CN111700585B - Human eye fatigue degree monitoring system - Google Patents
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- CN111700585B CN111700585B CN202010723595.9A CN202010723595A CN111700585B CN 111700585 B CN111700585 B CN 111700585B CN 202010723595 A CN202010723595 A CN 202010723595A CN 111700585 B CN111700585 B CN 111700585B
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 41
- 208000003464 asthenopia Diseases 0.000 title claims abstract description 23
- 238000003745 diagnosis Methods 0.000 claims abstract description 52
- 238000007405 data analysis Methods 0.000 claims abstract description 33
- 238000001914 filtration Methods 0.000 claims abstract description 30
- 238000004891 communication Methods 0.000 claims abstract description 24
- 238000006243 chemical reaction Methods 0.000 claims abstract description 12
- 230000009467 reduction Effects 0.000 claims abstract description 7
- 238000000034 method Methods 0.000 claims description 13
- 230000002457 bidirectional effect Effects 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 abstract description 6
- 238000012423 maintenance Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 5
- 230000009471 action Effects 0.000 description 3
- 230000004397 blinking Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 206010013774 Dry eye Diseases 0.000 description 1
- 206010047513 Vision blurred Diseases 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 235000019606 astringent taste Nutrition 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 208000030533 eye disease Diseases 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 230000028327 secretion Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
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- G—PHYSICS
- 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
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2560/00—Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
- A61B2560/02—Operational features
- A61B2560/0266—Operational features for monitoring or limiting apparatus function
- A61B2560/0276—Determining malfunction
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention discloses a human eye fatigue degree monitoring system which comprises an acquisition layer and a monitoring layer, wherein the acquisition layer comprises a sensor module, a signal conversion module and a first wireless communication unit, the monitoring layer comprises a second wireless communication unit, a filtering module, an information management module, a timing module, a server, a monitoring data analysis module, an alarm module and an intelligent diagnosis module, and the filtering module comprises a photoelectric noise database, a signal resolution unit, a photoelectric noise signal filtering unit and a signal reduction unit. This human eye fatigue degree monitoring system filters photoelectric noise through being equipped with filtration module, greatly reduced photoelectric noise to data transmission's influence to improved the accuracy of data feedback, through being equipped with intelligent diagnosis module, combine the data of transmission to predict sensor operating condition, and diagnose when breaking down, made things convenient for the maintenance work in later stage.
Description
Technical Field
The invention relates to the technical field of eye fatigue monitoring, in particular to a human eye fatigue degree monitoring system.
Background
Visual fatigue is a common disease of eyes, and the eye dryness, eye astringency and eye soreness caused by the visual fatigue directly affect the work and life of people due to blurred vision and even vision decline. The eye fatigue is mainly caused by that when people pay attention to watch screens of electronic products such as televisions, computers or mobile phones, eye blinking times are reduced, tear secretion is correspondingly reduced, and meanwhile, eyes are strongly stimulated by blinking screens. Eye fatigue can also cause and exacerbate various eye diseases. The best way to relieve eye strain is to rest the eyes.
The existing monitoring of human eye fatigue is usually to monitor and feed back through a sensor, but diagnosis and working state prediction when the sensor fails are lacking, and data fed back by the sensor are easily affected by photoelectric noise during transmission, so that the accuracy of data feedback is reduced.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a human eye fatigue degree monitoring system.
In order to achieve the above purpose, the invention is realized by the following technical scheme: the utility model provides a human eye fatigue degree monitoring system, includes acquisition layer and monitoring layer, acquisition layer includes sensor module, signal conversion module and first wireless communication unit, the monitoring layer includes second wireless communication unit, filtration module, information management module, timing module, server, monitoring data analysis module, alarm module and intelligent diagnosis module.
Preferably, the filtering module comprises a photoelectric noise database, a signal resolution unit, a photoelectric noise signal filtering unit and a signal restoring unit, wherein the output end of the photoelectric noise database is connected with the input end of the signal resolution unit, the output end of the signal resolution unit is connected with the input end of the photoelectric noise signal filtering unit, and the output end of the photoelectric noise signal filtering unit is connected with the input end of the signal restoring unit.
