KR102278855B1 - Worker Identification Management Method through Real-Time of Bio-Signals and Location Monitoring Technology - Google Patents

Abstract

The present invention relates to a worker identification management method by real-time biosignal and location monitoring technology. With the present invention, it is possible to confirm whether a worker has conducted work in a designated place at a designated time by monitoring the worker's brainwave and location in real time. The present invention includes: a step (100) of registering a worker on a computer; a step (200) of registering the normal and work brainwaves of each worker registered on the computer; a step (300) of attaching a brainwave measuring device and a location detecting device to the worker at a work site; a step (400) of monitoring the worker's brainwave and location with a monitoring device connected to the computer; a step (500) of comparing the worker's work brainwave to the registered worker's work brainwave and location on the computer; and a step (600) of identifying the worker through the brainwave comparison step (500) on the computer.

Description

Worker Identification Management Method through Real-Time of Bio-Signals and Location Monitoring Technology

The present invention relates to a method for identifying and managing a worker who is working in a workplace by monitoring a worker wearing a biosignal measuring device such as an EEG in real time and checking biosignal data and location data.

In the case of a large plant, the scale is large, and there are many devices that operate under extreme environments such as high temperature and high pressure, and must be specially manufactured in accordance with safety regulations.

For example, in the case of a pressure vessel in a power plant, it must be manufactured and performed in accordance with the welding procedure in accordance with the ASME Sec.III code. In addition, in the case of welding workers and non-destructive inspectors, it is stipulated that only those with professional qualifications as welders/non-destructive inspectors in advance should perform the work.

However, since the product is manufactured in a remote factory, etc. and the scale is also large, it is difficult to supervise the work process in real time. There is no way to check even if a welder/non-destructive inspector who does not have professional qualifications works in this process.

In order to solve this problem, worker authentication technology can be applied. The technology for authenticating a person is required in various technical fields, and one of them is a technology for personal authentication through bio-signal measurement such as EEG measurement is being developed.

Although EEG has a relatively low spatial resolution, it is the cheapest, harmless to the human body, and has a high temporal resolution, so it is widely used. Recently, it is actively used in BCI (Brain Computer Interface) research.

As an example of authentication technology using EEG, a self-authentication system (hereinafter referred to as 'Prior Art 1') through EEG measurement is disclosed in Korean Patent Publication No. 10-1643354.

The identity authentication system shown in the prior art 1 includes an EEG measuring device, a noise removing device, a feature extracting device for extracting EEG features, an EEG data classification device, a control unit, and a transmission device.

As another example, an individual authentication method (hereinafter referred to as 'prior art 2') through EEG measurement is disclosed in Korean Patent Publication No. 10-1607432.

In the prior art 2, individual power characteristics are extracted from the EEG measured while performing various cognitive tasks within a short time, and the individual characteristics and the synchronization characteristics between channels are combined to form a network characteristic-based personal authentication method based on a personal authentication method. Personal authentication used includes registration recognition task presentation, brain wave measurement, channel power characteristic and inter-channel synchronization characteristic extraction, network characteristic extraction, and optimal frequency domain calculation data storage and comparison steps.

The personal authentication method through EEG measurement shown in the prior art 2 can extract high-level individual unique characteristics with a relatively small number of channels from the EEG obtained during various cognitive tasks within a short time, so that individual recognition targets can be expanded. There are advantages.

In the prior art 1 and 2, a technique for measuring the EEG of the subject to which the EEG measurement device is attached and authenticating the subject through signal processing and analysis is shown, but even using the prior art 1 and 2, it is possible to work It is still difficult to identify whether an operator is an operator who can properly perform a required work process at a prescribed place in the workplace.

Republic of Korea Patent Registration No. 10-1643354 (2016.07.27.) Republic of Korea Patent Registration No. 10-1607432 (2016.03.29.)

The present invention has been developed to solve the above problems, and real-time bio-signal and location monitoring that can check whether the operator performed work at a prescribed place at a prescribed time by monitoring the brain wave and location of the worker in real time An object of the present invention is to provide a method for managing worker identification through technology.

