CN109657645B - Safety protection mechanism for medical equipment - Google Patents
Safety protection mechanism for medical equipment Download PDFInfo
- Publication number
- CN109657645B CN109657645B CN201910002353.8A CN201910002353A CN109657645B CN 109657645 B CN109657645 B CN 109657645B CN 201910002353 A CN201910002353 A CN 201910002353A CN 109657645 B CN109657645 B CN 109657645B
- Authority
- CN
- China
- Prior art keywords
- image
- particle
- oxygen cylinder
- pattern
- mean value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000007246 mechanism Effects 0.000 title claims abstract description 34
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 69
- 239000001301 oxygen Substances 0.000 claims abstract description 69
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 69
- 238000001514 detection method Methods 0.000 claims abstract description 5
- 239000002245 particle Substances 0.000 claims description 71
- 230000011218 segmentation Effects 0.000 claims description 31
- 238000012545 processing Methods 0.000 claims description 24
- 238000009499 grossing Methods 0.000 claims description 21
- 230000004069 differentiation Effects 0.000 claims description 11
- 238000001914 filtration Methods 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 10
- 238000007405 data analysis Methods 0.000 claims description 9
- 238000000605 extraction Methods 0.000 claims description 9
- 238000003384 imaging method Methods 0.000 claims description 9
- 238000000034 method Methods 0.000 claims description 7
- 238000005259 measurement Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 6
- 210000000746 body region Anatomy 0.000 claims description 4
- 230000037237 body shape Effects 0.000 claims description 4
- 238000003709 image segmentation Methods 0.000 claims description 4
- 238000012935 Averaging Methods 0.000 claims description 3
- 238000012790 confirmation Methods 0.000 claims description 3
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 230000011664 signaling Effects 0.000 claims description 3
- 230000006872 improvement Effects 0.000 claims description 2
- 238000010606 normalization Methods 0.000 claims description 2
- 239000010453 quartz Substances 0.000 claims description 2
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 claims description 2
- 238000011161 development Methods 0.000 abstract description 4
- 230000002265 prevention Effects 0.000 abstract description 2
- 238000013461 design Methods 0.000 description 6
- 239000013256 coordination polymer Substances 0.000 description 5
- 230000018109 developmental process Effects 0.000 description 4
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 201000010099 disease Diseases 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17C—VESSELS FOR CONTAINING OR STORING COMPRESSED, LIQUEFIED OR SOLIDIFIED GASES; FIXED-CAPACITY GAS-HOLDERS; FILLING VESSELS WITH, OR DISCHARGING FROM VESSELS, COMPRESSED, LIQUEFIED, OR SOLIDIFIED GASES
- F17C13/00—Details of vessels or of the filling or discharging of vessels
- F17C13/02—Special adaptations of indicating, measuring, or monitoring equipment
- F17C13/025—Special adaptations of indicating, measuring, or monitoring equipment having the pressure as the parameter
-
- G06T5/70—
-
- G06T5/90—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17C—VESSELS FOR CONTAINING OR STORING COMPRESSED, LIQUEFIED OR SOLIDIFIED GASES; FIXED-CAPACITY GAS-HOLDERS; FILLING VESSELS WITH, OR DISCHARGING FROM VESSELS, COMPRESSED, LIQUEFIED, OR SOLIDIFIED GASES
- F17C2221/00—Handled fluid, in particular type of fluid
- F17C2221/01—Pure fluids
- F17C2221/011—Oxygen
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17C—VESSELS FOR CONTAINING OR STORING COMPRESSED, LIQUEFIED OR SOLIDIFIED GASES; FIXED-CAPACITY GAS-HOLDERS; FILLING VESSELS WITH, OR DISCHARGING FROM VESSELS, COMPRESSED, LIQUEFIED, OR SOLIDIFIED GASES
- F17C2223/00—Handled fluid before transfer, i.e. state of fluid when stored in the vessel or before transfer from the vessel
- F17C2223/01—Handled fluid before transfer, i.e. state of fluid when stored in the vessel or before transfer from the vessel characterised by the phase
- F17C2223/0107—Single phase
- F17C2223/0123—Single phase gaseous, e.g. CNG, GNC
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17C—VESSELS FOR CONTAINING OR STORING COMPRESSED, LIQUEFIED OR SOLIDIFIED GASES; FIXED-CAPACITY GAS-HOLDERS; FILLING VESSELS WITH, OR DISCHARGING FROM VESSELS, COMPRESSED, LIQUEFIED, OR SOLIDIFIED GASES
- F17C2250/00—Accessories; Control means; Indicating, measuring or monitoring of parameters
- F17C2250/07—Actions triggered by measured parameters
- F17C2250/072—Action when predefined value is reached
