WO2023210889A1 - Kiosk system for non-face-to-face supply of specimen ampoules and method thereof - Google Patents

Abstract

The present invention relates to a kiosk system for automatically supplying specimen ampoules and a method thereof. The kiosk system automatically supplies specimen ampoules by using an automatic specimen ampoule supply kiosk device comprising: a housing; a touch panel that displays preset content on one side of the outer surface of the housing and detects touch inputs of a user; and a specimen ampoule inlet and outlet provided on the other side of the outer surface of the housing. The kiosk system comprises: a server unit that connects to a hospital server and transmits and receives patient information, a questionnaire form, a questionnaire result, and disease information material that are stored in advance; a patient information collection unit that captures an identification card image of a patient and collects personal information about the patient; a touch panel control unit that controls the state of the screen of the touch panel on the basis of an image captured by a user recognition camera, displays content when the patient is positioned facing the touch panel by means of the user recognition camera, and converts the display screen on the basis of the patient's touch input; a specimen target determination unit that determines whether the patient is a specimen collection target according to the questionnaire result filled by the patient; an ampoule supply unit that, when the patient is the specimen collection target, provides a specimen ampoule inscribed with the patient information; and a health care provider calling unit that transmits a call signal to a terminal of a health care provider in response to the specimen collection method, the filling of the questionnaire, and at least one request among a face-to-face treatment request and an emergency patient assistance request from the patient.

Description

Non-face-to-face sample ampoule supply kiosk system and method

The present invention relates to a sample ampoule supply kiosk system. More specifically, a non-face-to-face sample ampoule supply kiosk that collects patient information through ID cards and personal mobile phones, transmits a call signal to a clinician, and supplies ampoules to diagnose and manage infectious diseases. It relates to systems and methods.

Recently, Corona, the most representative infectious disease that has occurred in modern society, has been attracting people's attention as a crisis has been declared and a number of deaths have occurred worldwide.

However, now that more than two years have passed since the coronavirus pandemic, we are gradually moving toward a declaration of its end through the development of various vaccines and treatments.

Due to the risk of global infectious diseases such as Corona, many people have increased social interest in infectious disease management, and as concerns have increased about preventing infectious diseases that may occur in the future, technological advancements in health administration are required.

The above demands for technological development in health administration require top priority the technical development of non-face-to-face medical treatment equipment that can minimize infection and reduce the possibility of infection of medical staff as much as possible.

Meanwhile, kiosk refers to an unmanned information provision terminal, and is a general term for unmanned terminals installed in public places by exhibition halls, banks, shopping malls, and institutions so that the public can easily use them for information provision services and unmanned automation of work.

Most kiosk devices adopt a touch screen that allows hands to touch the screen rather than using a keyboard, providing easy step-by-step search for information services and a large screen at adult eye level, making it easy for the public to use. Representative examples include restaurants. The user's order can be computerized and provided to the kitchen, or services can be provided through devices installed in public facilities that provide information and are combined.

In addition, kiosks are suitable for non-face-to-face treatment because they reduce manpower through unmanned and automated information services and work and are not greatly restricted by location and time.

Therefore, non-face-to-face treatment management software is implanted in the kiosk terminal to provide information related to the infectious disease and guide treatment procedures to patients with infectious diseases or suspected infectious diseases, and provide audio output, video output, print output, and ampoules depending on the patient's case. Research is required on an automatic sample ampoule supply kiosk system and method that can perform non-face-to-face treatment without a resident person.

The purpose of the present invention is to provide medical services that improve patient convenience by providing patient information from a management server by providing an image capture device in a kiosk system to recognize ID cards.

In addition, the purpose is to prevent infection of medical personnel by suppressing contact between patients and medical staff through guidance using a kiosk system.

In addition, the purpose is to reduce the fatigue of medical personnel required for sample collection by supplying sample ampoules to patients through a kiosk system after determining whether patients who have filled out a questionnaire are eligible for sample collection.

A non-face-to-face sample ampoule supply kiosk system and method according to an embodiment of the present invention includes a housing, a touch panel for displaying preset content on one side of the outer surface of the housing and detecting a user's touch input, and a touch panel provided on the other side of the outer surface of the housing. In the kiosk system that automatically supplies sample ampoules using a sample ampoule automatic supply kiosk device including a sample ampoule inlet and outlet, it connects to the hospital server to transmit and receive pre-stored patient information, questionnaire form, questionnaire results, and disease information data. A server unit that captures the patient's ID card image and collects the patient's personal information, and controls the screen state of the touch panel based on the image captured through the user recognition camera. When the patient is positioned opposite the touch panel, a touch panel control unit that displays preset content and switches the display screen based on the patient's touch input, whether or not a sample is to be collected in response to the results of a questionnaire written by the patient. A sample subject determination unit that determines, if the patient is a subject of sample collection, an ampoule provider unit that provides a sample ampoule with patient information written on it, and at least one of the following: a method of collecting a sample from the patient, filling out the questionnaire, requesting face-to-face treatment, and requesting help for an emergency patient. It may include a medical practitioner call unit that transmits a call signal to the medical practitioner's terminal in response to one request.

In addition, the screen brightness of the touch panel is controlled based on the illuminance data collected from the illuminance sensor provided on the upper side of the touch panel, and when the illuminance data is below a preset reference value, the screen brightness of the touch panel is set to a preset initial value. is controlled to maintain, and when the illuminance data exceeds the reference value and the patient is recognized at a position opposite the touch panel in response to the user recognition camera for a preset time, the screen brightness of the touch panel is adjusted to It is automatically adjusted to the maximum value, and even if the illuminance data exceeds the standard value, if the patient is not recognized in the position facing the touch panel through the user recognition camera for a preset time, the screen brightness of the touch panel is adjusted to the maximum value. It can be automatically adjusted to the lowest value.

