wheelchair automatically controlled, wheelchair can be detected in time and fallen
The occurrence of, meanwhile, it is determined that and when receiving upper limbs deleted signal, be switched to lower limb controlling pattern, Voice command mould
Formula or brain wave control model, it is determined that and when receiving lower limb deleted signal, be switched to upper limbs control model, Voice command mould
Formula, brain wave control model or touch-screen control model.
According to an aspect of the present invention there is provided a kind of wheelchair automatically controlled, the wheelchair installs such control model
Switching system, the system includes：
Accelerograph, is arranged on wheelchair, is detected for the acceleration magnitude to wheelchair, and when the acceleration of wheelchair
When angle value is more than predetermined acceleration threshold value, acceleration pre-warning signal is sent, when the acceleration magnitude of wheelchair is less than or equal to default acceleration
When spending threshold value, acceleration normal signal is sent；
Drift angle detection device, is arranged on wheelchair, is detected for the drift angle value to wheelchair, and when the drift angle of wheelchair is worth
During more than default drift angle threshold value, drift angle pre-warning signal is sent, when the drift angle value of wheelchair is less than or equal to default drift angle threshold value, is sent
Drift angle normal signal；
ARM11 processing equipments, are connected with the accelerograph and the drift angle detection device respectively, for receiving
To the acceleration pre-warning signal and when receiving the drift angle pre-warning signal, send and fall down alarm signal；
Image capture device, for carrying out high-definition image data acquisition to wheelchair user, to obtain high definition target image；
Wherein, the control model to wheelchair is realized in output of the ARM11 processing equipments based on described image collecting device
Switching.
More specifically, in the wheelchair automatically controlled：
Described image collecting device is arranged on the cross bar of wheelchair front end, for carrying out high-definition image data to wheelchair user
Collection, to obtain high definition target image；
Wherein, the resolution ratio of the high definition target image is according to ambient brightness adaptive change, and ambient brightness is lower, described
The resolution ratio of high definition target image is higher.
More specifically, in the wheelchair automatically controlled：
The ARM11 processing equipments are additionally operable to receiving the acceleration normal signal or to receive the drift angle normal
During signal, send no personnel and fall down signal.
More specifically, in the wheelchair automatically controlled：
The control model of the wheelchair includes Voice command pattern, upper limbs control model, lower limb controlling pattern, touch-screen control
Molding formula and brain wave control model；
Wherein, the control model to wheelchair is realized in output of the ARM11 processing equipments based on described image collecting device
Switching include：Output of the ARM11 processing equipments based on described image collecting device is realized in Voice command pattern, upper limbs
Mutual switching between control model, lower limb controlling pattern, touch-screen control model and brain wave control model.
More specifically, in the wheelchair automatically controlled, the system also includes：
SD storage devices, for prestoring the crucial dot pattern of the crucial dot pattern of N number of benchmark arm and M benchmark leg,
The crucial dot pattern of the N number of benchmark arm is is shot only including correspondingly of obtaining respectively to N number of arm key point in advance
The image of arm key point, the crucial dot pattern in the M benchmark leg is that M benchmark leg key point is clapped respectively in advance
That takes the photograph and obtain only includes the image of correspondence leg key point；Wherein, N number of arm key point and M leg key point are from human body
Extracted at human trunk model, the Human torso is to set up to form based on human skeleton model and human synovial model；
Dimension normalization equipment, is connected with described image collecting device, for receiving the high definition target image, to described
High definition target image carries out dimension normalization processing to obtain normalized image；
Noise complexity detection device, is connected with the dimension normalization equipment, right for receiving the normalized image
The normalized image carries out the detection of noise complexity to determine simultaneously output image noise complexity；
Image block equipment, is connected with the noise complexity detection device, for receiving described image noise complexity
With the normalized image, and based on described image noise complexity to the normalized image carry out piecemeal processing it is many to obtain
Individual image block, wherein, described image noise complexity is higher, and the image that piecemeal processing is obtained is carried out to the normalized image
The quantity of block is more；