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17C—VESSELS FOR CONTAINING OR STORING COMPRESSED, LIQUEFIED OR SOLIDIFIED GASES; FIXED-CAPACITY GAS-HOLDERS; FILLING VESSELS WITH, OR DISCHARGING FROM VESSELS, COMPRESSED, LIQUEFIED, OR SOLIDIFIED GASES
- F17C2270/00—Applications
- F17C2270/02—Applications for medical applications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20021—Dividing image into blocks, subimages or windows
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/03—Recognition of patterns in medical or anatomical images
- G06V2201/034—Recognition of patterns in medical or anatomical images of medical instruments
Abstract
The general practitioner is a high-quality primary medical care talent with comprehensive clinical skills and high medical quality after being trained by the general medical profession, has independent working capacity, and provides convenient, cheap, and all-round high-quality services for prevention, treatment, protection and rehabilitation for individuals, families and communities. The development of general medical services, if no active general doctor is on a firm basis, the work will lack vitality and power, the simple special medical service system will cause disorder of medical order, and no country's economy can afford. The invention relates to a safety protection mechanism for medical equipment, which comprises: and the pressure detection equipment is arranged on the oxygen cylinder and used for detecting the real-time pressure in the oxygen cylinder and sending a pressure alarm command when the real-time pressure exceeds the limit, or sending a normal pressure command. By the invention, the medical equipment can be prevented from being used illegally.
Description
Technical Field
The invention relates to the field of medical equipment, in particular to a safety protection mechanism for medical equipment.
Background
The general practitioner is a high-quality primary medical care talent with comprehensive clinical skills and high medical quality after being trained by the general medical profession, has independent working capacity, and provides convenient, cheap, and all-round high-quality services for prevention, treatment, protection and rehabilitation for individuals, families and communities. The development of general medical services, if no active general doctor is on a firm basis, the work will lack vitality and power, the simple special medical service system will cause disorder of medical order, and no country's economy can afford.
The definition of the royal general medical institute in the uk for general doctors is: doctors providing personalized, primary, continuous medical services to individuals and families in homes, clinics, or hospitals. The general practitioner accumulates abundant practical experience due to long-term basic work, knows the mind, interpersonal communication and the coming and going pulse of diseases, and is the expert of primary medical care. General practitioners are not only confronted with ill persons, but also include a large population of healthy people who can use all the resources of the community, such as governments, politics, charities, and corporate groups, living meetings, etc., to address the specific difficulties of the patient. According to the needs of diseases, the patients can be properly transferred to specialized departments or large hospitals for diagnosis and treatment, the relationship between doctors and patients is comprehensively coordinated, and the patients are responsible for the whole course.
Disclosure of Invention
According to an aspect of the present invention, there is provided a medical device safety shield mechanism, the mechanism comprising:
and the pressure detection equipment is arranged on the oxygen cylinder and used for detecting the real-time pressure in the oxygen cylinder and sending a pressure alarm command when the real-time pressure exceeds the limit, or sending a normal pressure command.
More specifically, in the medical device safety protection mechanism, further include:
and the miniature imaging equipment is arranged above the oxygen cylinder and is used for performing imaging operation on the position of the oxygen cylinder so as to obtain an image around the oxygen cylinder.
More specifically, in the medical device safety protection mechanism, further include:
and the image traversing device is connected with the miniature imaging device and is used for receiving the images around the oxygen cylinder, performing non-overlapping traversing on the images around the oxygen cylinder by adopting a smooth window according to the sequence from left to right and from top to bottom to obtain corresponding traversing windows and outputting the traversing windows.