Another object of the present invention is to provide a method for managing worker identification through real-time bio-signals and location monitoring technology that can check whether a work defect is included in the work performed by monitoring the brain wave when the worker performs the work. .

Worker identification management method through real-time biosignal and location monitoring technology according to the present invention for solving the above object, the step of registering the information of the operator to the computer (100), the normal time and work of each registered worker Step (200) of registering the EEG at the time of the computer, the step of attaching the EEG measuring device and the position detecting device to the worker in the workplace (300), the step of monitoring the EEG and the position of the worker in the monitoring device connected to the computer (400) ), comparing the EEG at the time of the worker's work in the computer with the EEG and the position at the time of the worker's work registered in the computer (500), and the step of identifying the worker in the computer (600) may include have. At this time, the step of comparing the EEG during the operation of the operator in the computer with the EEG and the position of the registered operator at the time of the operation 500 includes the steps of checking whether the operator is a registered operator (530); determining (540) whether the operator is in a prescribed working position; and a step 550 of determining whether an EEG is included in the case of a work failure. In addition, the step of identifying the worker in the computer (600); The step of storing the worker monitored as unregistered in the unregistered worker identification unit provided in the computer (630); If it is monitored that the registered worker is a prescribed working position, storing the registered worker identification unit provided in the computer (610); If it is monitored that the registered worker is not a prescribed working location, storing the registered unqualified worker identification unit provided in the computer (640); When it is monitored that the EEG of the registered worker stored in the registered worker identification unit does not include the EEG when the work is defective, storing information in the registered worker normal work unit provided in the computer (611); And when it is monitored that the EEG of the registered worker stored in the registered worker identification unit includes the EEG when the work is defective, storing information in the registered worker defective work unit provided in the computer (612); includes; may be doing

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In addition, in the worker identification management method of the present invention, the step 500 of comparing the EEG at the time of the worker's work in the computer with the EEG and the location at the time of the registered worker's work is to check whether the worker is a qualified worker step 520 may be included.

Through the method for worker identification management through real-time bio-signal and location monitoring technology according to the present invention, while monitoring bio-signals and positions such as EEG signals of workers working in the workplace, it is compared with bio-signal information when working with registered workers in the workplace It is possible to improve the reliability of the work by identifying the workers who are working in the premises and clearly confirming that the identified workers are performing their tasks at the prescribed location or at the prescribed time, and accordingly, it is possible to improve the reliability of the work. It has the advantage of being able to prevent possible safety accidents in advance.

In addition, the worker identification management method according to the present invention can monitor and analyze the EEG characteristics during the worker's work to determine whether the worker is a worker with the qualifications to do the work, so that the worker is unqualified for work requiring professional qualifications It has the effect of eradicating the expedient act in which a worker works illegally in advance.

In addition, the worker identification management method according to the present invention can monitor and analyze EEG characteristics during the worker's work to determine whether a bad job is included while the worker performs the corresponding job, thereby improving the reliability of the job and , safety accidents, etc. can be prevented in advance.

1 is a block diagram of an EEG-based personal authentication system shown in prior art 1.
Figure 2 is a detailed block diagram of the brain wave-based personal authentication system shown in the prior art 2.
3 is a block diagram of an operator identification management system through real-time bio-signals and location monitoring technology according to the present invention.
4 is a flowchart of a method for managing worker identification through real-time bio-signals and location monitoring technology according to the present invention.
Figure 5 is a detailed flowchart of the step of preparing for EEG and position and worker identification management during operation.

Hereinafter, the present invention will be described with reference to the accompanying drawings. However, the present invention may be embodied in several different forms, and thus is not limited to the embodiments described herein.

Throughout the specification, when it is said that a part is "connected (connected, contacted, coupled)" with another part, it is not only "directly connected" but also "indirectly connected" with another member interposed therebetween. "Including cases where In addition, when a part "includes" a certain component, this means that other components may be further provided without excluding other components unless otherwise stated.

The terms used herein are used only to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In this specification, terms such as "comprises" or "have" are intended to designate that the features, numbers, steps, operations, components, parts, or combinations thereof described in the specification exist, but one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Hereinafter, a preferred embodiment of the present invention will be described with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement it.