Preferably, the monitoring data analysis module comprises a data analysis unit, a data classification unit and a data analysis model establishment unit, wherein the output end of the data analysis unit is connected with the input end of the data classification unit, and the output end of the data classification unit is connected with the input end of the data analysis model establishment unit.
Preferably, the alarm module comprises an early warning database, an early warning value setting unit, a data comparison unit and an alarm feedback unit, wherein the output end of the early warning database is connected with the input end of the early warning value setting unit, the output end of the early warning value setting unit is connected with the input end of the data comparison unit, and the output end of the data comparison unit is connected with the input end of the alarm feedback unit.
Preferably, the intelligent diagnosis module comprises a fault database, a fault diagnosis method forming unit, an algorithm unit, a fault diagnosis model generating unit, a diagnosis unit and a working state predicting unit, wherein the output ends of the fault database, the fault diagnosis method forming unit and the algorithm unit are connected with the input end of the fault diagnosis model generating unit, the output end of the fault diagnosis model generating unit is connected with the input end of the diagnosis unit, and the output end of the diagnosis unit is connected with the input end of the working state predicting unit.
Preferably, the sensor module comprises a flexible sensor and a piezoelectric sensor, the output end of the sensor module is connected with the input end of the signal conversion module, and the output end of the signal conversion module is connected with the input end of the first wireless communication unit.
Preferably, the output end of the first wireless communication unit is connected with the input end of the second wireless communication unit, the output end of the second wireless communication unit is connected with the input end of the filtering module, the output ends of the filtering module and the timing module are connected with the input end of the information management module, the monitoring data analysis module and the intelligent diagnosis module are connected with the server in a bidirectional mode, and the output end of the server is connected with the input end of the alarm module.
The invention provides a human eye fatigue degree monitoring system. Compared with the prior art, the method has the following beneficial effects:
(1) This human eye fatigue degree monitoring system, through being equipped with filter module, filter photoelectric noise, greatly reduced photoelectric noise to data transmission's influence to improved the accuracy of data feedback, through being equipped with intelligent diagnosis module, combine the data of transmission to predict sensor operating condition, and diagnose when breaking down, made things convenient for later maintenance work.
(2) The human eye fatigue degree monitoring system is characterized in that the monitoring data analysis module is used for analyzing the human eye fatigue degree through the monitoring of the flexible sensor and the piezoelectric sensor, so that the human eye fatigue degree is monitored, and the alarm module is used for alarming after a certain value is reached, so that a user is conveniently reminded of rest.
Drawings
FIG. 1 is a schematic block diagram of a system of the present invention;
FIG. 2 is a schematic block diagram of a filtration module of the present invention;
FIG. 3 is a schematic block diagram of a monitoring data analysis module of the present invention;
FIG. 4 is a schematic block diagram of an alarm module of the present invention;
fig. 5 is a schematic block diagram of the intelligent diagnostic module of the present invention.