More specifically, in the medical device safety protection mechanism, further include:
the particle acquisition equipment is connected with the image traversal equipment and used for receiving the traversal windows and performing the following particle confirmation actions on the traversal windows: obtaining the mean value of all brightness values of all pixel points in each traversal window to be used as a window mean value, carrying out deviation degree analysis on the window mean value and the overall brightness of the image around the oxygen cylinder, and when the deviation degree exceeds the limit, determining the traversal window to be a particle block;
the image dividing device is connected with the particle collecting device and used for forming a particle pattern in the oxygen cylinder periphery image based on each particle block output by the particle collecting device, and taking the image of the oxygen cylinder periphery image after the particle pattern is stripped as a non-particle pattern;
a differentiation processing device connected to the image dividing device, for receiving the grain pattern and the non-grain pattern, performing a low-pass filtering process on the grain pattern using a preset frequency threshold as a cutoff frequency to obtain a grain low-pass pattern, and further performing a low-pass filtering process on the non-grain pattern using one-half of the preset frequency threshold as the cutoff frequency to obtain a non-grain low-pass pattern, and outputting the grain low-pass pattern and the non-grain low-pass pattern;
the data fitting device is connected with the differentiation treatment device and used for receiving the particle low-pass pattern and the non-particle low-pass pattern and fitting the particle low-pass pattern and the non-particle low-pass pattern to obtain a fitted image corresponding to the image around the oxygen cylinder;
the signal analysis equipment is connected with the data fitting equipment and used for receiving the fitted image, extracting the characteristic quantity related to smoothing processing of the fitted image, inputting the extracted characteristic quantity into a data analysis model consisting of an input layer, an output layer and a plurality of hidden layers and carrying out data analysis on the characteristic quantity input by the input layer by layer, wherein the output layer is connected with the last hidden layer and used for outputting the result of data analysis of the last hidden layer, and the output quantity type of the output layer is a smoothing processing type;
the self-adaptive smoothing equipment is connected with the signal analysis equipment and is used for receiving the smoothing processing type and executing smoothing operation based on the smoothing processing type on the fitting image so as to obtain and output a smoothed image;
the amplitude measuring device is connected with the self-adaptive smoothing device and used for receiving the smoothed image, analyzing the amplitude of the noise in the smoothed image to obtain the maximum amplitude in the smoothed image, and determining the sizes of image segmentation blocks which are in direct proportion to the maximum amplitude based on the maximum amplitude to obtain all segmentation blocks with the same size;
the area selection device is connected with the amplitude measurement device and used for receiving the segmentation blocks with the same size and selecting four segmentation blocks positioned at four corner positions in the smoothed image from the segmentation blocks in the smoothed image as four corner segmentation blocks;
the regional identification equipment is respectively connected with the amplitude measurement equipment and the regional selection equipment and used for receiving the four segmentation blocks, acquiring the red component mean value of each corner segmentation block, calculating the mean value of the four red component mean values of the four corner image regions, outputting the acquired mean value as an integral component mean value, and acquiring the red component mean value of each corner segmentation block comprises: and obtaining each red component value of each pixel point of each corner segmentation block, sequencing each red component value of each pixel point, and taking the red component value of the central serial number as the red component average value of the corner segmentation block.
The invention has at least the following three key points: (1) performing particle analysis on an image to be processed by adopting a traversal window with the size in direct proportion to the signal-to-noise ratio of the image around the oxygen cylinder to obtain particle low-pass patterns and non-particle low-pass patterns, and performing different differentiation processing on the particle low-pass patterns and the non-particle low-pass patterns to obtain a filtered image with a clearer filtering effect; (2) determining the sizes of image segmentation blocks which are in direct proportion to the maximum amplitude of the noise in the image to obtain the segmentation blocks with the same size; (3) in order to save the amount of operation of image processing, the four red component mean values of the four corner image areas of the image are subjected to averaging calculation to obtain the red component mean value of the whole image, and whether to perform brightness enhancement processing is determined based on the red component mean value of the whole image to improve the usability of the image.
Detailed Description
Embodiments of the medical device safety shield mechanism of the present invention will now be described in detail.
The oxygen cylinder is particularly protected from the sun during use. Generally, the air bottle is transported and should be prevented from solarization in summer. Because the volume of the oxygen cylinder is limited, exposure to the sun can raise the temperature of the medium in the cylinder, resulting in a sudden increase in pressure within the cylinder, leaving the cylinder in a dangerous state. Some users do not take sun-shading measures in transportation, and the oxygen cylinder is exposed to the sun when the oxygen cylinder is used in summer. Particularly, the road temperature in summer often reaches more than 40 ℃, and if the gas cylinders have defects and are excessively filled or collide with each other, explosion accidents can occur.
In order to overcome the defects in the use of the oxygen cylinder in the prior art, the invention builds a safety protection mechanism for medical equipment.
The safety protection mechanism of the medical equipment according to the embodiment of the invention comprises:
and the pressure detection equipment is arranged on the oxygen cylinder and used for detecting the real-time pressure in the oxygen cylinder and sending a pressure alarm command when the real-time pressure exceeds the limit, or sending a normal pressure command.
Next, a detailed description of the structure of the safety guard mechanism for medical equipment according to the present invention will be further described.