3 is a flowchart of a method for managing worker identification through real-time bio-signals and location monitoring technology according to the present invention.

As shown in FIG. 3 , the method for managing worker identification through real-time bio-signals and location monitoring technology according to an embodiment of the present invention comprises: a worker registration step 100 of registering worker information in a computer; registering a worker brainwave in the computer (200); Attaching the EEG and position sensing device of the worker in the workplace (300); Monitoring the EEG and the location of the operator attached to the EEG and the position sensing device in the monitoring device connected to the computer (400); Preparing (500) for brain waves and location during the operation of the operator in the computer; and identifying and managing (600) the operator at the computer.

The worker registration step 100 is a step of registering worker information in a computer.

The worker registration step 100 is a step of registering information of workers who have the qualification to perform at least one job among various jobs performed at the corresponding workplace in the computer. At this time, the information of the worker may also include a prescribed position where each worker performs the work.

In the case of parts or devices of large plants, for example, pressure vessels in power plants, they must be manufactured while complying with welding procedures in accordance with the ASME Sec.III code, and in the case of welders and non-destructive inspectors, a welder in advance /Non-destructive inspection It is stipulated that only persons with professional qualifications should perform the work.

The worker registration step 100 is a step of registering information of workers who are put into production while being a worker who has the qualifications to perform the work required in each work process as described above.

In this case, the qualified worker may mean a worker who has the expertise to perform a specific task according to the requirements or a worker who has professional qualifications, etc. while having the expertise.

On the other hand, in the present invention, a worker who does not have the expertise to perform the work is referred to as an 'unqualified worker', and the unqualified worker means a worker who does not have the ability to perform any of the various tasks to be performed in the corresponding workplace. Therefore, if it is confirmed that an unqualified worker is performing a job instead of a qualified worker, it is necessary to immediately stop the corresponding job.

In addition, in the present invention, a worker who has expertise to perform at least one of the worker's tasks, but has not registered, is referred to as an 'unregistered worker', and an unregistered worker may perform the corresponding work, but is not registered, so the corresponding task Since the worker for the job is not specified, after stopping the corresponding job, it will be necessary to decide whether to let the 'unregistered worker' continue to perform the job or replace it with a registered worker to complete the job.

In addition, in the present invention, the 'registered worker' can perform only the prescribed work, and when the 'registered worker' performs a task other than the prescribed task, a worker who does not have the expertise to perform the task, that is, an unqualified worker corresponds to At this time, the 'registered worker' is referred to as a 'registered unqualified worker' for the corresponding job, and the 'registered unqualified worker' means a worker who is not capable of performing the corresponding job. Therefore, if it is confirmed that a ‘registered unqualified worker’ is performing a task for a specific task, it is necessary to immediately stop the task even at this time.

When performing worker identification management, safety and productivity problems may occur if unqualified workers or unregistered workers as described above occur. Therefore, it is desirable to register workers without omission for workers performing work in the corresponding workplace. will be.

At this time, it would be more preferable to clearly define the work that can be performed by each worker that can be performed by each worker to prevent the occurrence of unqualified workers according to the work in advance.

Next, the worker EEG registration step 200 is a step of registering the EEG characteristics of each worker registered in the worker registration step 100 in the computer.

The worker EEG registration step 200 includes a step 210 of measuring an EEG during normal operation and a step 220 of measuring an EEG during work for each worker, as shown in FIG. 4 .

Brain waves are typically delta (0.5 to 4.99 Hz), theta (5.7 to 7.99 Hz), alpha (8 to 11.99 Hz), beta (12 to 35 Hz), and gamma (30 to 50 Hz) waves, depending on the range of frequencies. is divided into

Delta waves mainly appear during deep sleep in normal people or in newborn babies, theta waves appear mainly in the process leading to emotional stability or sleep, and alpha waves appear mainly in a relaxed state such as relaxation. Stable alpha waves appear when you close your eyes and are in a true state, and when you open your eyes and look at an object or become mentally excited, alpha waves are suppressed.

Beta waves mainly appear in the frontal part of the brain, appearing during all conscious activities such as waking and talking, and also appear predominantly during anxious or nervous conditions, or complex computational processing.