Combined filter equipment, is connected with described image piecemeal equipment, for receiving the multiple image block, to each figure
As block performs following handle：Noise type analysis is carried out to each image block to obtain main noise type, based on mainly making an uproar
Sound type determines that corresponding types wave filter is filtered processing to image block to obtain filter block；The combined filter equipment will also
All filter blocks are combined to obtain and export combined filter image；
Limbs detection device, is connected with SD storage devices and combined filter equipment respectively, in the combined filter figure
Search and the object of each benchmark arm key point pattern match as in, if correspondence benchmark arm key point pattern match
Object search is arrived, it is determined that there is corresponding arm key point, otherwise determines that correspondence arm key point is not present, at described group
Search and the object of each benchmark leg key point pattern match in filtering image are closed, if the crucial point diagram in correspondence benchmark leg
The object search of case matching is arrived, it is determined that there is corresponding leg key point, is otherwise determined that correspondence leg key point is not present, is also used
In the crucial dot pattern of the crucial dot pattern of N number of benchmark arm and M benchmark leg respectively it is corresponding search for all terminate after, when it is determined that
When there is more than P correspondence arm key point, send upper limbs and there is signal, when it is determined that there is less than P correspondence arm key point
When, send upper limbs deleted signal, when it is determined that exist more than Q correspondence leg key point when, send lower limb and there is signal, when it is determined that
During in the presence of less than Q correspondence leg key point, lower limb deleted signal is sent, wherein, P is less than N and is less than M more than 0, Q and is more than
0；
Wherein, output of the ARM11 processing equipments based on described image collecting device realize Voice command pattern, on
Mutual switching between limb control model, lower limb controlling pattern, touch-screen control model and brain wave control model includes：Institute
ARM11 processing equipments are stated when receiving upper limbs deleted signal, lower limb controlling pattern, Voice command pattern or brain wave is switched to
Control model, when receiving lower limb deleted signal, is switched to upper limbs control model, Voice command pattern, brain wave control mould
Formula or touch-screen control model.
More specifically, in the wheelchair automatically controlled：The ARM11 processing equipments are receiving upper limbs deleted signal
When, it is switched to lower limb controlling pattern, Voice command pattern or brain wave control model according to priority selection from high to low.
More specifically, in the wheelchair automatically controlled：The ARM11 processing equipments are receiving lower limb deleted signal
When, according to from high to low priority selection be switched to upper limbs control model, Voice command pattern, brain wave control model or
Touch-screen control model.
More specifically, in the wheelchair automatically controlled：The ARM11 processing equipments are receiving upper limbs deleted signal
And when receiving lower limb deleted signal, Voice command pattern, brain wave control are switched to according to priority selection from high to low
Molding formula or touch-screen control model.
According to another aspect of the present invention, a kind of wheelchair control mode switching method is additionally provided, methods described includes making
With the wheelchair automatically controlled described above with based on carrying out the high definition target image that high-definition image data acquisition is arrived to wheelchair user
Realize the switching to the control model of wheelchair.
Brief description of the drawings
Embodiment of the present invention is described below with reference to accompanying drawing, wherein：
Fig. 1 is the block diagram of the wheelchair automatically controlled according to embodiment of the present invention.
Reference：1 accelerograph；2 drift angle detection devices；3ARM11 processing equipments；4 image capture devices
Embodiment
The embodiment to the wheelchair automatically controlled of the present invention is described in detail below with reference to accompanying drawings.
Most important Consideration is the size of wheelchair during from wheelchair.Take wheelchair person and bear the main portions of body weight and be
Around buttocks ischial tuberosity, around femur, around women's headgear nest and around shoulder blade.The size of wheelchair, particularly seat width, the depth
Whether the distance with height and pedal to the seat cushion of backrest is suitable, can all make occupant about putting forth effort the blood circulation at position
It is impacted, concurrent rawhide skin abrasion, or even pressure sore.In addition, it is also contemplated that the weight of the security of patient, operational capacity, wheelchair,
The problems such as place to use, outward appearance.