In the medical device safety protection mechanism, the medical device safety protection mechanism further comprises: and the miniature imaging equipment is arranged above the oxygen cylinder and is used for performing imaging operation on the position of the oxygen cylinder so as to obtain an image around the oxygen cylinder.
In the medical device safety protection mechanism, the medical device safety protection mechanism further comprises: and the image traversing device is connected with the miniature imaging device and is used for receiving the images around the oxygen cylinder, performing non-overlapping traversing on the images around the oxygen cylinder by adopting a smooth window according to the sequence from left to right and from top to bottom to obtain corresponding traversing windows and outputting the traversing windows.
In the medical device safety protection mechanism, the medical device safety protection mechanism further comprises:
the particle acquisition equipment is connected with the image traversal equipment and used for receiving the traversal windows and performing the following particle confirmation actions on the traversal windows: obtaining the mean value of all brightness values of all pixel points in each traversal window to be used as a window mean value, carrying out deviation degree analysis on the window mean value and the overall brightness of the image around the oxygen cylinder, and when the deviation degree exceeds the limit, determining the traversal window to be a particle block;
the image dividing device is connected with the particle collecting device and used for forming a particle pattern in the oxygen cylinder periphery image based on each particle block output by the particle collecting device, and taking the image of the oxygen cylinder periphery image after the particle pattern is stripped as a non-particle pattern;
a differentiation processing device connected to the image dividing device, for receiving the grain pattern and the non-grain pattern, performing a low-pass filtering process on the grain pattern using a preset frequency threshold as a cutoff frequency to obtain a grain low-pass pattern, and further performing a low-pass filtering process on the non-grain pattern using one-half of the preset frequency threshold as the cutoff frequency to obtain a non-grain low-pass pattern, and outputting the grain low-pass pattern and the non-grain low-pass pattern;
the data fitting device is connected with the differentiation treatment device and used for receiving the particle low-pass pattern and the non-particle low-pass pattern and fitting the particle low-pass pattern and the non-particle low-pass pattern to obtain a fitted image corresponding to the image around the oxygen cylinder;
the signal analysis equipment is connected with the data fitting equipment and used for receiving the fitted image, extracting the characteristic quantity related to smoothing processing of the fitted image, inputting the extracted characteristic quantity into a data analysis model consisting of an input layer, an output layer and a plurality of hidden layers and carrying out data analysis on the characteristic quantity input by the input layer by layer, wherein the output layer is connected with the last hidden layer and used for outputting the result of data analysis of the last hidden layer, and the output quantity type of the output layer is a smoothing processing type;
the self-adaptive smoothing equipment is connected with the signal analysis equipment and is used for receiving the smoothing processing type and executing smoothing operation based on the smoothing processing type on the fitting image so as to obtain and output a smoothed image;
the amplitude measuring device is connected with the self-adaptive smoothing device and used for receiving the smoothed image, analyzing the amplitude of the noise in the smoothed image to obtain the maximum amplitude in the smoothed image, and determining the sizes of image segmentation blocks which are in direct proportion to the maximum amplitude based on the maximum amplitude to obtain all segmentation blocks with the same size;
the area selection device is connected with the amplitude measurement device and used for receiving the segmentation blocks with the same size and selecting four segmentation blocks positioned at four corner positions in the smoothed image from the segmentation blocks in the smoothed image as four corner segmentation blocks;
the regional identification equipment is respectively connected with the amplitude measurement equipment and the regional selection equipment and used for receiving the four segmentation blocks, acquiring the red component mean value of each corner segmentation block, calculating the mean value of the four red component mean values of the four corner image regions, outputting the acquired mean value as an integral component mean value, and acquiring the red component mean value of each corner segmentation block comprises: obtaining each red component value of each pixel point of each corner segmentation block, sequencing each red component value of each pixel point, and taking the red component value of a central serial number as a red component mean value of the corner segmentation block;
the command starting device is connected with the regional identification device and used for receiving the integral component mean value, sending a red component mean value lower command when the integral component mean value is smaller than a preset red component mean value, and sending a red component mean value higher command when the integral component mean value is larger than or equal to the preset red component mean value;
the brightness improving device is respectively connected with the partitioned area identification device and the command starting device, and is used for executing brightness value improving processing on the smoothed image to obtain an improved processed image when receiving the command of low red component mean value, and skipping the brightness value improving processing on the smoothed image when receiving the command of high red component mean value, and outputting the smoothed image as an improved processed image;
the first extraction device is connected with the brightness improvement device and used for receiving the improved image, extracting a corresponding human body region to be detected from the improved image based on a preset standard human body shape, respectively carrying out normalization processing on the human body region to be detected and the preset standard human body shape to obtain a first normalized image and a second normalized image, subtracting the first normalized image and the second normalized image to obtain a difference image, extracting the number of pixels with nonzero pixel values in the difference image, and outputting the extracted number as the number of difference pixels;
the second extraction equipment is connected with the first extraction equipment and used for receiving the difference pixel number, extracting the total number of pixels of the first normalized image, and sending a human body matching signal when the proportion of the difference pixel number occupying the total number of pixels is smaller than or equal to a preset proportion threshold value, or sending a human body unmatched signal;
the state switching equipment is connected with the oxygen cylinder and the second extraction equipment, and is used for controlling the oxygen cylinder to enter a use state when receiving the human body matching signal and controlling the oxygen cylinder to enter a stop state when receiving the human body unmatching signal;
wherein, in the state switching apparatus, a safeguard level of the oxygen cylinder in the use state is higher than a safeguard level of the oxygen cylinder in the deactivated state.
