CN111700585A - Human eye fatigue degree monitoring system - Google Patents
Human eye fatigue degree monitoring system Download PDFInfo
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- CN111700585A CN111700585A CN202010723595.9A CN202010723595A CN111700585A CN 111700585 A CN111700585 A CN 111700585A CN 202010723595 A CN202010723595 A CN 202010723595A CN 111700585 A CN111700585 A CN 111700585A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 48
- 208000003464 asthenopia Diseases 0.000 title claims abstract description 27
- 238000003745 diagnosis Methods 0.000 claims abstract description 47
- 238000007405 data analysis Methods 0.000 claims abstract description 34
- 238000004891 communication Methods 0.000 claims abstract description 24
- 238000001914 filtration Methods 0.000 claims abstract description 23
- 238000006243 chemical reaction Methods 0.000 claims abstract description 12
- 238000000034 method Methods 0.000 claims description 13
- 230000005540 biological transmission Effects 0.000 abstract description 7
- 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
- 208000003556 Dry Eye Syndromes Diseases 0.000 description 1
- 206010013774 Dry eye Diseases 0.000 description 1
- 206010047513 Vision blurred Diseases 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 239000012141 concentrate Substances 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
- 230000009467 reduction Effects 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
- 230000009978 visual deterioration Effects 0.000 description 1
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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, the filtering module comprises a photoelectric noise database, a signal distinguishing unit, a photoelectric noise signal filtering unit and a signal restoring unit, and the invention relates to the technical field of eye fatigue monitoring. This human eye fatigue degree monitoring system filters photoelectric noise through being equipped with filter module, greatly reduced photoelectric noise to data transmission's influence to improved data feedback's accuracy, through being equipped with intelligent diagnosis module, the data that combine the transmission predicts 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
Asthenopia is a common ophthalmic disease, and dry eyes, sour eyes, blurred vision and even visual deterioration caused by asthenopia directly influence the work and life of people. The eyestrain is mainly caused by that when people concentrate on watching screens of electronic products such as televisions, computers or mobile phones and the like at ordinary times, the blinking frequency of eyes is reduced, the secretion of tears is correspondingly reduced, and meanwhile, a blinking screen strongly stimulates eyes. Eye fatigue can also cause and aggravate various eye diseases. The best way to relieve eye fatigue is to let the eyes rest.
The existing monitoring system for the human eye fatigue degree is generally used for monitoring and feeding back through a sensor, but diagnosis and working state prediction when the sensor fails are lacked, and data fed back by the sensor is easily influenced 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 purpose, the invention is realized by the following technical scheme: the human eye fatigue degree monitoring system 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, and 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.
Preferably, the filtering module comprises a photoelectric noise database, a signal distinguishing 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 distinguishing unit, the output end of the signal distinguishing 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 payroll state prediction unit, wherein the output ends of the fault database, the fault diagnosis method forming unit and the algorithm unit are all 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 payroll state prediction unit.
Preferably, the sensor module comprises a flexible sensor and a piezoelectric sensor, an output end of the sensor module is connected with an input end of the signal conversion module, and an output end of the signal conversion module is connected with an 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 two-way 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 filters photoelectric noise through being equipped with filter module, greatly reduced photoelectric noise to data transmission's influence to improved data feedback's accuracy, through being equipped with intelligent diagnosis module, the data that combine the transmission predicts sensor operating condition, and diagnose when breaking down, made things convenient for the maintenance work in later stage.
(2) This human eye fatigue degree monitoring system, through the monitoring of flexible sensor and piezoelectric sensor, monitoring data analysis module carries out the analysis to monitor human eye fatigue degree, report to the police by alarm module after reaching a definite value, be convenient for remind the user to pay attention to the rest.
Drawings
FIG. 1 is a schematic block diagram of the system of the present invention;
FIG. 2 is a functional block diagram of a filter module of the present invention;
FIG. 3 is a schematic block diagram of a monitor data analysis module according to the present invention;
FIG. 4 is a functional block diagram of the alarm module of the present invention;
FIG. 5 is a functional block diagram of the intelligent diagnostic module of the present invention.