In addition, the patient information collection unit further provides an ID card recording unit provided inside the kiosk system and includes an ID card input port, an image capture device, an illumination sensor, and a lighting device, and the patient's ID card image captured by the ID card capture unit is used to obtain the ID card image. We collect at least one or more patient information among the patient's name, resident registration number, address, date of initial issuance, license number, and date of first license acquisition, and determine whether the collected patient information matches the patient information stored in the server to identify new or existing patients. Can be classified as a patient.

In addition, the patient information collection unit includes an ID photographing step of photographing the ID card placed by the patient on the imaging device of the kiosk system, and collecting photo location, reflection pattern, color and size information of the ID card to confirm the type of ID card. An ID identification step, a character area extraction step of defining the location of the text object area corresponding to the identified type of ID, extracting characters and converting them into text data, and a patient information storage step of storing the recognized text data as patient information. The patient information can be collected by performing .

In addition, the patient information collection unit calculates a normal range and a valid data range for the measured value of the illuminance sensor provided in the ID card photographing unit, where the normal range is an upper limit of the value measured from the illuminance sensor during a preset period, Calculate the limit value (L _ud ) according to the following [Equation 1] using the lower limit value and the average value,

[Equation 1]

(Here, U _v means the upper limit, Av means the average value, and L _v means the lower limit)

The difference value obtained by subtracting the limit value from the average value or the value obtained by adding the limit value to the average value is calculated as a normal range, and data excluding the calculated normal range is determined as noise data, wherein the upper limit value and the lower limit value are the lower limit boundary. It is derived within the prediction range defined as the range from the value to the upper limit value, where the lower limit value is the average value of the preset initial value minus N times the average deviation, and the upper limit value is the preset initial value It can be calculated by adding N times the average deviation to the average value.

According to the present invention, by providing an image capture device in a kiosk system and recognizing an ID card, it is possible to receive patient information from a management server and provide medical services with improved patient convenience.

In addition, by preventing contact between patients and medical personnel through guidance using a kiosk system, infection of medical personnel can be prevented.

In addition, it is possible to reduce the fatigue of medical personnel required for sample collection by determining whether a patient who has completed a questionnaire is eligible for sample collection and then supplying sample ampoules to the patient through a kiosk system.

Figure 1 is a diagram showing the configuration of a non-face-to-face sample ampoule supply kiosk system according to an embodiment of the present invention.

Figure 2 is a diagram illustrating an identification card recognition method of a non-face-to-face sample ampoule supply kiosk system according to an embodiment of the present invention.

Figure 3 is a graph showing the illuminance measurement value of the illuminance sensor located in the ID card photographing unit according to an embodiment of the present invention.

FIG. 4 is a graph showing measured values including noise values generated at regular time intervals from an illuminance sensor located in an identification card photographing unit according to an embodiment of the present invention.

FIG. 5 is a graph showing measurement values including continuously occurring noise values among measurement values sensed by an illuminance sensor located in an ID card photographing unit according to an embodiment of the present invention.

Specific details, including the problem to be solved by the present invention, the means for solving the problem, and the effect of the invention, are included in the examples and drawings described below. The advantages and features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings.

The scope of the present invention is not limited to the embodiments described below, and various modifications can be made by those skilled in the art without departing from the technical gist of the present invention.

Hereinafter, the non-face-to-face sample ampoule supply kiosk system and method of the present invention will be described in detail with reference to the attached FIGS. 1 to 5.

First, Figure 1 is a diagram showing the configuration of a non-face-to-face sample ampoule supply kiosk system according to an embodiment of the present invention, and Figure 2 is a diagram illustrating the ID card recognition method of the non-face-to-face sample ampoule supply kiosk system according to an embodiment of the present invention. is a diagram illustrating, Figure 3 is a graph showing the illuminance measurement value of the illuminance sensor located in the ID card capturing unit according to an embodiment of the present invention, and Figure 4 is a graphical representation of the illuminance measurement value of the illuminance sensor located in the ID card capturing unit according to an embodiment of the present invention. It is a graph showing measured values including noise values generated at regular time intervals from an illumination sensor located at This is a graph showing the measured values including the noise values generated.

Referring to Figure 1, the non-face-to-face sample ampoule supply kiosk system and method according to an embodiment of the present invention includes a server unit 110, a patient information collection unit 120, a touch panel control unit 130, and a sample target determination unit. It may include (140), an ampoule providing unit (150), and a medical personnel calling unit (160).

Here, the sample ampoule automatic supply kiosk system 100, which provides guidance services through touch input and image output on the screen of the present inventor, displays preset content on one side of the housing and the outer surface of the housing and detects the user's touch input. Sample ampoules can be automatically supplied using a sample ampoule automatic supply kiosk device including a panel and a sample ampoule inlet and outlet provided on the other side of the outer surface of the housing.

The server unit 110 can connect to the hospital server to transmit and receive pre-stored patient information, questionnaire forms, questionnaire results, and disease information data.

More specifically, when the kiosk system 100 is located in a hospital, it receives patient data, questionnaire form data, patient questionnaire result data, disease-related guidance data, disease code of conduct data, and prevention rule data from the hospital's own server. can do.

In addition, simple patient information data input through the kiosk system 100 is transmitted to the hospital server to determine whether the patient has a history of visiting the hospital. However, if there is a previous visit history, the detailed patient information input screen is not displayed. You can print out the questionnaire right away.

Here, simple patient information data may mean data including the patient's name, date of birth, and contact information.

Meanwhile, in the detailed patient information input screen, if there is no matching patient on the hospital server after the patient inputs simple patient information data into the kiosk system 100, the patient may be determined to be a new patient.