In the medical device safety protection mechanism: the amplitude measuring device, the region selecting device, the sub-region identifying device, the command starting device and the brightness improving device share the same quartz oscillator.
In the medical device safety protection mechanism: in the differentiation treatment device, performing a low-pass filtering treatment on the particle pattern using a preset frequency threshold as a cutoff frequency to obtain a particle low-pass pattern includes: and an image obtained by removing frequency components of the particle pattern, the frequency components being higher than or equal to the cutoff frequency, is used as the particle low-pass pattern, and the particle low-pass pattern is output.
In the medical device safety protection mechanism: in the differentiation treatment device, performing a low-pass filtering treatment on the non-particle pattern with half of a preset frequency threshold as a cutoff frequency to obtain a non-particle low-pass pattern includes: and an image obtained by removing frequency components of the non-particle pattern, the frequency components being higher than or equal to a cutoff frequency, is used as the particle non-low-pass pattern, and the particle non-low-pass pattern is output.
In the medical device safety protection mechanism: in the image traversal equipment, the traversal window is a square window, and the side length of the square window is in direct proportion to the signal-to-noise ratio of the image around the oxygen bottle.
In the medical device safety protection mechanism: in the particle collecting apparatus, the overall brightness of the image around the oxygen cylinder is obtained in the following mode: and obtaining all brightness values of all pixel points of the image around the oxygen bottle, and averaging all brightness values of all pixel points of the image around the oxygen bottle to obtain the overall brightness of the image around the oxygen bottle.
In the medical device safety protection mechanism: and in the particle collection equipment, when the deviation degree is not exceeded, confirming that the traversal window is a non-particle block.
In addition, the particle collection device is a CP L D chip, CP L D has the advantages of flexible programming, high integration level, short design and development period, wide application range, advanced development tools, low design and manufacturing cost, low requirement on hardware experience of designers, no need of testing standard products, strong confidentiality, high price popularization and the like, and can realize large-scale circuit design, so that the device is widely applied to prototype design and product production (generally less than 10,000 pieces) of products, CP L D devices can be applied to almost all occasions of small-scale universal digital integrated circuits in application, CP L D devices become indispensable components of electronic products, and the design and application of the device become a necessary skill for electronic engineers.
The CP L D is a digital integrated circuit whose logic function is built by user according to their needs, the basic design method is to generate corresponding target file by means of integrated development software platform and using principle diagram, hardware description language, etc. to transfer the code to target chip by means of download cable ("in-system" programming) to implement the designed digital system.
