CN112989960A - Method and system for monitoring putting-on and taking-off behaviors of protective articles based on computer vision technology - Google Patents
Method and system for monitoring putting-on and taking-off behaviors of protective articles based on computer vision technology Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/20—Movements or behaviour, e.g. gesture recognition
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- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
- G06K17/0029—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement being specially adapted for wireless interrogation of grouped or bundled articles tagged with wireless record carriers
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
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Abstract
The invention discloses a method and a system for monitoring putting-on and taking-off behaviors of protective articles based on a computer vision technology, wherein the monitoring method comprises the steps of monitoring the whole process from the time when medical workers enter to the time when the medical workers leave the wearing and taking-off states of protective garments, determining the wearing and taking-off behaviors of the protective articles with the monitoring targets of the medical workers to acquire information, converting the acquired monitoring target information into data signals to perform deep learning, transmitting effective information acquired by the deep learning to an early warning model, and identifying correct actions, wrong actions and missing actions after the analysis of the early warning model, and sending an alarm signal once the wrong actions and the missing actions are found so as to alarm by an alarm. The invention can accurately and comprehensively monitor the putting-on and taking-off behaviors of the protective clothing of the medical personnel and give an alarm in time, thereby improving the medical safety and reducing the occurrence of infection events.
Description
Technical Field
The invention relates to a monitoring method based on a computer vision technology, in particular to a method and a system for monitoring the putting-on and taking-off behaviors of protective articles based on the computer vision technology.
Background
Along with the continuous improvement of hospital management system and measures, in the aspect of infection prevention and control, high attention is paid to health administrative departments at all levels, the supervision and enforcement strength is enhanced unprecedentedly, and the infection prevention and control consciousness of medical staff is also enhanced continuously. The medical protective clothing is the most important anti-interference protective article for doctors and patients. The medical protective clothing has good moisture permeability and barrier property, can effectively resist the penetration of alcohol, blood, body fluid, air dust particles and bacteria, is safe and convenient to use, can effectively protect a wearer from being threatened by infection, and has the advantages of comfortable wearing, good hand feeling, strong tensile resistance, air permeability, water resistance, no cross infection and the like. The medical protective clothing can only be put on or taken off in a special protective clothing putting-on or taking-off room, the protective clothing needs to be put on all the time when working in an isolation monitoring ward, the protective clothing needs to be changed every 4 hours, and if the medical protective clothing is not well worn, the medical protective clothing is not put on or taken off normally, great potential safety hazards exist.
The existing protective clothing for medical care personnel is not provided with related supervision measures for putting on and taking off, even if the existing protective clothing for medical care personnel is provided with the related supervision measures, the method only adopts a manual supervision mode, and is time-consuming and labor-consuming in manual supervision management, and the method is inevitable to have omission, incomplete in information monitoring and incapable of realizing lasting real-time monitoring and intervention. Therefore, the prior protective clothing for medical care personnel has no comprehensive and effective supervision and monitoring measures for the putting on and taking off actions.
Disclosure of Invention
The invention aims to provide a method and a system for monitoring the putting-on and taking-off behaviors of protective articles based on a computer vision technology. The invention can accurately and comprehensively monitor the putting-on and taking-off behaviors of the protective clothing of the medical personnel and give an alarm in time, thereby improving the medical safety and reducing the occurrence of infection events.
The technical scheme of the invention is as follows: the method comprises the steps of monitoring the whole process from the time when medical personnel enter to the time when the medical personnel leave the protective clothing wearing and taking off, determining that the monitoring target is the protective clothing wearing and taking off behavior of the medical personnel to acquire information, converting the acquired monitoring target information into a data signal to perform deep learning, transmitting effective information obtained by the deep learning to an early warning model, and identifying correct action, wrong action and missing action after analysis by the early warning model, and sending an alarm signal once the wrong action and the missing action are found so as to alarm.