As above, basic patient information such as name, date of birth, contact information, contact information of guardian, information on medications currently being taken, information on diseases currently being treated, and information on currently identified allergic substances, as well as the type of disease that is the target of the interview, are provided from patients determined to be new patients. Correspondingly, an input box for required patient medical information can be provided in the kiosk system 100 to receive input from the patient.

Through this, the collected patient information can be collected and stored through the patient information collection unit 120.

Meanwhile, the above questionnaire consists of a table that includes questions such as the patient's medical history, whether there are major symptoms of the infectious disease, the time of onset, progress, and current symptoms. According to the results of the questionnaire filled out by the patient, the current patient is likely to be infected with the infectious disease and has already It can be used as basic data to determine whether someone is infected.

The patient information collection unit 120 may collect the patient's personal information by capturing the patient's ID card image.

More specifically, the patient information collection unit 120 may be provided inside the kiosk system 100 to further provide an ID card capturing unit including an ID card input port, an image capture device, an illuminance sensor, and a lighting device.

Here, an infrared detection sensor is provided at the ID card input port, so that when the ID card is input, infrared rays are irradiated, and the presence or absence of the ID card can be determined through the difference in the detection amount of reflected infrared rays received.

Additionally, the video recording device may refer to a color video camera, an ID scanner, an atypical ID identifier, etc.

Using this, when a patient inserts his or her ID card into the ID card slot, the patient's ID card can be photographed by the ID card capture unit and collected as ID image data.

Through the ID image captured in this way, patient information such as the patient's name, resident registration number, address, date of initial issuance, license number, and date of first license acquisition included in the ID image can be collected.

Here, the collected patient information can be compared to match the patient information stored in the hospital server received through the server unit 110, and if they match, they can be classified as existing patients. If they do not match, they can be classified as new patients.

At this time, in the case of an existing patient, the patient information stored in the hospital server is received from the hospital server, skipping entering additional patient information and moving to the questionnaire creation screen, and in the case of a new patient, the detailed patient information input screen is displayed on the kiosk system (100) screen. You can request additional patient information input by printing it out.

Meanwhile, the method of collecting patient information in the ID card through the patient's ID card image captured with an imaging device will be described in more detail with reference to FIG. 2.

Referring to Figure 2, the patient information collection unit 120 includes an ID photographing step (210), an ID identification step (220), a character area extraction step (230), a character recognition step (240), and a patient information storage step ( 250) can be performed to collect patient information.

In the ID photographing step 210, when a patient uses the kiosk system 100 to register for treatment, the phrase 'Please place your ID card on the appropriate location to identify patient information' may be displayed to encourage the patient to take an ID photograph.

At this time, the position where the ID card is placed along with the above phrase can be output on the screen of the kiosk system 100 as video material including a picture or photo to guide the user to place the ID card in the optimal location for taking a picture of the ID card.

Through this, if the patient's ID card is located at a point where an image capture device is installed in the kiosk system 100, the ID card can be photographed and collected in the form of video data.

In the identification identification step 220, the type of the photographed identification card can be confirmed by collecting the photo location, character position, reflection pattern, color, and size information of the identification card.

Meanwhile, the types of identification can be divided into the representative identification cards such as resident registration card, driver's license and passport. Other types of identification include youth identification card, civil service identification card, sailor's notebook, national technical qualification certificate, university or higher student identification card, disabled person welfare card, discharge certificate within one year after discharge, and alien registration card. , Domestic residence report card for Koreans with foreign nationality, domestic residence report card for overseas nationals, certificate of enrollment, etc. may be further included.

As described above, in order to distinguish the type of ID card from various types of ID images, big data images for each type of ID card can be received from the outside.

Using this, feature areas according to the type of ID can be extracted and set as a standard for judging the type of ID.

Here, the feature area may mean an area where features that are different from other types of ID cards exist, such as color data values of a common area for each ID card, a hologram image, and an official seal image of a government office.

More specifically, the color data value of the common area for each ID card may mean a data value obtained by extracting the color code value of the common area excluding the photo location and character location from multiple identical ID images received from outside.

Here, the RGB color code value of the extracted common area can be collected and stored as unique ID card color data for the corresponding type.

At this time, the color data of the ID card can be stored by setting the center of the area recognized as the photo area of the ID card as the reference position.

In addition, the average value and error range of the RGB color code value of each pixel corresponding to the common area can be calculated from the reference position of the same type of ID card and set as the color data value range of the corresponding ID card type.

At this time, the location of the photo in the ID card can be recognized by specifying the photo area in the ID card using facial recognition technology that extracts and recognizes a person's face from a still image.

Through this, it is possible to recognize the location of the photo in the ID card, set it as a reference position, and determine the type of ID card by comparing the average value of the RGB color code value in the common area and whether it is within the error range.

Meanwhile, the hologram image is scanned through a scanning device that scans the hologram image in the ID photographing step 210 and is stored as an image image to determine the type of ID card.

At this time, the scanning device can be placed in a location where the image capturing device is installed in the kiosk system 100 and transmit the scanned image to the patient information collection unit 120.

In addition, the hologram for each ID card can be compared to determine whether the hologram image received from the national agency that issued the ID card matches the hologram image scanned through the scanning device.

In another method, a hologram image is collected from a pre-stored ID image in which the type of ID card is clearly determined, and the hologram image in the patient's ID card collected in the ID photographing step (210) is matched to select the ID type with the highest matching rate. You can judge.

On the other hand, since the official seal image of a government office appears only in a specific ID card, it can be first judged by the list of ID cards containing the official seal image among the types of ID cards extracted from the big data.

In other words, it is possible to further determine the type of ID card after excluding the ID card that contains an official image among various types of ID cards.

Here, the type of ID card can be determined in more detail by comparing the photo position in the ID card with the official image position.

In addition, since the official seal images provided on the ID cards are inserted in batches, it is possible to determine whether they match the official seal images collected through big data on each type of ID card and identify the public institution that has the official seal on the ID card.