By adopting the medical equipment safety protection mechanism, aiming at the technical problem that the oxygen cylinder in the prior art is lack of an adaptive control mechanism, the pressure detection equipment is arranged on the oxygen cylinder and used for detecting the real-time pressure in the oxygen cylinder and sending a pressure alarm command when the real-time pressure exceeds the limit, otherwise, sending a normal pressure command; the state switching equipment is connected with the oxygen cylinder and the second extraction equipment, and is used for controlling the oxygen cylinder to enter a use state when receiving the human body matching signal and controlling the oxygen cylinder to enter a stop state when receiving the human body unmatching signal; in the state switching device, the oxygen cylinder in the use state has a higher safeguard level than the oxygen cylinder in the deactivated state; thereby solving the technical problem.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (7)
1. A medical device safety shield mechanism, comprising:
the pressure detection equipment is arranged on the oxygen cylinder and used for detecting the real-time pressure in the oxygen cylinder and sending a pressure alarm command when the real-time pressure exceeds the limit, otherwise, sending a normal pressure command;
the miniature imaging device is arranged above the oxygen cylinder and used for performing imaging operation on the position of the oxygen cylinder to obtain an image around the oxygen cylinder;
the image traversing device is connected with the miniature imaging device and used for receiving the images around the oxygen cylinder, performing non-overlapping traversing on the images around the oxygen cylinder by adopting smooth windows according to the sequence from left to right and from top to bottom to obtain corresponding traversing windows and outputting the traversing windows;
the particle acquisition equipment is connected with the image traversal equipment and used for receiving the traversal windows and performing the following particle confirmation actions on the traversal windows: obtaining the mean value of all brightness values of all pixel points in each traversal window to be used as a window mean value, carrying out deviation degree analysis on the window mean value and the overall brightness of the image around the oxygen cylinder, and when the deviation degree exceeds the limit, determining the traversal window to be a particle block;
the image dividing device is connected with the particle collecting device and used for forming a particle pattern in the oxygen cylinder periphery image based on each particle block output by the particle collecting device, and taking the image of the oxygen cylinder periphery image after the particle pattern is stripped as a non-particle pattern;
a differentiation processing device connected to the image dividing device, for receiving the grain pattern and the non-grain pattern, performing a low-pass filtering process on the grain pattern using a preset frequency threshold as a cutoff frequency to obtain a grain low-pass pattern, and further performing a low-pass filtering process on the non-grain pattern using one-half of the preset frequency threshold as the cutoff frequency to obtain a non-grain low-pass pattern, and outputting the grain low-pass pattern and the non-grain low-pass pattern;
the data fitting device is connected with the differentiation treatment device and used for receiving the particle low-pass pattern and the non-particle low-pass pattern and fitting the particle low-pass pattern and the non-particle low-pass pattern to obtain a fitted image corresponding to the image around the oxygen cylinder;
the signal analysis equipment is connected with the data fitting equipment and used for receiving the fitted image, extracting the characteristic quantity related to smoothing processing of the fitted image, inputting the extracted characteristic quantity into a data analysis model consisting of an input layer, an output layer and a plurality of hidden layers and carrying out data analysis on the characteristic quantity input by the input layer by layer, wherein the output layer is connected with the last hidden layer and used for outputting the result of data analysis of the last hidden layer, and the output quantity type of the output layer is a smoothing processing type;
the self-adaptive smoothing equipment is connected with the signal analysis equipment and is used for receiving the smoothing processing type and executing smoothing operation based on the smoothing processing type on the fitting image so as to obtain and output a smoothed image;
the amplitude measuring device is connected with the self-adaptive smoothing device and used for receiving the smoothed image, analyzing the amplitude of the noise in the smoothed image to obtain the maximum amplitude in the smoothed image, and determining the sizes of image segmentation blocks which are in direct proportion to the maximum amplitude based on the maximum amplitude to obtain all segmentation blocks with the same size;
the area selection device is connected with the amplitude measurement device and used for receiving the segmentation blocks with the same size and selecting four segmentation blocks positioned at four corner positions in the smoothed image from the segmentation blocks in the smoothed image as four corner segmentation blocks;
the regional identification equipment is respectively connected with the amplitude measurement equipment and the regional selection equipment and used for receiving the four segmentation blocks, acquiring the red component mean value of each corner segmentation block, calculating the mean value of the four red component mean values of the four corner image regions, outputting the acquired mean value as an integral component mean value, and acquiring the red component mean value of each corner segmentation block comprises: obtaining each red component value of each pixel point of each corner segmentation block, sequencing each red component value of each pixel point, and taking the red component value of a central serial number as a red component mean value of the corner segmentation block;
the command starting device is connected with the regional identification device and used for receiving the integral component mean value, sending a red component mean value lower command when the integral component mean value is smaller than a preset red component mean value, and sending a red component mean value higher command when the integral component mean value is larger than or equal to the preset red component mean value;
the brightness improving device is respectively connected with the partitioned area identification device and the command starting device, and is used for executing brightness value improving processing on the smoothed image to obtain an improved processed image when receiving the command of low red component mean value, and skipping the brightness value improving processing on the smoothed image when receiving the command of high red component mean value, and outputting the smoothed image as an improved processed image;
the first extraction device is connected with the brightness improvement device and used for receiving the improved image, extracting a corresponding human body region to be detected from the improved image based on a preset standard human body shape, respectively carrying out normalization processing on the human body region to be detected and the preset standard human body shape to obtain a first normalized image and a second normalized image, subtracting the first normalized image and the second normalized image to obtain a difference image, extracting the number of pixels with nonzero pixel values in the difference image, and outputting the extracted number as the number of difference pixels;
the second extraction equipment is connected with the first extraction equipment and used for receiving the difference pixel number, extracting the total number of pixels of the first normalized image, and sending a human body matching signal when the proportion of the difference pixel number occupying the total number of pixels is smaller than or equal to a preset proportion threshold value, or sending a human body unmatched signal;
the state switching equipment is connected with the oxygen cylinder and the second extraction equipment, and is used for controlling the oxygen cylinder to enter a use state when receiving the human body matching signal and controlling the oxygen cylinder to enter a stop state when receiving the human body unmatching signal;
wherein, in the state switching apparatus, a safeguard level of the oxygen cylinder in the use state is higher than a safeguard level of the oxygen cylinder in the deactivated state.