In the method for monitoring putting-on and taking-off behaviors of the protective articles based on the computer vision technology, the acquisition mode comprises the steps of acquiring personal information of medical personnel through an electronic tag, acquiring images at different angles through a plurality of cameras, and acquiring displacement of an object through an acceleration sensor to obtain the action state of the object; sensing a final position of the object by a positioning sensor; monitoring target information includes: the personal information of the medical personnel and the key behaviors screened from the putting-on and taking-off behaviors of the protective articles of the medical personnel.
In the method for monitoring putting-on and taking-off behaviors of the protective articles based on the computer vision technology, the deep learning comprises the steps of processing data signals by adopting a deep image, retaining related character behavior information, blurring the face of a human body, removing irrelevant interference information to obtain processed key behaviors, and decomposing each key behavior into key actions or states, wherein the key actions comprise putting-on and taking-off actions of the protective articles, personal moving positions, putting-on and taking-off fixed point positions, discarding positions of the protective articles and skin disinfection; and calibrating the same motion sequence obtained from multiple angles into a group of motions.
In the method for monitoring the putting-on and taking-off behaviors of the protective articles based on the computer vision technology, the correct putting-on and taking-off key behaviors and sequences of the protective articles are stored in the early warning model in advance, and the collected information is compared with the pre-stored information one by one, so that the correct putting-on and taking-off actions and the wrong putting-on and taking-off actions are identified.
The protective article wearing and taking-off behavior monitoring system based on the computer vision technology is used for realizing the monitoring method and comprises a data acquisition module and an integrated protective garment, wherein the output end of the data acquisition module is connected with the input end of a computer, and the output end of the computer is connected with a display screen and an alarm; the data acquisition module comprises an image collector, an RFID reader-writer and a signal receiver which are arranged between the wearing and the taking-off of the protective clothing; the integrated protective clothing comprises a coat, the lower end of the coat is connected with trousers, a zipper is arranged on the back of the coat, a chest card is arranged on one side of the chest of the coat, an electronic tag is arranged on the chest card and connected with a computer through an RFID reader-writer, a waist seal is fixedly connected with the waist of the coat, an acceleration sensor is arranged on the waist seal and connected with the computer through a signal receiver, sticky hair is arranged at one end of the waist seal, and sticky thorns are arranged at the other end of the waist seal.
In the protection article putting-on and taking-off behavior monitoring system based on the computer vision technology, the number of the image collectors is multiple, and the plurality of image collectors are distributed at different positions.
In the system for monitoring putting-on and taking-off behaviors of the protective articles based on the computer vision technology, the upper end of the coat is connected with the hat, the hat is provided with an opening corresponding to the face, the edge of the opening is provided with the fastening ring, the opening is provided with the mask, the two sides of the edge of the opening on the hat are both provided with the first connecting hole and the second connecting hole, and the elastic ear band of the mask penetrates out of the first connecting hole and then penetrates into the second connecting hole.
In the aforementioned protective articles wears to take off action monitored control system based on computer vision technique, the elasticity ear area is connected with the adjusting collar after wearing out first connecting hole, and the second connecting hole is penetrated again to the elasticity ear area after passing the adjusting collar, and the elasticity ear area has the lag along elasticity ear area length direction parcel after penetrating the second connecting hole.
In the above-mentioned protective article putting-on and taking-off behavior monitoring system based on the computer vision technology, the volume of the adjusting sleeve is larger than the aperture of the first connecting hole.
In the system for monitoring putting-on and taking-off behaviors of the protective articles based on the computer vision technology, the coat, the trousers, the hat and the mask are of an integrated structure.
Compared with the prior art, the invention can comprehensively monitor the putting-on and taking-off behaviors entering the putting-on and taking-off process of the protective clothing, improve the compliance of medical workers to the putting-on and taking-off system implementation of the protective clothing, detect and intervene irregular behaviors in real time, trace the putting-on and taking-off behaviors of the medical workers to individuals, ensure correct wearing, improve medical safety and reduce the occurrence of infection events.