Current wheelchair intelligent level is not high, still lacks effective processor in terms of detection and patient service is fallen down
System.In order to overcome above-mentioned deficiency, the present invention has built a kind of wheelchair automatically controlled, for solving above-mentioned technical problem.
A kind of wheelchair automatically controlled, the wheelchair installs control mode switch system.Fig. 1 is according to embodiment of the present invention
The block diagram of the control mode switch system shown, the system includes：
Accelerograph, is arranged on wheelchair, is detected for the acceleration magnitude to wheelchair, and when the acceleration of wheelchair
When angle value is more than predetermined acceleration threshold value, acceleration pre-warning signal is sent, when the acceleration magnitude of wheelchair is less than or equal to default acceleration
When spending threshold value, acceleration normal signal is sent；
Drift angle detection device, is arranged on wheelchair, is detected for the drift angle value to wheelchair, and when the drift angle of wheelchair is worth
During more than default drift angle threshold value, drift angle pre-warning signal is sent, when the drift angle value of wheelchair is less than or equal to default drift angle threshold value, is sent
Drift angle normal signal；
ARM11 processing equipments, are connected with the accelerograph and the drift angle detection device respectively, for receiving
To the acceleration pre-warning signal and when receiving the drift angle pre-warning signal, send and fall down alarm signal；
Image capture device, for carrying out high-definition image data acquisition to wheelchair user, to obtain high definition target image；
Wherein, the control model to wheelchair is realized in output of the ARM11 processing equipments based on described image collecting device
Switching.
Then, continue that the concrete structure of the wheelchair automatically controlled of the present invention is further detailed.
In the wheelchair automatically controlled：
Described image collecting device is arranged on the cross bar of wheelchair front end, for carrying out high-definition image data to wheelchair user
Collection, to obtain high definition target image；
Wherein, the resolution ratio of the high definition target image is according to ambient brightness adaptive change, and ambient brightness is lower, described
The resolution ratio of high definition target image is higher.
In the wheelchair automatically controlled：
The ARM11 processing equipments are additionally operable to receiving the acceleration normal signal or to receive the drift angle normal
During signal, send no personnel and fall down signal.
In the wheelchair automatically controlled：
The control model of the wheelchair includes Voice command pattern, upper limbs control model, lower limb controlling pattern, touch-screen control
Molding formula and brain wave control model；
Wherein, the control model to wheelchair is realized in output of the ARM11 processing equipments based on described image collecting device
Switching include：Output of the ARM11 processing equipments based on described image collecting device is realized in Voice command pattern, upper limbs
Mutual switching between control model, lower limb controlling pattern, touch-screen control model and brain wave control model.