2. The medical device safety shield mechanism of claim 1, wherein:
the amplitude measuring device, the region selecting device, the sub-region identifying device, the command starting device and the brightness improving device share the same quartz oscillator.
3. The medical device safety shield mechanism of claim 2, wherein:
in the differentiation treatment device, performing a low-pass filtering treatment on the particle pattern using a preset frequency threshold as a cutoff frequency to obtain a particle low-pass pattern includes: and an image obtained by removing frequency components of the particle pattern, the frequency components being higher than or equal to the cutoff frequency, is used as the particle low-pass pattern, and the particle low-pass pattern is output.
4. The medical device safety shield mechanism of claim 3, wherein:
in the differentiation treatment device, performing a low-pass filtering treatment on the non-particle pattern with half of a preset frequency threshold as a cutoff frequency to obtain a non-particle low-pass pattern includes: and an image obtained by removing frequency components of the non-particle pattern, the frequency components being higher than or equal to a cutoff frequency, is used as the particle non-low-pass pattern, and the particle non-low-pass pattern is output.
5. The medical device safety shield mechanism of claim 4, wherein:
in the image traversal equipment, the traversal window is a square window, and the side length of the square window is in direct proportion to the signal-to-noise ratio of the image around the oxygen bottle.
6. The medical device safety shield mechanism of claim 5, wherein:
in the particle collecting apparatus, the overall brightness of the image around the oxygen cylinder is obtained in the following mode: and obtaining all brightness values of all pixel points of the image around the oxygen bottle, and averaging all brightness values of all pixel points of the image around the oxygen bottle to obtain the overall brightness of the image around the oxygen bottle.
7. The medical device safety shield mechanism of claim 6, wherein:
and in the particle collection equipment, when the deviation degree is not exceeded, confirming that the traversal window is a non-particle block.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910002353.8A CN109657645B (en) | 2019-01-02 | 2019-01-02 | Safety protection mechanism for medical equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910002353.8A CN109657645B (en) | 2019-01-02 | 2019-01-02 | Safety protection mechanism for medical equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109657645A CN109657645A (en) | 2019-04-19 |
| CN109657645B true CN109657645B (en) | 2020-08-07 |
Family
ID=66118746
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910002353.8A Active CN109657645B (en) | 2019-01-02 | 2019-01-02 | Safety protection mechanism for medical equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109657645B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107143748A (en) * | 2017-07-04 | 2017-09-08 | 卢云丽 | A kind of quick oxygen cylinder for rushing oxygen |
| CN108076506A (en) * | 2017-11-30 | 2018-05-25 | 秦广民 | A kind of method that power consumption is adaptively adjusted |
| WO2017062454A9 (en) * | 2015-10-07 | 2018-08-02 | Velez Michael D | Flow alarm |
| CN108734678A (en) * | 2018-05-22 | 2018-11-02 | 任阿毛 | Dining table closure of openings control system |
| CN108786127A (en) * | 2018-06-25 | 2018-11-13 | 王芳 | Parachute-type lifting body manoeuvring platform |
| CN108870073A (en) * | 2018-06-29 | 2018-11-23 | 中国人民解放军陆军军医大学第附属医院 | A kind of oxygen uses warning device |
| CN108969858A (en) * | 2018-08-08 | 2018-12-11 | 黄颖琦 | Oxygen method and system in a kind of full-automatic feeding oxygen robot |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170015263A1 (en) * | 2015-07-14 | 2017-01-19 | Ford Global Technologies, Llc | Vehicle Emergency Broadcast |
| CN108388012B (en) * | 2018-03-22 | 2021-01-26 | 中电莱斯信息系统有限公司 | Intelligent fire-fighting respirator glasses with multi-information fusion display function |
-
2019