In the figure, 1, an acquisition layer; 11. a sensor module; 111. a flexible sensor; 112. a piezoelectric sensor; 12. a signal conversion module; 13. a first wireless communication unit; 2. monitoring a layer; 21. a second wireless communication unit; 22. a filtration module; 221. a photoelectric noise database; 222. a signal discrimination unit; 223. a photoelectric noise signal filtering unit; 224. a signal reduction unit; 23. an information management module; 24. a timing module; 25. a server; 26. a monitoring data analysis module; 261. a data analysis unit; 262. a data classification unit; 263. a data analysis model building unit; 27. an alarm module; 271. an early warning database; 272. an early warning value setting unit; 273. a data comparison unit; 274. an alarm feedback unit; 28. an intelligent diagnosis module; 281. a fault database; 282. a failure diagnosis method forming unit; 283. an algorithm unit; 284. a failure diagnosis model generation unit; 285. a diagnosis unit; 286. and an operating state prediction unit.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-5, the embodiment of the present invention provides a technical solution: the utility model provides a human eye fatigue degree monitoring system, including acquisition layer 1 and monitoring layer 2, acquisition layer 1 includes sensor module 11, signal conversion module 12 and first wireless communication unit 13, sensor module 11 includes flexible sensor 111 and piezoelectric sensor 112, the output of sensor module 11 is connected with the input of signal conversion module 12, and the output of signal conversion module 12 is connected with the input of first wireless communication unit 13, monitoring layer 2 includes second wireless communication unit 21, filter module 22, information management module 23, timing module 24, server 25, monitoring data analysis module 26, alarm module 27 and intelligent diagnosis module 28, the output of first wireless communication unit 13 is connected with the input of second wireless communication unit 21, the output of second wireless communication unit 21 is connected with the input of filter module 22, the output ends of the filtering module 22 and the timing module 24 are connected with the input end of the information management module 23, the monitoring data analysis module 26 and the intelligent diagnosis module 28 are connected with the server 25 in a bidirectional manner, the output end of the server 25 is connected with the input end of the alarm module 27, the filtering module 22 comprises a photoelectric noise database 221, a signal resolution unit 222, a photoelectric noise signal filtering unit 223 and a signal reduction unit 224, the output end of the photoelectric noise database 221 is connected with the input end of the signal resolution unit 222, the output end of the signal resolution unit 222 is connected with the input end of the photoelectric noise signal filtering unit 223, the output end of the photoelectric noise signal filtering unit 223 is connected with the input end of the signal reduction unit 224, the monitoring data analysis module 26 comprises a data analysis unit 261, a data classification unit 262 and a data analysis model establishment unit 263, the output end of the data analysis unit 261 is connected with the input end of the data classification unit 262, the output end of the data classification unit 262 is connected with the input end of the data analysis model establishment unit 263, the alarm module 27 comprises an early warning database 271, an early warning value setting unit 272, a data comparison unit 273 and an alarm feedback unit 274, the output end of the early warning database 271 is connected with the input end of the early warning value setting unit 272, the output end of the early warning value setting unit 272 is connected with the input end of the data comparison unit 273, the output end of the data comparison unit 273 is connected with the input end of the alarm feedback unit 274, the intelligent diagnosis module 28 comprises a fault database 281, a fault diagnosis method formation unit 282, an algorithm unit 283, a fault diagnosis model generation unit 284, a diagnosis unit 285 and an operating state prediction unit 286, the output ends of the fault database 281, the fault diagnosis method forming unit 282 and the algorithm unit 283 are all connected with the input end of the fault diagnosis model generating unit 284, the output end of the fault diagnosis model generating unit 284 is connected with the input end of the diagnosis unit 285, the output end of the diagnosis unit 285 is connected with the input end of the working state predicting unit 286, the influence of photoelectric noise on data transmission is greatly reduced by filtering the photoelectric noise through the filter module 22, the accuracy of data feedback is improved, the working state of the sensor is predicted by combining the transmitted data through the intelligent diagnosis module 28, diagnosis is performed when faults occur, the later maintenance work is facilitated, the monitoring data analyzing module 26 is used for analyzing the eye fatigue degree of a human body, the alarm module 27 alarms after a certain value is reached, is convenient for reminding the user to pay attention to rest.
And all that is not described in detail in this specification is well known to those skilled in the art.