Gamma waves vibrate faster than beta waves, and are either emotionally agitated or deeply related to high-level cognitive information processing such as reasoning and judgment.

EEG with these various characteristics changes even when the subject opens or closes his/her eyes, and changes occur even if the subject's body movements or hearing or tactile differences occur, and each individual has different characteristics. .

The normal EEG measurement step 210 is a step of measuring EEG in a state in which the operator does not work.

In the normal EEG measurement step 210, a method of measuring EEG in a stable state is also possible, but a method of measuring EEG in a state before work wearing an EEG measuring device in a workplace is also possible.

At this time, the EEG is measured in each situation before the actual work, such as the state with the eyes open, the state with the eyes closed, and each worker preparing the equipment for his or her work, for example, welding equipment, etc. It will also be possible

The normally measured EEG may have a common part for each worker, but there is a difference for each individual, so it may be used as information for identifying the worker.

Next, the EEG measurement step 220 during work is a step of measuring EEG when the worker actually performs his/her own work, for example, a welding work or a non-destructive test work, in the corresponding workplace.

When each worker performs his/her task, since it is performed in a state of concentration so that he/she can perform the task properly, the characteristics of the EEG are clearly different from the EEG measured in the usual way, and the degree of change and the characteristics of the change are also shown. Each worker is different.

This step is to measure EEG during work and register it in the computer, so it is not a product or material for actual work in the workplace, but a material for practice, for example, a material for qualification test in the qualification test for a welder or non-destructive inspector. It will also be possible to measure brain waves while performing and register them in the computer.

On the other hand, since this step is a step for storing the characteristics of the worker's EEG in the computer, it will be possible to store these characteristics by distinguishing the EEG when the operator performs a normal operation and the EEG when a defect occurs during the operation. .

When an operator normally performs a task in charge, the EEG exhibits common characteristics until the task is completed, and after the task is completed, the EEG characteristic appears in a direction in which concentration is relaxed.

On the other hand, if a defect occurs while the worker who is measuring EEG for registration is performing his/her task, the defect is recognized, and the EEG characteristic distinct from the EEG characteristic during normal work appears due to the recognition of the work defect.

If the worker is an unqualified worker who cannot recognize the defect during work, the defect may not be recognized and there may be no change in the EEG. However, in the present invention, since the operator who registers the characteristics of the EEG is targeted at the registered operator to perform the corresponding task, the registered operator can recognize whether the task is defective in the task prescribed to be sufficiently performed, thereby affecting the task failure Distinctive EEG features may be present.

In this way, it is possible to measure an EEG at a normal time before work and an EEG at the time of work for each worker, and register various EEG characteristics in each state in the computer.

At this time, since the measured EEG typically includes noise, a noise removal step 230 may be additionally provided as shown in FIG. 4 .

The noise removing step 230 may be implemented by allowing the measured EEG signal to pass through the noise removing device.

The noise removing device typically includes at least one filter selected from among filters such as a low pass filter, a high pass filter, a band pass filter, and a notch filter. After removing the noise included in the EEG signal measured by using such a noise removing device, EEG features can be extracted.

As shown in FIG. 4 , the EEG from which noise has been removed may undergo an EEG feature extraction step 240 to extract various EEG features.

The EEG feature extraction step 240 is a step of extracting various EEG features using a feature extraction device capable of extracting various information in the frequency domain by converting the EEG signal from which the noise of the time domain is removed into the frequency domain. .

As shown in prior art 1 and 2, the EEG characteristic includes various characteristics, for example, average power spectrum, peak frequency band, relative power intensity for each EEG region, correlation for each measurement channel, similarity, directionality, coherence, phase characteristic and There is a causal relationship, and some or all of these may be registered as a characteristic of EEG.

The noise removal device and the feature extraction device for noise removal and feature extraction of EEG may be provided in the EEG measuring device or a separate device.

Next, the step of forming a database 250 is a step of storing various EEG characteristic information extracted for each worker in a storage unit provided in the computer. At this time, it will be more preferable to match and store the information of each registered operator and the derived EEG characteristic information in the storage unit.