The image collector that sets up through wearing between taking off at the protective clothing passes into the computer with personage's action image, implements the control and judges whether accurate, the standard of medical personnel's protective clothing behavior of wearing to take off to the acceleration sensor that sets up on the integral type protective clothing is cooperated, through signal receiver with acceleration sensor response integral type protective clothing's motion direction information spread into the computer, and then more accurately, judge comprehensively whether wearing of integral type protective clothing is taken off accurately, the standard, to the real-time early warning of the non-standard action.
Furthermore, through the electronic tags on the integrated protective clothing, the related information of the medical personnel wearing the integrated protective clothing can be known, and the identity of the medical personnel can be determined, so that the early warning is more targeted.
Therefore, the invention can accurately and comprehensively monitor the wearing and taking-off behaviors of the protective clothing of medical personnel, improve the medical safety and reduce the occurrence of infection events.
Drawings
FIG. 1 is a flow chart of a monitoring method of the present invention;
FIG. 2 is a schematic diagram of the monitoring system of the present invention;
FIG. 3 is a schematic structural view of the unitary body armor;
fig. 4 is an enlarged view of a portion of a structure in fig. 3.
The labels in the figures are: 1. a data acquisition module; 11. an image collector; 12. an RFID reader; 13. a signal receiver; 2. a computer; 31. a display screen; 32. an alarm; 4. an integrated protective garment; 41. a coat; 42. trousers; 43. chest cards; 44. an electronic tag; 45. waist sealing; 46. an acceleration sensor; 47. sticking hair; 48. sticking thorns; 51. a cap; 52. an opening; 53. a fastening ring; 54. a mask; 55. a first connection hole; 56. a second connection hole; 57. an elastic ear band; 58. an adjusting sleeve; 59. a protective sleeve.
Detailed Description
The present invention is further illustrated by the following examples, which are not to be construed as limiting the invention.
Example (b):
as shown in figure 1, the method for monitoring the putting-on and taking-off behaviors of the protective articles based on the computer vision technology comprises the steps of monitoring the whole process from the time when medical workers enter to the time when the medical workers leave the putting-on and taking-off states of the protective garments, determining the putting-on and taking-off behaviors of the protective articles with the monitoring targets as the medical workers to acquire information, converting the acquired monitoring target information into data signals to perform deep learning, conveying effective information acquired by the deep learning to an early warning model, and identifying correct actions, wrong actions and missing actions after analysis through the early warning model, and sending an alarm signal once the wrong actions and the missing actions are found so as to alarm.
The acquisition mode comprises the steps of acquiring personal information of medical personnel through an electronic tag; the method comprises the following steps of acquiring images at different angles through a plurality of cameras, acquiring the displacement of an object through an acceleration sensor, and obtaining the action state of the object by matching with shooting of the cameras; the final position of the object is sensed by the position sensor, for example, to know whether the used protective article is to be discarded to the correct disposal location. Monitoring target information includes: the personal information of the medical personnel and the key behaviors screened from the putting-on and taking-off behaviors of the protective articles of the medical personnel.
The deep learning comprises the steps of processing data signals by adopting a deep image, keeping related character behavior information, blurring the face of a human body, removing irrelevant interference information to obtain processed key behaviors, and decomposing each key behavior into key actions or states, wherein the key actions comprise putting-on and taking-off actions of protective articles, personal moving positions, putting-on and taking-off fixed point positions, discarding positions of the protective articles, skin disinfection and the like; the same action sequence obtained from multiple angles is calibrated into a group of actions, and the identification accuracy of the target action is improved. The protective articles comprise masks, protective clothing, hats, gloves, protective glasses and the like.
The early warning model stores correct key actions and sequences of putting on and taking off of the protective articles in advance, defines actions or states to be recognized, and compares the collected information with prestored information one by one, so that correct putting on and taking off actions, wrong putting on and taking off actions and missing actions are recognized.