It can also include in the wheelchair automatically controlled：
SD storage devices, for prestoring the crucial dot pattern of the crucial dot pattern of N number of benchmark arm and M benchmark leg,
The crucial dot pattern of the N number of benchmark arm is is shot only including correspondingly of obtaining respectively to N number of arm key point in advance
The image of arm key point, the crucial dot pattern in the M benchmark leg is that M benchmark leg key point is clapped respectively in advance
That takes the photograph and obtain only includes the image of correspondence leg key point；Wherein, N number of arm key point and M leg key point are from human body
Extracted at human trunk model, the Human torso is to set up to form based on human skeleton model and human synovial model；
Dimension normalization equipment, is connected with described image collecting device, for receiving the high definition target image, to described
High definition target image carries out dimension normalization processing to obtain normalized image；
Noise complexity detection device, is connected with the dimension normalization equipment, right for receiving the normalized image
The normalized image carries out the detection of noise complexity to determine simultaneously output image noise complexity；
Image block equipment, is connected with the noise complexity detection device, for receiving described image noise complexity
With the normalized image, and based on described image noise complexity to the normalized image carry out piecemeal processing it is many to obtain
Individual image block, wherein, described image noise complexity is higher, and the image that piecemeal processing is obtained is carried out to the normalized image
The quantity of block is more；
Combined filter equipment, is connected with described image piecemeal equipment, for receiving the multiple image block, to each figure
As block performs following handle：Noise type analysis is carried out to each image block to obtain main noise type, based on mainly making an uproar
Sound type determines that corresponding types wave filter is filtered processing to image block to obtain filter block；The combined filter equipment will also
All filter blocks are combined to obtain and export combined filter image；
Limbs detection device, is connected with SD storage devices and combined filter equipment respectively, in the combined filter figure
Search and the object of each benchmark arm key point pattern match as in, if correspondence benchmark arm key point pattern match
Object search is arrived, it is determined that there is corresponding arm key point, otherwise determines that correspondence arm key point is not present, at described group
Search and the object of each benchmark leg key point pattern match in filtering image are closed, if the crucial point diagram in correspondence benchmark leg
The object search of case matching is arrived, it is determined that there is corresponding leg key point, is otherwise determined that correspondence leg key point is not present, is also used
In the crucial dot pattern of the crucial dot pattern of N number of benchmark arm and M benchmark leg respectively it is corresponding search for all terminate after, when it is determined that
When there is more than P correspondence arm key point, send upper limbs and there is signal, when it is determined that there is less than P correspondence arm key point
When, send upper limbs deleted signal, when it is determined that exist more than Q correspondence leg key point when, send lower limb and there is signal, when it is determined that
During in the presence of less than Q correspondence leg key point, lower limb deleted signal is sent, wherein, P is less than N and is less than M more than 0, Q and is more than
0；
Wherein, output of the ARM11 processing equipments based on described image collecting device realize Voice command pattern, on
Mutual switching between limb control model, lower limb controlling pattern, touch-screen control model and brain wave control model includes：Institute
ARM11 processing equipments are stated when receiving upper limbs deleted signal, lower limb controlling pattern, Voice command pattern or brain wave is switched to
Control model, when receiving lower limb deleted signal, is switched to upper limbs control model, Voice command pattern, brain wave control mould
Formula or touch-screen control model.
In the wheelchair automatically controlled：The ARM11 processing equipments are when receiving upper limbs deleted signal, according to from height
Lower limb controlling pattern, Voice command pattern or brain wave control model are switched to low priority selection.
In the wheelchair automatically controlled：The ARM11 processing equipments are when receiving lower limb deleted signal, according to from height
Upper limbs control model, Voice command pattern, brain wave control model or touch-screen control are switched to low priority selection
Pattern.
In the wheelchair automatically controlled：The ARM11 processing equipments are in the case where receiving upper limbs deleted signal and receiving
During deficiency of skeletal limb signal, it is switched to Voice command pattern, brain wave control model according to priority selection from high to low or touches
Touch screen control model.
Meanwhile, in order to overcome above-mentioned deficiency, the present invention has also built a kind of wheelchair control mode switching method, methods described
Including the use of the wheelchair automatically controlled described above with based on the high definition mesh arrived to wheelchair user progress high-definition image data acquisition
Logo image realizes the switching to the control model of wheelchair.
In addition, image filtering, i.e., press down under conditions of image detail feature is retained as far as possible to the noise of target image
System, is indispensable operation in image preprocessing, and the quality of its treatment effect will directly influence successive image processing and divide
The validity and reliability of analysis.