Through the steps described above, it is possible to complete the registration of EEG characteristic information during normal and prescribed tasks of the registered worker.

When the operator registration and the operator's EEG registration are completed in this way, the preparation to identify the operator in the actual workplace is complete.

The step of attaching the EEG and position detecting device 300 of the worker shown in FIG. 3 is a step of attaching the EEG measuring device and the location detecting device to the worker who wants to work in the actual workplace, that is, the worker who needs identification.

The EEG measuring device may be a headset-type or band-type device to be worn on the worker's head, and the position sensing device may be attached to the body including the head, but is not limited thereto. And a device that is configured to detect its location will suffice.

At this time, it would be desirable to enable the EEG measurement device and the position sensing device to communicate wirelessly so as to be received by a monitoring device to be described later and to be able to contrast with the registered EEG and the registered worker examined in the above step.

For this purpose, it is preferable that a wireless transmission device capable of wirelessly transmitting a signal is additionally configured in the EEG measuring device and the position detection device. The wireless transmission device may include an RF transmitter capable of transmitting and receiving even at a relatively long distance, but is not limited thereto, and a device capable of wireless communication at a distance between an operator and a monitoring device to be described later will be sufficient.

Next, the EEG and position monitoring step 400 shown in FIG. 3 is a step of monitoring the EEG and the position sensing device with a monitoring device connected to the computer when the worker moves to the workplace and performs the task in charge to be.

EEG and location monitoring can be monitored by receiving each signal from a monitoring device connected to a computer.

Since the monitoring device may be far away from the workplace where the operator performs the work, it is preferable that a wireless receiving device capable of wirelessly receiving the signal of the EEG measuring device and the position detecting device is additionally configured, and the wireless The reception device may include an RF receiver, but is not limited thereto, and any device capable of receiving the signal of the wireless transmission device may be sufficient.

It is preferable that an input unit and a display unit are formed in the monitoring device, and at least one of time domain data about the operator's brain wave and location, time domain data from which noise is removed, and frequency domain data from which EEG features are extracted can be selected and displayed. It would be desirable to be configured so that

In addition, it would be preferable that the monitoring device be configured to display the EEG characteristic information of each operator registered in the storage unit together, and it would be preferable that a control unit capable of controlling it is also provided.

Next, as shown in FIG. 3 , there is an EEG and position comparison step 500 and an operator identification management step 600 through which the operator works on the computer.

EEG and position comparison step 500 when the operator works on the computer is the EEG preparation step 510 when the operator works on the computer, as shown in FIG. 5 , the qualification worker check step 520, the registered worker check step ( 530), whether or not the prescribed work position 540, and whether or not a work defect is included may include a check step (550).

In the computer, the worker identification management step 600 is a step of deriving the identification result for the currently monitored worker through the EEG and location comparison step during the operation, as shown in FIG. 5, and is stored in the registered worker identification unit of the computer. Step 610, storing in the unqualified worker identification unit (620), storing in the unregistered worker identification unit (630), and storing in the registered unqualified worker identification unit (640), each result is determined by the monitoring This step is indicated on the display unit of the device. At this time, as shown in FIG. 5, the registered worker of the prescribed work location stored in the step 610 of storing in the registered worker identification unit performed a task containing a defect or whether the operator to monitor additionally performed the task normally It may include a step (611) of dividing and storing the registered worker normal work unit of the computer (611) or a step (612) of storing the registered worker defective work unit.

Looking at each step in detail with reference to FIG. 5 , first, the step of preparing for EEG when working on a computer 510 is the EEG when the worker works and the EEG of each worker registered in the worker EEG registration step 200 . It is a stage of preparation. That is, it is a step of comparing the EEG characteristics monitored in real time with the EEG characteristics of each registered worker registered in the storage unit.

The EEG preparation step 510 at the time of the operation includes a step 520 of checking whether a qualified worker is a qualified worker on a computer, a step of checking whether a registered worker on a computer 530, a step of checking whether a prescribed work position on the computer 540, and a malfunction of the computer It may include a checking step 550 .