The wearing and taking-off behavior of the protective clothing between wearing and taking-off is monitored, the compliance of medical workers to the implementation of the wearing and taking-off system of the protective articles is improved, irregular behaviors are perceived and intervened in real time, individuals can be traced back to the wearing and taking-off behaviors of the medical workers, correct wearing is ensured, and medical safety is improved.
A protective article putting-on and taking-off behavior monitoring system based on computer vision technology is used for realizing the method, and comprises a data acquisition module 1 and an integrated protective garment 4, wherein the output end of the data acquisition module 1 is connected with the input end of a computer 2, and the output end of the computer 2 is connected with a display screen 31 and an alarm 32; the data acquisition module 1 comprises an image collector 11, an RFID reader-writer 12 and a signal receiver 13 which are arranged between the wearing and the taking-off of the protective clothing; the integrated protective suit 4 comprises a coat 41, the lower end of the coat 41 is connected with trousers 42, the back of the coat 41 is provided with a zipper, one side of the chest of the coat 41 is provided with a chest plate 43, the chest plate 43 is provided with an electronic tag 44, the electronic tag 44 is connected with the computer 2 through the RFID reader-writer 12, the waist of the coat 41 is fixedly connected with a waist seal 45, the waist seal 45 is provided with an acceleration sensor 46, the acceleration sensor 46 is connected with the computer 2 through a signal receiver 13, one end of the waist seal 45 is provided with sticky hair 47, and the other end of the waist seal 45 is provided with sticky stabs 48.
The image collector 11 is provided with a plurality of image collectors 11, the plurality of image collectors 11 are distributed at different positions, and the image collectors 11 adopt cameras to collect pictures at different angles.
The upper end of the coat 41 is connected with a hat 51, the hat 51 is provided with an opening 52 corresponding to the face, the edge of the opening 52 is provided with a fastening ring 53, the opening 52 is provided with a mask 54, the two sides of the edge of the opening 52 on the hat 51 are provided with a first connecting hole 55 and a second connecting hole 56, and an elastic ear band 57 of the mask 54 penetrates through the first connecting hole 55 and then penetrates into the second connecting hole 56.
The elastic ear band 57 penetrates through the first connecting hole 55 and then is connected with an adjusting sleeve 58, the elastic ear band 57 penetrates through the adjusting sleeve 58 and then penetrates through the second connecting hole 56, and the elastic ear band 57 penetrates through the second connecting hole 56 and then is wrapped by a protective sleeve 59 along the length direction of the elastic ear band 57.
The volume of the adjustment sleeve 58 is larger than the aperture of the first connection hole 55. The adjusting sleeve is used outside the cap, so that the adjustment is more convenient.
The jacket 41, the trousers 42, the cap 51 and the mask 54 are of an integrated structure. The integral type is worn to take off, avoids omitting.
The trousers 42, the hat 51 and the mask 54 can also be provided with the acceleration sensor 46, so that the sensing accuracy and comprehensiveness are improved.
The connection mode, the information transmission mode and the operation principle among the acceleration sensor 46, the signal receiver 13 and the computer 2 are based on the ZigBee technology, and are all the prior art, and therefore, they are not specifically described here.
The connection mode, information transmission mode and operation principle between the electronic tag 44, the RFID reader/writer 12 and the computer 2 are based on the RFID technology, and are all the prior art, and therefore are not specifically described here.
The computer vision technology is a leading-edge field of artificial intelligence, and refers to a technology for converting a shot target into a data signal for deep learning through a special image shooting device. Computer vision has played an irreplaceable role in image diagnosis radiology, pathological image diagnosis, drug production, inspection systems, quality inspection of surgical instruments, and genomics modeling.