Using this, you can determine the type of ID card more accurately by identifying the organization that issued the ID card.

For example, if the official seal recognized from the patient's ID card is judged to be the official seal of the Seoul Metropolitan Police Agency, and the photo in the ID card is located on the left, it can be judged to be a driver's license.

As another example, if the official seal recognized on the photographed patient's ID card is determined to be the head of Jongno-gu, Seoul, the ID card may be judged to be a resident registration card or youth ID card. At this time, if the photo is located to the right of the ID card and above the official seal, it can be judged to be a resident registration card.

In the text area extraction step 230, the location of the text object area corresponding to the identified ID card may be defined, and the text may be extracted from the limited text object area and converted into text data.

Here, the text object area may mean an area containing text in the ID card image.

For example, in the case of a resident registration card, 'Resident Registration Card', 'Hong Gil-dong (洪吉童)', '820701-2345678', '#1204, Building 1203, 93 Euncheon-ro, Jongno-gu, Seoul (#2301, Building 101, Jindallae Apartment, Bongcheon-dong)', 2019. 11. 28', 'Haengbok Special City Mayor of Haengbok-gu' are limited to the text object area and can be converted to text data.

In other words, it is possible to collect patient information by identifying the position where letters are written depending on the type of ID card and recognizing letters containing information necessary for collecting patient information according to the positions of the letters written.

For example, if the patient's identification card taken through the kiosk system is determined to be a resident registration card, only the text objects containing the patient's name, resident registration number, and address can be recognized and stored as text data.

At this time, the method of converting the text object into text data is to convert the text object image into text by applying an artificial neural network model consisting of an input layer, a hidden layer, and an output layer based on the ID card big data for each type, and utilizing technology to convert the text object image into text. It can be saved as .

Through this, text objects corresponding to the elements necessary for recording patient information (name, resident registration number, address) in the ID card are converted into text and stored, and unnecessary elements (driver's license aptitude test period, driver's license number, driver's license issuance date, resident registration card) are converted into text and stored. By not recognizing information (information not required for hospital treatment, such as date of issuance, location of issuance, etc.), the time required to collect patient information using ID cards can be shortened.

In the patient information storage step 240, text data recognized through the ID card image can be stored as patient information.

Meanwhile, the patient information collection unit 120 can photograph the patient's ID card entered into the ID photographing unit.

More specifically, an object detection sensor is provided at the ID card slot to recognize whether the patient's ID card has been inserted, and the illumination level inside the ID card slot can be sensed through an illumination sensor provided inside the ID card slot.

Through this, the illumination intensity of the lighting device can be adjusted according to the sensed illuminance measurement value to fall within the preset illuminance measurement range, and then an ID card image can be captured using a video recording device.

Here, by providing a control device that increases or decreases the brightness of the lighting device in response to the measured value using the illuminance sensor, the brightness of the lighting device can be automatically controlled according to the measured value of the illuminance sensor.

For example, when photographing an ID card in the ID recording department, the clearest illuminance is 550 lx (lux, light intensity), the recommended illuminance is 400 to 700 lx, and the current measurement value sensed through the illuminance sensor is 200 lx, the above control By transmitting a signal from the device to the lighting device, the brightness of the lighting device can be increased.

At this time, if the measurement value measured through the illuminance sensor is within the recommended illuminance range, the current brightness of the lighting device can be maintained as is, and a lighting preparation completion signal can be transmitted to the imaging device to photograph the patient's identification card.

Meanwhile, the patient information collection unit 120 can calculate the normal range and effective data range for the displayed measurement value by sensing the illuminance inside the ID card recording unit.

Through this, it is confirmed whether the internal brightness of the ID card recording unit is maintained within the ideal illuminance range, and only valid values are extracted from the measured values sensed by the illuminance sensor, excluding values corresponding to noise, to adjust the internal brightness of the ID card recording unit. It can be done.

More specifically, in order to remove noise and extract valid data from the measured value sensed from the illuminance sensor provided in the ID card recording unit, the normal range and valid data range for the measured value of the illuminance sensor are calculated, and the normal range is calculates the limit value (L _ud ) according to the following [Equation 1] using the upper limit, lower limit, and average value of the values measured from the temperature sensor during a preset period,

[Equation 1]

(Here, U _v means the upper limit, Av means the average value, and L _v means the lower limit)

A difference value obtained by subtracting the limit value from the average value or a value obtained by adding the limit value to the average value is calculated as a normal range, and data outside the calculated normal range can be determined as noise data.

For example, in [Equation 1], when the upper limit value (U _v ) is 750 lx, the average value (Av) is 600 lx, and the lower limit value (L _v ) is 400 lx, the difference between the upper limit value and the average value is 750-400= 350, the difference between the average value and the lower limit is 600-400=200, so the larger element, 350, can be calculated as the limit value (L _ud ).

When the limit value is calculated as described above, the normal range can be determined. The normal range can be determined from the value obtained by subtracting the limit value from the average value to the value obtained by adding the limit value to the average value.

Therefore, in principle, data that is not included within the calculated normal range is judged as noise data.

However, the following criteria can be additionally applied to further subdivide the noise data.

For example, noise data is when the measured value from the sensor is outside the normal range, and data outside the normal range does not occur continuously more than a preset number of times, and at the same time, the previous value and the previous data value that were immediately outside the normal range are Measured values determined to be outside the set error range (at this time, the error range can be set between -5% to +5% to -20% to +20% depending on the type and sensitivity of the sensor) are used as noise data. By making the final decision, you can increase the accuracy of noise data selection.

Additionally, the preset number of times can be set to 2 to 5 times, and it can be determined whether data outside the normal range is continuous or discontinuous depending on whether the number satisfies the range.

Here, the process of calculating the normal range and classifying noise data using the total measurement values of the preset sensors will be described in more detail with reference to FIG. 3.