- 2019-01-02 CN CN201910002353.8A patent/CN109657645B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017062454A9 (en) * | 2015-10-07 | 2018-08-02 | Velez Michael D | Flow alarm |
| CN107143748A (en) * | 2017-07-04 | 2017-09-08 | 卢云丽 | A kind of quick oxygen cylinder for rushing oxygen |
| CN108076506A (en) * | 2017-11-30 | 2018-05-25 | 秦广民 | A kind of method that power consumption is adaptively adjusted |
| CN108734678A (en) * | 2018-05-22 | 2018-11-02 | 任阿毛 | Dining table closure of openings control system |
| CN108786127A (en) * | 2018-06-25 | 2018-11-13 | 王芳 | Parachute-type lifting body manoeuvring platform |
| CN108870073A (en) * | 2018-06-29 | 2018-11-23 | 中国人民解放军陆军军医大学第附属医院 | A kind of oxygen uses warning device |
| CN108969858A (en) * | 2018-08-08 | 2018-12-11 | 黄颖琦 | Oxygen method and system in a kind of full-automatic feeding oxygen robot |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109657645A (en) | 2019-04-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Alsmadi | A hybrid Fuzzy C-Means and Neutrosophic for jaw lesions segmentation | |
| Oo et al. | Brain tumor detection and segmentation using watershed segmentation and morphological operation | |
| CN107977926B (en) | PET/MRI different-computer brain image information fusion method with improved neural network | |
| US20210133473A1 (en) | Learning apparatus and learning method | |
| CN107977963A (en) | Decision method, device and the realization device of Lung neoplasm | |
| Mahmood et al. | Image segmentation methods and edge detection: An application to knee joint articular cartilage edge detection | |
| Mishra et al. | Automatic lesion border selection in dermoscopy images using morphology and color features | |
| Mittal et al. | Identification & enhancement of different skin lesion images by segmentation techniques | |
| CN109657645B (en) | Safety protection mechanism for medical equipment | |
| Xuanyang et al. | Computer aided detection of SARS based on radiographs data mining | |
| Ajam et al. | Segmentation of CT brain stroke image using marker controlled watershed | |
| US8116545B2 (en) | Method and system for analysis of bone density | |
| Silva et al. | A computational method for semi‐automatic measurement of pressure ulcers | |
| Spitzer et al. | Interpretable surface-based detection of focal cortical dysplasias: a MELD study | |
| Ye et al. | Segmentation and feature extraction of endoscopic images for making diagnosis of acute appendicitis | |
| CN107633882B (en) | Mix the minimally invasive medical service system and its aid decision-making method under cloud framework | |
| CN110363744B (en) | Lung age detection method and equipment | |
| CN109727220B (en) | Instrument state unlocking mechanism | |
| Chen et al. | Detection of Various Dental Conditions on Dental Panoramic Radiography Using Faster R-CNN | |
| Sadeghi et al. | A new method for the diagnosis of urinary tract stone in radiographs with image processing | |
| Bhuvaneswari et al. | Oral Cancer Detection at Early Stage Using Convolutional Neural Network in Healthcare Informatics | |
| Al-Ghraibah et al. | Tibia Fracture Detection using a Modified Edge Detection Method based on Bone Length | |
| CN109886184B (en) | Real-time outpatient service data correction platform | |
| Shen et al. | Morphometric analysis of genetic variation in hippocampal shape in mild cognitive impairment: Role of an il-6 promoter polymorphism | |
| Nivetha et al. | Automated Lesion Image Segmentation Based on Novel Histogram-Based K-Means Clustering Using COVID-19 Chest CT Images |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: No.57, 7th floor, No.37, Renmin West Road, Qindu District, Xianyang City, Shaanxi Province Applicant after: Wang Ping Address before: Room A606, AB Building, Landscape Scenic Plaza, 23 Cangwu Road, Haizhou District, Lianyungang City, Jiangsu Province, 2002 Applicant before: Wang Ping |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20211230 Address after: 224600 west of Xiangshui County, Yancheng City, Jiangsu Province Patentee after: JIANGSU XIANGRUI PHARMACEUTICAL CO.,LTD. Address before: 712000 No. 57, 7th floor, No. 37, Renmin West Road, Qindu District, Xianyang City, Shaanxi Province Patentee before: Wang Ping |