Due to the imperfection of imaging system, transmission medium and recording equipment etc., digital picture is in its formation, transmission log mistake
Often polluted in journey by a variety of noises.In addition, some links in image procossing work as the picture object of input and not as pre-
Also noise can be introduced when thinking in result images.These noises often show as one on image and cause the isolated of stronger visual effect
Pixel or block of pixels.Typically, noise signal it is uncorrelated to the object to be studied it occur with useless message form, upset figure
The observable information of picture.For data image signal, psophometer is either large or small extreme value, and these extreme values are acted on by plus-minus
On the true gray value of image pixel, the interference of bright, dim spot is caused to image, picture quality is greatly reduced, influence image restoration,
The progress of the follow-up work such as segmentation, feature extraction, image recognition.A kind of effective wave filter for suppressing noise is constructed to must take into consideration
Two basic problems：The noise in target and background can effectively be removed；Meanwhile, can protect well image object shape,
Size and specific geometry and topological features.
One kind in conventional image filtering pattern is, nonlinear filter, it is, in general, that when signal spectrum and noise frequency
Such as the noise as caused by mission nonlinear or there is non-gaussian and make an uproar during spectrum aliasing or when containing nonadditivity noise in signal
Sound etc.), the conversion of traditional linear filter technology, such as Fourier, while noise is filtered out, always blurred picture is thin in some way
Section (such as edge) and then the extraction property reduction for causing the positioning precision and feature as linear character.And nonlinear filter is
Based on a kind of Nonlinear Mapping relation to input signal, often a certain specific noise approx can be mapped as zero and retained
Signal wants feature, thus it can overcome the weak point of linear filter to a certain extent.
Using the wheelchair automatically controlled of the present invention, for wheelchair control mechanism backward technology problem in the prior art,
Fall down the detection and alarm of state to wheelchair with reference to completion by introducing drift angle detector and accelerograph, it is more crucial
It is that, by the image recognition mechanism targetedly set up based on Human torso, the disabled situation to the patient on wheelchair is entered
Row identification, important reference data is provided for the switching of wheelchair control pattern.
Although it is understood that the present invention is disclosed as above with preferred embodiment, but above-described embodiment and being not used to
Limit the present invention.For any those skilled in the art, without departing from the scope of the technical proposal of the invention,
Many possible variations and modification are all made to technical solution of the present invention using the technology contents of the disclosure above, or are revised as
With the equivalent embodiment of change.Therefore, every content without departing from technical solution of the present invention, the technical spirit pair according to the present invention
Any simple modifications, equivalents, and modifications made for any of the above embodiments, still fall within the scope of technical solution of the present invention protection
It is interior.
Claims (9)
1. a kind of wheelchair automatically controlled, the wheelchair installs such control mode switch system, the system includes：
Accelerograph, is arranged on wheelchair, is detected for the acceleration magnitude to wheelchair, and when the acceleration magnitude of wheelchair
During more than predetermined acceleration threshold value, acceleration pre-warning signal is sent, when the acceleration magnitude of wheelchair is less than or equal to predetermined acceleration threshold
During value, acceleration normal signal is sent；
Drift angle detection device, is arranged on wheelchair, is detected for the drift angle value to wheelchair, and when the drift angle value of wheelchair is more than
During default drift angle threshold value, drift angle pre-warning signal is sent, when the drift angle value of wheelchair is less than or equal to default drift angle threshold value, drift angle is sent
Normal signal；
ARM11 processing equipments, are connected with the accelerograph and the drift angle detection device, for receiving respectively
When stating acceleration pre-warning signal and receiving the drift angle pre-warning signal, send and fall down alarm signal；
Image capture device, for carrying out high-definition image data acquisition to wheelchair user, to obtain high definition target image；
Wherein, cutting to the control model of wheelchair is realized in output of the ARM11 processing equipments based on described image collecting device
Change.
2. the wheelchair automatically controlled as claimed in claim 1, it is characterised in that：
Described image collecting device is arranged on the cross bar of wheelchair front end, is adopted for carrying out high-definition image data to wheelchair user
Collection, to obtain high definition target image；
Wherein, the resolution ratio of the high definition target image is according to ambient brightness adaptive change, and ambient brightness is lower, the high definition
The resolution ratio of target image is higher.