The invention adopts the computer 2 vision technology, namely, a plurality of image collectors 11 arranged in the wearing and taking-off room of the protective clothing comprehensively collect each behavior image of the person, and the behavior image of the person is transmitted into the computer 2, real-time monitoring is implemented, whether the wearing and taking-off behavior of the protective clothing of medical personnel is accurate and standard is judged, the acceleration sensor 46 arranged on the integrated protective clothing 4 is matched, the movement direction of the object is sensed through the acceleration sensor 46, so that the displacement of the object is judged, and some action behaviors of the object can be preliminarily judged through the displacement, for example: stoop, lift hands, etc.
The motion direction information of the acceleration sensor 46 sensing integrated protective clothing 4 is transmitted into the computer 2 through the signal receiver 13, so that whether the integrated protective clothing 4 is worn to take off accurately and normatively is judged more accurately and comprehensively, and the alarm 32 is used for early warning nonstandard behaviors in real time to guide medical workers to develop the normative integrated protective clothing 4 to wear to take off behavior habits, thereby reducing potential safety hazards and reducing infection risk rate.
Further, through the electronic tag 44 on the integrated protective clothing 4, the relevant information of the medical personnel wearing the integrated protective clothing 4 can be known, and the identity of the medical personnel can be determined, so that the early warning is more targeted.
When the medical staff wears the integrated protective suit 4, the waist seal 45 is worn at last, and when the integrated protective suit 4 is taken off, the waist seal 45 is detached at first. The waist seal 45 is connected with the adhesive thorns 48 through the adhesive hairs 47, so that the integrated protective suit 4 can be well worn by different medical workers in a fit manner, and the interference caused by overlarge size is avoided; the elastic ear band 57 of the mask 54 penetrates through the first connecting hole 55 and then penetrates through the second connecting hole 56, so that the elastic ear band 57 is connected to the integrated protective suit 4 to prevent the mask 54 from being missed, and the cap 51 is tightened by the elastic ear band 57 to be more attached to the face of a human body and to be more tightly protected while the mask 54 is worn. The adjusting sleeve 58 is arranged on the elastic ear band 57, so that the length of the elastic ear band 57 can be adjusted, and the wearing is convenient; the protective sleeve 59 arranged on the elastic ear band 57 effectively improves the comfort level when the doctor wears the elastic ear band 57, and reduces the discomfort caused by the medical care personnel wearing the mask 54 for a long time.
Claims (10)
1. A method for monitoring the putting-on and taking-off behaviors of protective articles based on a computer vision technology is characterized by comprising the following steps: the method comprises the steps of monitoring the whole process from the time when medical personnel enter to the time when the medical personnel leave the protective clothing, determining that the monitoring target is information acquisition for the wearing and taking-off behavior of the protective articles of the medical personnel, converting the acquired monitoring target information into data signals to carry out deep learning, conveying effective information obtained by the deep learning to an early warning model, identifying correct action, wrong action and missing action after the early warning model is analyzed, and sending an alarm signal once the wrong action and the missing action are found so as to enable an alarm to give an alarm.
2. The computer vision technology-based protective article putting-on and taking-off behavior monitoring method as claimed in claim 1, wherein: the acquisition mode comprises the steps of acquiring personal information of medical personnel through an electronic tag, acquiring images at different angles through a plurality of cameras, and acquiring the displacement of an object through an acceleration sensor to obtain the action state of the object; sensing a final position of the object by a positioning sensor; monitoring target information includes: the personal information of the medical personnel and the key behaviors screened from the putting-on and taking-off behaviors of the protective articles of the medical personnel.
3. The computer vision technology-based protective article putting-on and taking-off behavior monitoring method as claimed in claim 1, wherein: the deep learning comprises the steps of processing data signals by adopting a deep image, keeping related character behavior information, blurring the face of a human body, removing irrelevant interference information to obtain processed key behaviors, and decomposing each key behavior into key actions or states, wherein the key actions comprise putting-on and taking-off actions of protective articles, personal moving positions, putting-on and taking-off fixed point positions, discarding positions of the protective articles and skin disinfection; and calibrating the same motion sequence obtained from multiple angles into a group of motions.