As shown in FIG. 3, the measured value of the internal brightness of the ID card recording unit sensed through the illuminance sensor can be expressed in a graph.

Here, the patient information collection unit 120 recognizes only values measured within the normal range 340 as valid values, and the normal range 340 is defined by receiving initial values for a preset interval and then It can be calculated using the average value (330) and average deviation of the initial values.

At this time, since meaningless data may be included among the initial values, only initial values within the prediction range among all initial values input are used to derive the normal range 340, and the prediction range 350 is determined by the method below. It can be calculated as

In order to calculate the prediction range 350, the average value 330 of all initial values during the preset interval plus N multiples of the average deviation is taken as the upper boundary value 310 of the prediction range 350, and the preset interval The value obtained by subtracting the N multiple of the average deviation from the average value 330 of all initial values during the period is determined as the lower boundary value 320 of the prediction range 350, and the value between the upper and lower limits can be calculated as the prediction range 350. there is.

At this time, the N value of the N multiple can be set from a minimum of 1.5 to a maximum of 20 depending on the sensor.

For example, if the average value (330) of the initial value measured during a preset period in which patient information was normally collected by taking an ID card using an illuminance sensor was 400 lx, the average deviation was calculated as 25, and the N multiple was set to 8, The upper boundary value 310 of the prediction range 350 can be calculated as 400+25×8=600lx, and the lower boundary value 320 can be calculated as 400-25×8=200lx.

Through the above process, the patient information collection unit 120 calculates the upper limit value 310 and the lower limit value 320 using the average value 330, average deviation, and multiple, and the range between them. 200 lx ~ 600 lx can be set as the prediction range (350).

As described above, by calculating the prediction range 350 using the average value 330, upper boundary value 310, and lower boundary value 320, data selection to determine the normal range 340 can be made more reliable. there is.

Below, the process for calculating the normal range 340 using the predicted range 350 will be described.

First, the largest measured value within the prediction range 350 is extracted as the upper limit 305, and the smallest measured value is extracted as the lower limit 306, and the average value 330, upper limit 305, and The limit value can be calculated using the lower limit value 306.

When the limit value is calculated through [Equation 1], the measured value obtained by subtracting the limit value from the average value 330 or the measured value obtained by adding the limit value to the average value 330 is determined as the normal range 340, and the normal range ( 340) can be judged as noise data.

At this time, the previously determined prediction range is 200 lx ~ 600 lx. If we derive the upper limit value (305), which is the largest value, and the lower limit value (306), which is the smallest value, and apply this to [Equation 1] to calculate the limit value, the limit value is max{(580-400), (400-240)} It can be determined as =180lx.

That is, the first point data 301, the second point data 302, the third point data 303, and the fourth point data 304, which are data outside the prediction range 350, are excluded from calculating the upper and lower limits. By doing so, it is possible to prevent meaningless data from being used to calculate the normal range.

Through the above process, the normal range 340 is calculated from 400-180 = 220 lx, which is the difference between the average value 330 and the limit value, to 400 + 180 = 580 lx, which is the sum of the average value 330 and the limit value, and the normal range ( The first point data 301, the second point data 302, the third point data 303, and the fourth point data 304, which are measurement values not included in 340, may be determined to be noise data.

Meanwhile, the patient information collection unit 120 can use the generation pattern of noise data to determine the possibility of unusual events such as sensor failure, an example of which will be described in more detail below.

For example, if the noise data is within the preset error range compared to the previous value, and multiple sensing cycles of the same value are measured at preset time intervals, it is determined that this is likely to occur due to a sensor defect. can do.

In other words, when a number of measured values and measurement intervals that are outside the normal range and are judged to be noise data are included within the error range and are measured at regular intervals, the presence of contaminants in the sensor measurement area, problems with transmitting and receiving electrical signals of the sensor, etc., continuously change the normal range. Since it is judged that there is a high possibility that deviant measurement values will be measured, it can be recognized as sensor defective data and used as a basis for considering repair or replacement of the sensor.

For example, if a normal range is set as shown in FIG. 3 and includes noise data outside the normal range, but meets the sensor defect data conditions, the noise data may be recognized as data generated due to a sensor defect. This can be done, and specific examples will be described in more detail with reference to FIG. 4 above.

Referring to FIG. 4, in the process of sensing the brightness data inside the ID card recording unit through the illuminance sensor, noise data outside the normal range is generated multiple times, and compared to the previous noise data, noise data is within -10% to +10%. It can be confirmed that it occurs continuously within the error range.

In this way, when noise data occurring within the error range repeats at a certain cycle, it can be predicted that a sensor failure has occurred based on the noise data.

Here, the fact that the noise data is repeated at a certain period may mean that the period in which the noise data appears is within an error range of -10% to +10%.

More specifically, the fifth point data 401, sixth point data 402, and seventh point data 403 that are outside the normal range are measured, and the fifth point data 401 is measured at 27 seconds. , and if the sixth point data 402 was measured at 41 seconds, the time interval between the fifth point 401 and the sixth point 402 is 14 seconds (t ₁ ). In addition, since the 7th point data 403 was measured at 54 seconds, the time interval between the 6th point data 402 and the 7th point data 403 was 13 seconds (t ₂ ), so the 5th point data ( The time interval between 401) and 6th point data 402 and the 6th point data 402 and 7th point data 403 are 1 second, and do not occur beyond 1.4 seconds, which is the 10% error range. didn't

Therefore, since a large number of noise data is outside the normal range and the generation cycle is determined to be within a certain range, it can be predicted that a defect has occurred in the sensor.

In this case, a guidance message, etc. can be sent to the manager of the kiosk system 100 to check whether the illuminance sensor is defective. More specifically, the ID photographing unit sensed by the illuminance sensor in the patient information collection unit 120 If a sensor defect is predicted through internal brightness data, an alarm can be provided to the administrator terminal to encourage inspection of the sensor.