3. the wheelchair automatically controlled as claimed in claim 2, it is characterised in that：
The ARM11 processing equipments are additionally operable to receiving the acceleration normal signal or receiving the drift angle normal signal
When, send no personnel and fall down signal.
4. the wheelchair automatically controlled as claimed in claim 3, it is characterised in that：
The control model of the wheelchair includes Voice command pattern, upper limbs control model, lower limb controlling pattern, touch-screen control mould
Formula and brain wave control model；
Wherein, cutting to the control model of wheelchair is realized in output of the ARM11 processing equipments based on described image collecting device
Change including：Output of the ARM11 processing equipments based on described image collecting device is realized to be controlled in Voice command pattern, upper limbs
Mutual switching between pattern, lower limb controlling pattern, touch-screen control model and brain wave control model.
5. the wheelchair automatically controlled as claimed in claim 4, it is characterised in that the system also includes：
SD storage devices, for prestoring the crucial dot pattern of the crucial dot pattern of N number of benchmark arm and M benchmark leg, the N
The crucial dot pattern of individual benchmark arm closes to be shot the correspondence arm that only includes obtained respectively to N number of arm key point in advance
The image of key point, the crucial dot pattern in the M benchmark leg is obtained to be shot respectively to M benchmark leg key point in advance
What is obtained only includes the image of correspondence leg key point；Wherein, N number of arm key point and M leg key point are from trunk mould
Extracted at type, the Human torso is to set up to form based on human skeleton model and human synovial model；
Dimension normalization equipment, is connected with described image collecting device, for receiving the high definition target image, to the high definition
Target image carries out dimension normalization processing to obtain normalized image；
Noise complexity detection device, is connected with the dimension normalization equipment, for receiving the normalized image, to described
Normalized image carries out the detection of noise complexity to determine simultaneously output image noise complexity；
Image block equipment, is connected with the noise complexity detection device, for receiving described image noise complexity and institute
Normalized image is stated, and carries out piecemeal processing to the normalized image to obtain multiple figures based on described image noise complexity
As block, wherein, described image noise complexity is higher, and the image block that piecemeal processing is obtained is carried out to the normalized image
Quantity is more；
Combined filter equipment, is connected with described image piecemeal equipment, for receiving the multiple image block, to each image block
Perform following handle：Noise type analysis is carried out to each image block to obtain main noise type, based on main noise class
Type determines that corresponding types wave filter is filtered processing to image block to obtain filter block；The combined filter equipment will also be all
Filter block is combined to obtain and export combined filter image；
Limbs detection device, is connected with SD storage devices and combined filter equipment respectively, in the combined filter image
Search and the object of each benchmark arm key point pattern match, if the object of correspondence benchmark arm key point pattern match
Search, it is determined that there is corresponding arm key point, otherwise determine that correspondence arm key point is not present, in the combination filter
Search and the object of each benchmark leg key point pattern match in ripple image, if the crucial dot pattern in correspondence benchmark leg
The object search matched somebody with somebody is arrived, it is determined that there is corresponding leg key point, is otherwise determined that correspondence leg key point is not present, is additionally operable to
The crucial dot pattern of the crucial dot pattern of N number of benchmark arm and M benchmark leg respectively it is corresponding search for all terminate after, when it is determined that in the presence of
During more than P correspondence arm key point, send upper limbs and there is signal, when it is determined that there is less than P correspondence arm key point, hair
Go out upper limbs deleted signal, when it is determined that exist more than Q correspondence leg key point when, send lower limb and there is signal, when it is determined that in the presence of
During less than Q correspondence leg key point, lower limb deleted signal is sent, wherein, P is less than N and is less than M and more than 0 more than 0, Q；
Wherein, output of the ARM11 processing equipments based on described image collecting device is realized in Voice command pattern, upper limbs control
Mutual switching between molding formula, lower limb controlling pattern, touch-screen control model and brain wave control model includes：It is described
ARM11 processing equipments are switched to lower limb controlling pattern, Voice command pattern or brain wave control when receiving upper limbs deleted signal
Molding formula, when receiving lower limb deleted signal, is switched to upper limbs control model, Voice command pattern, brain wave control model
Or touch-screen control model.