In the figure, 1, 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. a monitoring 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 establishing 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 fault diagnosis method forming unit; 283. an arithmetic unit; 284. a fault diagnosis model generation unit; 285. a diagnostic unit; 286. and a payroll state prediction unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, an embodiment of the present invention provides a technical solution: a human eye fatigue degree monitoring system comprises a collection layer 1 and a monitoring layer 2, wherein the collection layer 1 comprises a sensor module 11, a signal conversion module 12 and a first wireless communication unit 13, 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, the output end of the signal conversion module 12 is connected with the input end of the first wireless communication unit 13, 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 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 information management module 23, the monitoring data analysis module 26 and the intelligent diagnosis module 28 are all in bidirectional connection with the server 25, the output end of the server 25 is connected with the input end of the alarm module 27, the filter module 22 includes a photoelectric noise database 221, a signal resolution unit 222, a photoelectric noise signal filter unit 223 and a signal restoration 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 filter unit 223, the output end of the photoelectric noise signal filter unit 223 is connected with the input end of the signal restoration unit 224, the monitoring data analysis module 26 includes 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 establishing unit 263, the alarm module 27 includes 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 includes 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 payroll state predicting unit 286, 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, and the output of the diagnostic model of the trouble 284 is connected with input of the diagnostic unit 285, the output of the diagnostic unit 285 is connected with input of the salary state prediction unit 286, through being equipped with the filter module 22, filter the photoelectric noise, greatly reduce the influence of the photoelectric noise on data transmission, thus has improved the accuracy of data feedback, through being equipped with the intelligent diagnosis module 28, combine the data of transmission to predict the sensor operating condition, and diagnose when breaking down, the maintenance work in later stage has been made things convenient for, through the monitoring of flexible sensor 111 and piezoelectric sensor 112, the monitoring data analysis module 26 analyzes, thus monitor the fatigue degree of human eyes, report to the police by the alarm module 27 after reaching a definite value, be convenient for remind the user to pay attention to the rest.
And those not described in detail in this specification are well within the skill of those in the art.
When the device is used, the flexible sensor 111 tests relevant parameters of skin, the pressure of the piezoelectric sensor 112 is changed into electricity, blink behaviors can be fed back in real time in a long time, the fed back data enters the filtering module 22 through the signal conversion module 12, the first wireless communication unit 13 and the second wireless communication unit 21 and is distinguished by the signal distinguishing unit 222 in the filtering module 22, the photoelectric noise signal filtering unit 223 filters the fed back data, the signal restoring unit 224 restores the fed back data, the restored data are transmitted to the information management module 23, the timing module 24 performs timing at the moment, the information management module 23 transmits the restored data and 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, then the data classification unit 262 classifies the data, then the data analysis model establishing unit 263 establishes a data analysis model, and then the data analysis model is transmitted back to the server 25, so that the observation and the intervention of the working personnel are facilitated;
in the alarm module 27, an early warning value setting unit 272 sets an early warning value according to an early warning database 271 in advance, then after the alarm module 27 receives data, a data comparison unit 273 performs data comparison, and if the data is higher than the set value, an 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 establishes a fault diagnosis model, then the fault diagnosis model is subjected to fault diagnosis by the diagnosis unit 285, the diagnosis data is transmitted back to the server 25, if no fault exists, the data is transmitted to the payroll 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 working personnel are facilitated.
It is noted that, herein, relational terms such as first and second, and the like may be 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. Also, 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 appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. A human eye fatigue degree monitoring system comprises an acquisition layer (1) and a monitoring layer (2), and is 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).
2. The system for monitoring the degree of eye fatigue of a human according to claim 1, wherein: the filtering module (22) comprises a photoelectric noise database (221), a signal distinguishing unit (222), a photoelectric noise signal filtering unit (223) and a signal restoring unit (224), wherein the output end of the photoelectric noise database (221) is connected with the input end of the signal distinguishing unit (222), the output end of the signal distinguishing 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 restoring unit (224).
3. The system for monitoring the degree of eye fatigue of a human according to claim 1, wherein: the monitoring data analysis module (26) comprises a data analysis unit (261), a data classification unit (262) and a data analysis model establishing 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 establishing unit (263).
4. The system for monitoring the degree of eye fatigue of a human 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).
5. The system for monitoring the degree of eye fatigue of a human according to claim 1, wherein: 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 payroll 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 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), and the output end of the diagnosis unit (285) is connected with the input end of the payroll state predicting unit (286).
6. The system for monitoring the degree of eye fatigue of a human according to claim 1, wherein: 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).
7. The system for monitoring the degree of eye fatigue of a human according to claim 1, wherein: 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 of filter module (22) and timing module (24) all is connected with the input of information management module (23), monitoring data analysis module (26) and intelligent diagnosis module (28) all realize two-way connection with server (25), and the output of server (25) is connected with the input of alarm module (27).
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| JP2011120887A (en) * | 2009-11-12 | 2011-06-23 | Panasonic Corp | Eye potential measuring device, ophthalmic diagnosis apparatus, visual line detector, wearable camera, head-mounted display, electronic glasses, and eye potential measuring method, and program |
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