4. The computer vision technology-based protective article putting-on and taking-off behavior monitoring method as claimed in claim 1, wherein: the early warning model stores correct key actions and sequences of putting on and taking off the protective articles in advance, and compares the collected information with prestored information one by one, so that correct putting on and taking off actions and wrong putting on and taking off actions are identified.
5. Protective articles wears to take off action monitored control system based on computer vision technique, its characterized in that: the monitoring method for realizing the monitoring method according to any one of claims 1 to 4, comprising a data acquisition module (1) and an integrated protective suit (4), wherein the output end of the data acquisition module (1) is connected with the input end of a computer (2), and the output end of the computer (2) is connected with a display screen (31) and an alarm (32); the data acquisition module (1) comprises an image collector (11), an RFID reader-writer (12) and a signal receiver (13), wherein the image collector is arranged between the wearing and taking-off of the protective clothing; integral type protective clothing (4) include jacket (41), the lower extreme of jacket (41) is connected with trousers (42), the back of jacket (41) is equipped with the zip fastener, chest card (43) are equipped with to the chest one side of jacket (41), be equipped with electronic tags (44) on chest card (43), electronic tags (44) are connected with computer (2) through RFID read write line (12), the waist fixedly connected with waist of jacket (41) seals (45), be equipped with acceleration sensor (46) on waist seals (45), acceleration sensor (46) pass through signal receiver (13) and are connected with computer (2), the one end of waist seals (45) is equipped with glues hair (47), the other end of waist seals (45) is equipped with glues thorn (48).
6. The system for monitoring the putting-on and putting-off behaviors of protective articles based on the computer vision technology as claimed in claim 5, wherein: the image collectors (11) are arranged in a plurality of numbers, and the image collectors (11) are distributed at different positions.
7. The system for monitoring the putting-on and putting-off behaviors of protective articles based on the computer vision technology as claimed in claim 5, wherein: the upper end of the coat (41) is connected with a hat (51), the hat (51) is provided with an opening (52) corresponding to the face, the edge of the opening (52) is provided with a fastening ring (53), the opening (52) is provided with a mask (54), the two sides of the edge of the opening (52) on the hat (51) are provided with a first connecting hole (55) and a second connecting hole (56), and an elastic ear band (57) of the mask (54) penetrates out of the first connecting hole (55) and then penetrates into the second connecting hole (56).
8. The system for monitoring the putting-on and putting-off behaviors of protective articles based on the computer vision technology as claimed in claim 7, wherein: the elastic ear belt (57) penetrates out of the first connecting hole (55) and then is connected with the adjusting sleeve (58), the elastic ear belt (57) penetrates through the adjusting sleeve (58) and then penetrates into the second connecting hole (56), and the elastic ear belt (57) penetrates into the second connecting hole (56) and then wraps the protecting sleeve (59) along the length direction of the elastic ear belt (57).
9. The system for monitoring putting-on and taking-off behaviors of protective articles based on computer vision technology as claimed in claim 8, wherein: the volume of the adjusting sleeve (58) is larger than the aperture of the first connecting hole (55).
10. The system for monitoring the putting-on and putting-off behaviors of protective articles based on the computer vision technology as claimed in claim 7, wherein: the coat (41), the trousers (42), the hat (51) and the mask (54) are of an integrated structure.
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| CN202110198236.0A CN112989960A (en) | 2021-02-22 | 2021-02-22 | Method and system for monitoring putting-on and taking-off behaviors of protective articles based on computer vision technology |
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| CN202110198236.0A CN112989960A (en) | 2021-02-22 | 2021-02-22 | Method and system for monitoring putting-on and taking-off behaviors of protective articles based on computer vision technology |
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| CN114926970A (en) * | 2022-05-20 | 2022-08-19 | 深圳市第三人民医院 | Medical protective article wearing and taking-off reminding method and related device |
| CN116152927A (en) * | 2023-02-24 | 2023-05-23 | 中山大学附属第三医院 | Protective clothing wears to take off action supervisory systems |
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