6. the wheelchair automatically controlled as claimed in claim 5, it is characterised in that：
The ARM11 processing equipments are switched to when receiving upper limbs deleted signal according to priority selection from high to low
Lower limb controlling pattern, Voice command pattern or brain wave control model.
7. the wheelchair automatically controlled as claimed in claim 5, it is characterised in that：
The ARM11 processing equipments are switched to when receiving lower limb deleted signal according to priority selection from high to low
Upper limbs control model, Voice command pattern, brain wave control model or touch-screen control model.
8. the wheelchair automatically controlled as claimed in claim 5, it is characterised in that：
The ARM11 processing equipments are when receiving upper limbs deleted signal and receiving lower limb deleted signal, according to from high to low
Priority selection be switched to Voice command pattern, brain wave control model or touch-screen control model.
9. a kind of wheelchair control mode switching method, methods described is including the use of the automatic control as described in claim 1-8 is any
The wheelchair of system is with based on the control realized to the high definition target image that wheelchair user progress high-definition image data acquisition is arrived to wheelchair
The switching of pattern.
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| CN201710593585.6A CN107224359A (en) | 2017-07-20 | 2017-07-20 | The wheelchair automatically controlled |
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| CN201710593585.6A CN107224359A (en) | 2017-07-20 | 2017-07-20 | The wheelchair automatically controlled |
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Family
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109363401A (en) * | 2018-11-16 | 2019-02-22 | 苏州小点智能家居有限公司 | A kind of intelligent shatter-resistant chair with sitting posture prompting function |
| CN110162598A (en) * | 2019-04-12 | 2019-08-23 | 北京搜狗科技发展有限公司 | A kind of data processing method and device, a kind of device for data processing |
| CN110782413A (en) * | 2019-10-30 | 2020-02-11 | 北京金山云网络技术有限公司 | Image processing method, device, equipment and storage medium |
| CN110796624A (en) * | 2019-10-31 | 2020-02-14 | 北京金山云网络技术有限公司 | Image generation method and device and electronic equipment |
| CN111667782A (en) * | 2019-03-06 | 2020-09-15 | 丰田自动车株式会社 | Moving body and moving system |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0869549A (en) * | 1994-08-29 | 1996-03-12 | Nippon Signal Co Ltd:The | Automatic ticket examining machine |
| JPH11169407A (en) * | 1997-12-15 | 1999-06-29 | Kiyomi Tameshige | Emergency alarm for wheelchair |
| CN202096374U (en) * | 2010-12-15 | 2012-01-04 | 南开大学 | Intelligent wheelchair based on eye electric signals and head movement signals |
| CN202126600U (en) * | 2011-05-26 | 2012-01-25 | 江苏科技大学 | Intelligent voice drive control device of wheel chair |
| CN202136503U (en) * | 2011-07-01 | 2012-02-08 | 山东科技大学 | Voice controlled obstacle-avoidance wheelchair |
| CN102499828A (en) * | 2011-11-09 | 2012-06-20 | 北京化工大学 | Old and disabled-assistant bed chair integrated robot |
| CN202342324U (en) * | 2011-11-23 | 2012-07-25 | 浙江大学 | Intelligent power-assisted wheel chair |
| CN203291128U (en) * | 2013-05-06 | 2013-11-20 | 浙江大学 | Intelligent obstacle avoiding wheelchair based on bioelectrical multi-modal control |