The step of checking whether the worker is qualified ( 520 ) is a step of checking in the computer whether the worker being monitored is a worker having the qualification to perform the corresponding job.

For example, welding work or welding inspection work of a large pressure vessel in a nuclear power plant must be performed by a professionally qualified worker. Qualification at this time may be a certificate, but it also means a worker with expertise in the relevant work. Workers with expertise in the work must perform the required normal work when performing welding or welding work inspection, etc., and accordingly, EEG has specific characteristics, and although there may be differences between registered workers specifically, There are EEG features common to workers.

However, if the worker does not have expertise and is not qualified for the work, he/she cannot grasp the main characteristics of the work, so it is to perform welding or inspect the welding work without grasping the gist of the normal work. There will be a big difference in EEG characteristics with workers with expertise.

That is, in the verification step 520 of whether the worker is qualified, the EEG of the currently monitored worker (the worker who is working in the workplace) is clearly different from the common EEG characteristics of registered workers who have the expertise and qualifications to perform the task. By determining whether or not, it is possible to determine whether the worker currently performing the job is a qualified worker.

Through this, if it is confirmed that the worker currently being monitored is not a registered worker and not a qualified worker, the worker corresponds to an unqualified worker, and as shown in FIG. 5, storing in the unqualified worker identification unit of the computer (620) , and generates an alarm for this. At this time, the alarm may be displayed on the display unit of the monitoring device, or implemented to generate an alarm sound together.

If an unqualified worker is performing work, it is desirable to immediately stop the work, replace it with a registered worker, and proceed with the work. Through this step, it is possible to prevent an unqualified worker from performing work in the relevant workplace in advance. have.

Next, the step 530 of checking whether the computer is a registered worker is a step of preparing for the EEG characteristics of the worker registered in the storage unit when the currently monitored worker is recognized as a qualified worker.

That is, it is a step of identifying the currently monitored worker as a specific person among registered workers in preparation for the EEG information during the operation of the currently monitored worker and the EEG information during the operation of each worker registered in the storage unit.

Through this, if it is confirmed that it matches the registered EEG information of one of the registered workers, the worker who performed a specific task at the corresponding location at the corresponding time is specified as one of the registered workers.

In this case, for the specified registered worker, a step 540 of checking whether the specified job location is located in the computer is performed.

Checking whether the prescribed work location step 540 is a step of confirming whether the location or place currently working is a prescribed location for the specified registered worker to work.

Through this step, it can be confirmed whether the identified registered worker is performing work at a prescribed place or location that can be performed, and if the currently monitored location or location corresponds to the identified registered worker's work location or location, Since the registered worker performs work at a prescribed place, the result is stored in the registered worker identification unit of the computer as shown in FIG. 5 ( 610 ), and may be displayed on the display unit of the monitoring device There will be.

On the other hand, there may not be the same EEG information as the registered EEG information of the workers currently monitored by the registered workers.

This corresponds to the case where the currently monitored worker is a worker with expertise in the corresponding job, but is not a registered worker, that is, an unregistered worker. In this case, as shown in FIG. 5 , a step 630 of storing in the unregistered worker identification unit of the computer may be performed, and this may be displayed on the display unit of the monitoring device. In addition, in this case, it would be more preferable to configure the alarm to inform that the currently unregistered worker is performing the work.

When the unregistered worker is performing the work, it is more preferable to stop the work and then proceed with the work after determining whether the unregistered worker will continue to perform the work. For example, if it is determined that the unregistered operator has sufficient expertise to perform the task, the task is continued. If it is determined that the unregistered operator does not have enough expertise to perform the task, the task is replaced by a registered operator. will be able to do

Next, the step 550 of determining whether the computer shown in FIG. 5 includes a defective operation can be additionally performed when the monitoring worker is identified as one of the registered workers working at a prescribed location or place. there is a step

If the worker is identified as one of the registered workers working in a prescribed location or place, while continuing EEG monitoring, check whether EEG characteristics when a work defect occurs in EEG characteristic information appear, and It is a step to check whether the work contains defects.

Registered workers with expertise perform their tasks with a certain level of concentration or more. At this time, a work defect may occur during work, and when a work defect occurs, the worker has expertise in the work, so that the defect can be identified in real time, which greatly affects the change in EEG characteristics.