On the other hand, if the internal brightness data of a plurality of ID recording units measured by the patient information collection unit 120 is outside the normal range for a certain period of time but is continuously measured within a similar value range, it is not a sensor defect but a malfunction in a peripheral device. It can be judged that this has occurred. This is explained in more detail with reference to FIG. 5 .

Referring to Figure 5, a number of noise data exceeding the normal range were detected in the section between 27 and 42 seconds, but a number of noise data were within a certain error range (e.g., 10% from the noise data value that first appeared in the section). distributed within the range). In this case, it can be determined that it is not a defective sensor, but a malfunction of a peripheral device that controls the environment measured by the sensor. For example, the lighting device must immediately lower the brightness starting at 27 seconds when the value measured through the illuminance sensor exceeds the predicted range, but it operates starting at 37 seconds, which is 8 seconds later, requiring readjustment of the operation timing. In this case, the lighting device operates immediately from 27 seconds, but due to an error in the lighting device's lighting control function, the proper lighting control function is performed 8 seconds after operation, resulting in an abnormal operation of the lighting device's lighting control function. Data received by the sensor. It may cause errors.

In this case, the patient information collection unit 120 can predict errors in the illuminance sensor peripheral device and send an inspection alarm for the peripheral device to the administrator terminal.

Referring again to FIG. 1, the touch panel control unit 130 may control the screen state of the touch panel based on an image captured through the user recognition camera.

Here, the user recognition camera determines whether a person is a person by determining the location of the person's eyes, nose, mouth, face, arms, legs, etc. using image big data captured using the camera and judged to be a person. Patients can be recognized by applying a camera with learning technology and facial recognition technology.

Through this, when a patient is positioned opposite the touch panel, preset content can be displayed and the display screen can be switched based on the patient's touch input.

Here, the preset content may include a patient information input screen, a questionnaire creation screen, a QR code screen, and a disease-related promotional materials screen.

More specifically, when a patient inputs a touch on the touch panel to use the kiosk system 100, at least one of the following is displayed, such as printing the patient information input screen, directly entering the patient information, taking an ID card to input the patient information, or printing a QR code. By selecting one, a screen encouraging input of patient information may be displayed.

At this time, when the patient selects to directly enter patient information, a screen for entering patient information and a touch keyboard screen can be output to encourage the patient to directly input patient information using the kiosk system 100.

Additionally, if you select QR code printing, the QR code can be printed along with a phrase encouraging the patient to recognize the QR code with their smartphone.

Here, when the patient recognizes the QR code using a smartphone, a patient information input screen is output on the patient's smartphone to induce patient information input, and the patient information created on the patient's smartphone is sent to the server unit 110. Can be transmitted.

Thereafter, the server unit 110 transmits the medical questionnaire to the patient's smartphone, encouraging the patient to fill out the medical questionnaire using the smartphone and transmit it back to the server unit 110, thus improving the patient's convenience.

At this time, the server unit 110 may receive the questionnaire prepared by the patient from the patient's smartphone and transmit the questionnaire results back to the patient's smartphone.

Meanwhile, the disease-related promotional materials screen can automatically print disease-related promotional materials if no one is currently using the kiosk system (100) and display disease-related behavior rules, disease prevention rules, and the location of screening stations in the hospital. there is.

Additionally, the touch panel control unit 130 may control the screen brightness of the touch panel based on illuminance data collected from an illuminance sensor provided on the upper side of the touch panel.

That is, when the illuminance data is below a preset reference value, the screen brightness of the touch panel can be controlled to maintain the preset initial value.

Meanwhile, when the illuminance data exceeds the above reference value and the patient is recognized in a position facing the touch panel in response to the user recognition camera for a preset time, the screen brightness of the touch panel may be automatically adjusted to the maximum value.

In addition, even if the illuminance data exceeds the above reference value, if the patient is not recognized in the position facing the touch panel through the user recognition camera for a preset period of time, the screen brightness of the touch panel may be automatically adjusted to the lowest value.

Here, the standard value of the illuminance data may be 150 lx to 550 lx.

Meanwhile, the illuminance sensor provided in the touch panel control unit 130 also calculates the normal range and effective data range for the sensed measurement value like the illuminance sensor provided in the patient information collection unit 120, and calculates the measured value corresponding to the noise data. Excluding, only valid values can be extracted to determine whether the sensor is malfunctioning.

When the sample subject determination unit 140 receives a signal from the server unit 110 that determines that sample collection is necessary from the results of the questionnaire written by the patient, it sends an alarm to the patient's smartphone notifying the sample collection target. Can be transmitted.

At this time, the sample ampoule is received from the kiosk system 100 on the smartphone of the patient subject to sample collection, and information on how to collect the sample is provided in the form of video and text to encourage smooth sample collection by the patient.

Here, whether the subject is subject to sample collection can be determined if the number of items checked among preset items in the questionnaire exceeds a certain number of times.

For example, if the patient must select 'Yes' or 'No' for 20 questions in the questionnaire, and the total number of items checked as 'Yes' exceeds 11, the patient may be judged to be subject to sample collection.

When a patient is the subject of sample collection, the ampoule providing unit 150 may provide a sample ampoule containing patient information.

For example, if a patient is determined to be a subject for sample collection, the patient may select to receive a sample ampoule on the touch panel control unit 130 to provide a sample ampoule.

At this time, in order to confirm whether the patient is a recipient of the sample ampoule, the patient's ID card may be rephotographed to verify the patient's identity, and then the sample ampoule may be provided.

As another method, when a QR code is output to the touch panel control unit 130 and the QR code is recognized by the patient's smartphone, it is determined that the patient is located in the kiosk system 100 and a sample ampoule can be provided.