| CN104887414A (en) * | 2015-06-03 | 2015-09-09 | 北京理工大学 | Omni-directionally movable wheelchair with gravity center adjusting function |
| CN106038149A (en) * | 2016-05-24 | 2016-10-26 | 王翠平 | Special bed for department of gynecology and obstetrics |
| CN106176081A (en) * | 2016-07-05 | 2016-12-07 | 国家康复辅具研究中心 | A kind of electric wheel-chair vehicle anti-tilting apparatus comprising acceleration transducer and method |
| CN106933157A (en) * | 2017-04-20 | 2017-07-07 | 武汉理工大学 | A kind of wheelchair safety monitoring assembly and monitoring method |
-
2017
- 2017-07-20 CN CN201710593585.6A patent/CN107224359A/en not_active Withdrawn
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0869549A (en) * | 1994-08-29 | 1996-03-12 | Nippon Signal Co Ltd:The | Automatic ticket examining machine |
| JPH11169407A (en) * | 1997-12-15 | 1999-06-29 | Kiyomi Tameshige | Emergency alarm for wheelchair |
| CN202096374U (en) * | 2010-12-15 | 2012-01-04 | 南开大学 | Intelligent wheelchair based on eye electric signals and head movement signals |
| CN202126600U (en) * | 2011-05-26 | 2012-01-25 | 江苏科技大学 | Intelligent voice drive control device of wheel chair |
| CN202136503U (en) * | 2011-07-01 | 2012-02-08 | 山东科技大学 | Voice controlled obstacle-avoidance wheelchair |
| CN102499828A (en) * | 2011-11-09 | 2012-06-20 | 北京化工大学 | Old and disabled-assistant bed chair integrated robot |
| CN202342324U (en) * | 2011-11-23 | 2012-07-25 | 浙江大学 | Intelligent power-assisted wheel chair |
| CN203291128U (en) * | 2013-05-06 | 2013-11-20 | 浙江大学 | Intelligent obstacle avoiding wheelchair based on bioelectrical multi-modal control |
| CN104887414A (en) * | 2015-06-03 | 2015-09-09 | 北京理工大学 | Omni-directionally movable wheelchair with gravity center adjusting function |
| CN106038149A (en) * | 2016-05-24 | 2016-10-26 | 王翠平 | Special bed for department of gynecology and obstetrics |
| CN106176081A (en) * | 2016-07-05 | 2016-12-07 | 国家康复辅具研究中心 | A kind of electric wheel-chair vehicle anti-tilting apparatus comprising acceleration transducer and method |
| CN106933157A (en) * | 2017-04-20 | 2017-07-07 | 武汉理工大学 | A kind of wheelchair safety monitoring assembly and monitoring method |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109363401A (en) * | 2018-11-16 | 2019-02-22 | 苏州小点智能家居有限公司 | A kind of intelligent shatter-resistant chair with sitting posture prompting function |
| CN111667782A (en) * | 2019-03-06 | 2020-09-15 | 丰田自动车株式会社 | Moving body and moving system |
| CN111667782B (en) * | 2019-03-06 | 2022-10-28 | 丰田自动车株式会社 | Mobile body and mobile system |
| CN110162598A (en) * | 2019-04-12 | 2019-08-23 | 北京搜狗科技发展有限公司 | A kind of data processing method and device, a kind of device for data processing |
| CN110782413A (en) * | 2019-10-30 | 2020-02-11 | 北京金山云网络技术有限公司 | Image processing method, device, equipment and storage medium |
| CN110782413B (en) * | 2019-10-30 | 2022-12-06 | 北京金山云网络技术有限公司 | Image processing method, device, equipment and storage medium |
| CN110796624A (en) * | 2019-10-31 | 2020-02-14 | 北京金山云网络技术有限公司 | Image generation method and device and electronic equipment |
| CN110796624B (en) * | 2019-10-31 | 2022-07-05 | 北京金山云网络技术有限公司 | Image generation method and device and electronic equipment |
| US11836898B2 (en) | 2019-10-31 | 2023-12-05 | Beijing Kingsoft Cloud Network Technology Co., Ltd. | Method and apparatus for generating image, and electronic device |
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Application publication date: 20171003 |