When the intelligent skin monitoring device is used, the flexible sensor 111 tests related parameters of skin, the pressure of the piezoelectric sensor 112 becomes electricity, blink behaviors can be fed back in real time in a longer time, fed back data enter the filtering module 22 through the signal conversion module 12, the first wireless communication unit 13 and the second wireless communication unit 21, the signals are resolved by the signal resolution unit 222 in the filtering module 22, the photoelectric noise signal filtering unit 223 filters the data, the signal reduction unit 224 reduces the data, then the reduced data is transmitted to the information management module 23, the timing module 24 counts the time at the moment, the information management module 23 transmits the reduced data and the time data to the server 25, and the server 25 transmits the data to the monitoring data analysis module 26, the alarm module 27 and the intelligent diagnosis module 28 respectively;
the data analysis unit 261 in the monitoring data analysis module 26 analyzes the data, the data classification unit 262 classifies the data, the data analysis model establishment unit 263 establishes a data analysis model, and the data analysis model is transmitted back to the server 25, so that the observation and the intervention of staff are facilitated;
in the alarm module 27, the early warning value setting unit 272 sets an early warning value according to the early warning database 271 in advance, then the data comparison unit 273 performs data comparison after the alarm module 27 receives the data, and if the data is higher than the set value, the alarm feedback unit 274 performs alarm feedback;
after the intelligent diagnosis module 28 receives the data, the transmitted data, the fault database 281, the fault diagnosis method forming unit 282 and the algorithm unit 283 are combined, the fault diagnosis model generating unit 284 builds a fault diagnosis model, then the fault diagnosis unit 285 performs fault diagnosis on the fault diagnosis model, the diagnosis data is transmitted back to the server 25, if no fault exists, the data is transmitted to the working state prediction unit 286 for prediction, and the prediction data is transmitted back to the server 25, so that the observation and the intervention of staff are facilitated.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (2)
1. Human eye fatigue degree monitoring system, including gathering layer (1) and monitoring layer (2), its characterized in that: the acquisition layer (1) comprises a sensor module (11), a signal conversion module (12) and a first wireless communication unit (13), and the monitoring layer (2) comprises a second wireless communication unit (21), a filtering module (22), an information management module (23), a timing module (24), a server (25), a monitoring data analysis module (26), an alarm module (27) and an intelligent diagnosis module (28);
the filtering module (22) comprises a photoelectric noise database (221), a signal resolution unit (222), a photoelectric noise signal filtering unit (223) and a signal reduction unit (224), wherein the output end of the photoelectric noise database (221) is connected with the input end of the signal resolution unit (222), the output end of the signal resolution unit (222) is connected with the input end of the photoelectric noise signal filtering unit (223), and the output end of the photoelectric noise signal filtering unit (223) is connected with the input end of the signal reduction unit (224);
the intelligent diagnosis module (28) comprises a fault database (281), a fault diagnosis method forming unit (282), an algorithm unit (283), a fault diagnosis model generating unit (284), a diagnosis unit (285) and a working state predicting unit (286), wherein the output ends of the fault database (281), the fault diagnosis method forming unit (282) and the algorithm unit (283) are connected with the input end of the fault diagnosis model generating unit (284), the output end of the fault diagnosis model generating unit (284) is connected with the input end of the diagnosis unit (285), and the output end 286 of the diagnosis unit (285) is connected with the input end of the working state predicting unit (286);
the sensor module (11) comprises a flexible sensor (111) and a piezoelectric sensor (112), the output end of the sensor module (11) is connected with the input end of the signal conversion module (12), and the output end of the signal conversion module (12) is connected with the input end of the first wireless communication unit (13);
the output end of the first wireless communication unit (13) is connected with the input end of the second wireless communication unit (21), the output end of the second wireless communication unit (21) is connected with the input end of the filtering module (22), the output ends of the filtering module (22) and the timing module (24) are both connected with the input end of the information management module (23), the monitoring data analysis module (26) and the intelligent diagnosis module (28) are both connected with the server (25) in a bidirectional manner, and the output end of the server (25) is connected with the input end of the alarm module (27);
the monitoring data analysis module (26) comprises a data analysis unit (261), a data classification unit (262) and a data analysis model establishment unit (263), wherein the output end of the data analysis unit (261) is connected with the input end of the data classification unit (262), and the output end of the data classification unit (262) is connected with the input end of the data analysis model establishment unit (263).
2. The human eye fatigue monitoring system according to claim 1, wherein: the alarm module (27) comprises an early warning database (271), an early warning value setting unit (272), a data comparison unit (273) and an alarm feedback unit (274), wherein the output end of the early warning database (271) is connected with the input end of the early warning value setting unit (272), the output end of the early warning value setting unit (272) is connected with the input end of the data comparison unit (273), and the output end of the data comparison unit (273) is connected with the input end of the alarm feedback unit (274).
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