Therefore, while monitoring the EEG during the worker's work, it is possible to determine whether there is a change in EEG characteristic information and primarily determine whether a defect is included in the corresponding work.

At this time, although the operator may not recognize all the cases in which the defect has occurred, it is possible to identify the occurrence of the defective work for the work recognized by the operator as a defect during the operation.

That is, this step is to determine whether or not work defects are included from the operator's point of view, and if the EEG characteristic of the work failure does not appear in the EEG of the worker being monitored, the information is stored in the normal work unit of the registered worker of the computer as shown in FIG. Step 611 may be performed, and this may be displayed on the display unit of the monitoring device.

On the other hand, when the EEG characteristic of a work failure appears in the EEG of the worker being monitored, as shown in FIG. 5 , a step 612 of storing information in the registered worker defective work unit of the computer is performed, and this is performed on the display unit of the monitoring device. may be displayed.

In this way, when the work recognized as a work defect is inspected more precisely, it is possible to prevent a safety problem from occurring in advance.

In the EEG and location comparison step 500 and worker identification management step 600 when working on the computer looked at above, it is possible to identify the registered worker by checking several steps, whether the registered worker is performing a normal operation, poor work Not only will it be possible to determine whether or not it is included, but also unqualified workers and unregistered workers will be identified.

The description of the present invention described above is for illustration, and those of ordinary skill in the art to which the present invention pertains can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a distributed manner, and likewise components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention.

100: worker registration step 200: operator EEG registration step
210: normal EEG measurement step 220: EEG measurement step at work
221: normal work EEG measurement step 222: bad work EEG measurement step
230: noise removal step 240: EEG feature extraction step
250: Databaseization step 300: EEG and location sensing device attachment step
400: EEG and location monitoring phase
500: EEG non-position contrast stage when working
510: EEG preparation during work 520: Check whether the worker is qualified
530: Check whether a registered worker is present
540: Check whether a prescribed action is located
550: Step to check whether the operation contains a defect
600: worker identification management step 610: registered worker identification unit
611: Registered Worker Normal Work Unit 612: Registered Operator Bad Work Unit
620: unqualified worker identification unit 630: unregistered worker identification unit
640: registered unqualified worker identification unit

Claims (3)

Registering the operator's information to the computer (100);
Registering the EEG in the computer during normal and working times of each of the registered workers (200);
Attaching the EEG measuring device and the position sensing device to the worker in the workplace (300);
Monitoring the EEG and location of the operator in a monitoring device connected to the computer (400);
Comparing the EEG when the operator works in the computer with the EEG and the location of the operator registered in the computer 500; and
In the operator identification management method through real-time bio-signals and location monitoring technology comprising; identifying the operator in the computer (600),
Comparing the EEG during the operation of the operator in the computer with the EEG and the location of the registered operator at the time of operation (500) is,
checking whether the worker is a registered worker (530);
determining (540) whether the operator is in a prescribed working position; and
Including the; step 550 to determine whether or not to include an EEG when the work is faulty;
Identifying the operator in the computer (600);
Storing the monitored worker as unregistered in the unregistered worker identification unit provided in the computer (630);
If it is monitored that the registered worker is a prescribed working position, storing the registered worker identification unit provided in the computer (610);
If it is monitored that the registered worker is not a prescribed working location, storing the registered unqualified worker identification unit provided in the computer (640);
If it is monitored that the EEG of the registered worker stored in the registered worker identification unit does not include the EEG when the work is defective, storing information in the registered worker normal work unit provided in the computer (611); and
When it is monitored that the EEG of the registered worker stored in the registered worker identification unit includes the EEG when the work is defective, storing information in the registered worker defective work unit provided in the computer (612); including; Worker identification management method through real-time biosignal and location monitoring technology, characterized in that.
delete According to claim 1,
Comparing the EEG during the operation of the operator in the computer with the EEG and the location of the registered operator at the time of operation (500) is,
Worker identification management method through real-time bio-signals and location monitoring technology, comprising the step (520) of checking whether the worker is a qualified worker.

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