At this time, the sample ampoule provided to the patient may be provided to the patient after attaching a sticker printed with the patient's name, suspected disease name, test item name, etc., through a sticker attachment device that attaches the sample ampoule to the sample ampoule.

Meanwhile, the ampoule providing unit 150 may further include an ampoule replacement unit that automatically replaces the ampoules in the kiosk.

The ampoule replacement unit may count the number of sample ampoules discharged from the kiosk system 100 and, when a preset number is reached, transmit an ampoule cartridge replacement request signal to a predetermined manager terminal.

More specifically, the ampoule cartridge accommodating a plurality of ampoules discharges one ampoule according to the ampoule providing signal received from the ampoule providing unit 150, and determines whether the ampoule is discharged through an infrared object detection sensor provided at the ampoule discharge port. can be counted.

Through this, if the quantity of ampoules in the initial ampoule cartridge matches the counting number of discharged ampoules, the ampoule cartridge can be automatically replaced or an ampoule cartridge replacement request signal can be sent to a predetermined manager terminal.

Here, the predetermined manager terminal may mean an electronic device capable of wired and wireless communication, such as a smartphone, PC, laptop, or tablet PC of the manager registered in the ampoule replacement unit.

For example, a maximum of one ampoule cartridge is input into the kiosk system 100, and the ampoule cartridge, which can accommodate a total of 100 ampoules per ampoule cartridge, can provide one ampoule to each patient according to the results of the patient's questionnaire. there is.

At this time, an infrared object detection sensor can be provided at a location where the ampoule passes just before being discharged from the ampoule discharge port to count the number of ampoules discharged from the ampoule discharge port.

Here, while dispensing ampoules continuously to a large number of patients, when the number of ampoules is counted reaches 40, position exchange with the remaining ampoule cartridges located in the kiosk system 100 can be automatically performed to provide subsequent ampoules.

At this time, the positions between the ampoule cartridges can be exchanged through a replacement device located at the bottom of the ampoule cartridge and changing positions through a rotational motion. A proximity sensor is provided on the lower surface of the individual ampoule cartridge, so that the ampoule cartridge can be replaced within the ampoule cartridge. It is possible to determine whether the ampoule is full or empty.

Through this, if it is determined that the remaining ampoule cartridges other than the ampoule cartridge currently supplying ampoules are full, ampoule replacement can be performed automatically after counting 40 times.

On the other hand, if the ampoule is judged to be empty by sensing the weight of the remaining ampoule cartridges other than the ampoule cartridge currently supplying the ampoule, the administrator terminal starts counting from the first count of the ampoule cartridge currently supplying the ampoule exceeding 30 times. The current remaining number of ampoules and an ampoule cartridge replacement request signal can be transmitted.

Through this process, automatic replacement of the ampoule cartridge within the kiosk system 100 and replacement of all ampoule cartridges can be performed.

The medical personnel call unit 160 may transmit a call signal to the medical practitioner's terminal in response to at least one request from a patient among a request for assistance in collecting a sample, a request for assistance in filling out a questionnaire, a request for face-to-face treatment, and a request for assistance with an emergency patient.

More specifically, if a patient is subject to sample collection through the questionnaire of the kiosk system 100, the sample collection method may be provided through the touch panel control unit 130 of the kiosk system 100 or the patient's smartphone. When it is difficult to collect a sample yourself, you can call a medical professional in charge of sample collection by selecting 'Request assistance with sample collection'.

Here, the 'request for help with sample collection' can be called by touching the button displayed on the touch panel control unit 130 in the kiosk system 100.

In addition, patients can recognize the QR code and call the medical professional in charge of sample collection by displaying the 'Request sample collection assistance' button even while watching the sample collection method on their smartphone.

At this time, the name, date of birth, and call location information entered by the patient are displayed on the terminal of the medical professional in charge of sample collection, thereby minimizing the time the medical professional spends searching for the patient and providing efficient sample collection assistance.

In addition, when a patient requests to fill out a questionnaire, a call signal can be sent to the medical professional's terminal as described above, so that the medical professional can provide assistance to the patient in filling out the medical questionnaire.

On the other hand, if the patient skips the questionnaire filling out and sample collection process and requests face-to-face medical treatment and emergency patient assistance through the kiosk system (100) or the patient's smartphone that recognizes the QR code, the professional medical staff is immediately sent to the terminal. You can transmit a call signal.

At this time, the kiosk system 100 can provide patient information and current patient location information to the professional medical staff's terminal.

Through this, it is possible to prevent unnecessary sample collection by reducing errors in filling out questionnaires in cases where the patient is not related to the disease being questioned in the kiosk system 100 or in elderly patients who have difficulty using the kiosk system 100 and smartphones.

Additionally, in emergency situations where a medical examination is not possible, patients can call the medical staff and receive quick face-to-face treatment.

Through the above process, the specimen ampoule automatic supply kiosk system and method connects the server unit provided in the kiosk with the hospital server to transmit and receive patient information and questionnaire-related data to confirm patient management and whether sample measurement is necessary according to the questionnaire. And, the brightness of the touch panel can be automatically adjusted by recognizing the patient located in the kiosk system. Meanwhile, before filling out the patient's questionnaire, the patient's ID card can be input, the patient's ID card can be photographed, and the text object can be converted into text data to update or newly register patient information. Meanwhile, if sample collection is required according to the results of the questionnaire filled out by the patient using the kiosk system or smartphone, a sample ampoule is provided so that the sample collected by the patient can be received again. In addition, patients can use the kiosk system or smartphone to call medical staff by selecting the following items: requesting help filling out a questionnaire, requesting help collecting samples, and calling a medical professional in the event of an emergency. In addition, when entering the questionnaire and patient information, a QR code can be printed on the kiosk to input information and fill out the questionnaire using a personal smartphone. Meanwhile, when collecting patient information by photographing the patient's ID card, a video recording device, an illumination sensor, and a lighting device are provided in the ID recording unit where the ID card is photographed, and the normal range and valid data for the measured value sensed from the illumination sensor are provided. By calculating the range, you can quickly determine whether the illumination sensor is defective or the lighting device is defective, thereby preventing errors in taking ID cards.

According to one embodiment of the present invention, a video recording device is provided in a kiosk system to recognize an ID card, thereby receiving patient information from a management server and providing medical services that improve patient convenience.

In addition, by preventing contact between patients and medical personnel through guidance using a kiosk system, infection of medical personnel can be prevented.

In addition, it is possible to reduce the fatigue of medical personnel required for sample collection by determining whether a patient who has completed a questionnaire is eligible for sample collection and then supplying sample ampoules to the patient through a kiosk system.

As described above, although one embodiment of the present invention has been described with limited examples and drawings, one embodiment of the present invention is not limited to the above-described embodiment, which is based on common knowledge in the field to which the present invention pertains. Anyone who has the knowledge can make various modifications and variations from this description. Accordingly, one embodiment of the present invention should be understood only by the scope of the claims set forth below, and all equivalent or equivalent modifications thereof shall fall within the scope of the spirit of the present invention.

100: Automatic sample ampoule supply kiosk system

110: server unit

120: Patient information collection department

130: Touch panel control unit

140: Sample target judgment unit

150: Ampoule provision unit

160: Medical personnel call book

210: Shooting step

220: ID identification step

230: Character area extraction step

240: Patient information storage step

301: first point data

302: second point data

303: Third point data

304: 4th point data

305: upper limit value

306: lower limit

310: upper boundary line

320: Lower boundary line

330: average value

340: Normal range

350: Prediction range

401: Fifth point data

402: 6th point data

403: 7th point data

Claims (5)

1. A sample ampoule is supplied using an automatic sample ampoule supply kiosk device including a housing, a touch panel that displays preset content on one side of the outer surface of the housing and detects the user's touch input, and a sample ampoule inlet and outlet provided on the other side of the outer surface of the housing. In the kiosk system that automatically supplies,

   A server unit that connects to the hospital server to transmit and receive pre-stored patient information, questionnaire forms, questionnaire results, and disease information materials;

   a patient information collection unit that collects the patient's personal information by capturing the patient's ID card image;

   The screen state of the touch panel is controlled based on an image captured through a user recognition camera, and when the patient is positioned opposite the touch panel through the user recognition camera, preset content is displayed and the patient touch input. a touch panel control unit that switches the display screen based on;

   a sample subject determination unit that determines whether a sample is subject to collection in response to the results of the questionnaire completed by the patient;

   When the patient is a subject for sample collection, an ampoule providing unit that provides a sample ampoule with patient information written on it; and

   A medical practitioner call unit that transmits a call signal to the medical practitioner's terminal in response to at least one request among the method of collecting a sample from the patient, filling out the questionnaire, requesting face-to-face treatment, and requesting assistance for an emergency patient;

   Automatic sample ampoule supply kiosk system and method comprising a.
2. According to paragraph 1,

   The touch panel control unit,

   Controlling the screen brightness of the touch panel based on illuminance data collected from an illuminance sensor provided on the upper side of the touch panel,

   If the illuminance data is below a preset reference value, the screen brightness of the touch panel is controlled to maintain the preset initial value,

   When the illuminance data exceeds the reference value and the patient is recognized in a position facing the touch panel in response to the user recognition camera for a preset time, the screen brightness of the touch panel is automatically adjusted to the maximum value, and ,

   Even if the illuminance data exceeds the reference value, if the patient is not recognized in a position opposite the touch panel through the user recognition camera for a preset time, the screen brightness of the touch panel is automatically adjusted to the lowest value. Automatic sample ampoule supply kiosk system and method.
3. According to paragraph 1,

   The patient information collection department,

   An ID recording unit is further provided inside the kiosk system and includes an ID card input slot, a video recording device, an illuminance sensor, and a lighting device,

   Collect at least one of the patient's name, resident registration number, address, initial issuance date, license number, and first license acquisition date from the patient's ID image captured by the ID recording unit,

   An automatic sample ampoule supply kiosk system characterized by determining whether the collected patient information matches the patient information stored in the server unit and classifying them as new or existing patients.
4. According to paragraph 3,

   The patient information collection department,

   An ID photographing step of photographing an ID card placed by the patient on an image capture device of the kiosk system;

   An ID identification step of confirming the type of ID card by collecting photo location, reflection pattern, color, and size information of the ID card;

   A character area extraction step of defining the location of a text object area corresponding to the identified type of identification card, extracting the text, and converting it into text data; and

   A patient information storage step of storing the recognized text data as patient information;

   Automatic sample ampoule supply kiosk system, characterized in that the patient information is collected by performing.
5. According to clause 4,

   The patient information collection department,

   Calculate the normal range and effective data range for the measured value of the illuminance sensor provided in the ID card photographing unit,

   The normal range is,

   Calculate the limit value (L _ud ) according to the following [Equation 1] using the upper limit, lower limit, and average value of the values measured from the illuminance sensor during a preset period,

   [Equation 1]

   

   (Here, U _v means the upper limit, Av means the average value, and L _v means the lower limit)

   The difference between the average value minus the limit value or the average value plus the limit value is calculated as a normal range, and data outside the calculated normal range is judged as noise data,

   The upper limit and the lower limit are,

   Derived within the prediction range defined as the range from the lower boundary value to the upper boundary value,

   The lower limit value is the average value of the preset initial value minus N times the average deviation,

   The upper limit value is the average value of the preset initial value plus N times the average deviation. The automatic sample ampoule supply kiosk system and method.

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