WO2025094437A1 - 作業記録方法、情報処理装置、及びプログラム - Google Patents

作業記録方法、情報処理装置、及びプログラム Download PDF

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Publication number
WO2025094437A1
WO2025094437A1 PCT/JP2024/020244 JP2024020244W WO2025094437A1 WO 2025094437 A1 WO2025094437 A1 WO 2025094437A1 JP 2024020244 W JP2024020244 W JP 2024020244W WO 2025094437 A1 WO2025094437 A1 WO 2025094437A1
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Prior art keywords
work
recording method
information
work content
work recording
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English (en)
French (fr)
Japanese (ja)
Inventor
隆史 大隈
良介 一刈
洋靖 三輪
里樹 小木曽
康行 吉田
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National Institute of Advanced Industrial Science and Technology AIST
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National Institute of Advanced Industrial Science and Technology AIST
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services

Definitions

  • This disclosure relates to a work recording method, an information processing device, and a program.
  • Patent Document 1 discloses a method for dividing the work area in which staff members move into small work sections, and for recording and tabulating the work content by combining the work name with the name of the small work section.
  • a work recording method is a work recording method executed by an information processing device, Acquiring environmental information related to the work content of staff members; estimating a plurality of task content candidates based on the environmental information; presenting the plurality of work content candidates; determining a work content selected from the plurality of work content candidates as the work content of the staff member; Includes.
  • a work recording method is the work recording method according to (1),
  • the environmental information includes a group of data relating to position information on a facility floor plan, posture information of the staff member, and time information.
  • a work recording method is the work recording method according to (2),
  • the staff member's posture information includes sensing data acquired from a terminal worn or carried by the staff member.
  • a work recording method is the work recording method according to (3), further comprising:
  • the sensing data includes acceleration information, angular velocity information, and magnetic information.
  • a work recording method is the work recording method according to any one of (2) to (4), further comprising:
  • the position information on the facility floor plan includes position information of the staff observed by beacons placed in the facility.
  • a work recording method is the work recording method according to any one of (1) to (5),
  • the environmental information includes at least one of staff attendance information and work schedule information.
  • a work recording method is the work recording method according to any one of (1) to (6),
  • the plurality of work content candidates are estimated by inputting the environmental information into a trained learning model that has undergone machine learning to estimate the plurality of work content candidates.
  • a work recording method is the work recording method according to any one of (1) to (7),
  • the learning model further outputs an estimated likelihood of each task content candidate, and a presentation order of the multiple task content candidates is based on the estimated likelihood.
  • a work recording method is the work recording method according to any one of (1) to (8), The number of presented work content candidates is seven or less.
  • a work recording method is the work recording method according to any one of (1) to (9),
  • the number of the plurality of task content candidates to be presented is determined based on a total value of estimated likelihoods related to the plurality of task content candidates.
  • a work recording method is the work recording method according to any one of (7) to (10),
  • the work content of the staff member determined in the step of determining the work content of the staff member is used as training data to re-learn the learning model.
  • a work recording method is the work recording method according to any one of (1) to (11), When a candidate task content with a predetermined estimated likelihood or higher is changed, an alert is issued by sound or vibration.
  • a work recording method is the work recording method according to any one of (1) to (12), When a special task or a candidate task content not included in the task schedule information is estimated, an alert is issued by sound and vibration.
  • An information processing device is an information processing device including a processor, The processor executes the work recording method described in any one of (1) to (13).
  • a program executed by an information processing device causes a computer to execute the work recording method according to any one of (1) to (13).
  • the work recording method, information processing device, and program according to one embodiment of the present disclosure can improve the technology for recording staff work.
  • FIG. 1 is a block diagram showing a schematic configuration of an information processing device that executes a work recording technique according to an embodiment of the present disclosure.
  • 1 is a flowchart illustrating a work recording method according to an embodiment of the present disclosure.
  • 1 is a flowchart illustrating an example of a procedure for generating a learning model for estimating work content in a work recording method according to an embodiment of the present disclosure.
  • FIG. 2 is a diagram showing an example of a hierarchical structure of work contents.
  • FIG. 11 is a diagram illustrating an example of a user interface screen output by an information processing device.
  • the work recording technology according to the embodiment of the present disclosure is executed by an information processing device 10.
  • the work recording technology according to the embodiment of the present disclosure can be used, for example, in caregiving, nursing, medical care, and other fields. Work in these fields is more diverse than work in a factory, as described in Patent Document 1, and flexible responses according to the situation are expected, so the effects of the present invention are even more pronounced.
  • the information processing device 10 acquires environmental information related to the work content of the staff and can estimate multiple work content candidates from the environmental information.
  • the estimated multiple work content candidates are presented to the user.
  • the user can select an appropriate one from the multiple presented work content candidates. If the user selects one of the multiple work content candidates, the selected work content is determined as the work content of the staff. This not only allows the work content of the staff to be recorded correctly, but also reduces the burden of recording itself, contributing to the efficiency of recording work.
  • the work recording technology according to this embodiment allows users to reduce the frequency with which they manually input the work content of their staff when recording the work content of their staff, improving the technology for recording staff work.
  • the information processing device 10 is any device used by a user.
  • a personal computer, a server computer, a general-purpose electronic device, or a dedicated electronic device can be adopted as the information processing device 10.
  • the information processing device 10 includes a control unit 11, a memory unit 12, an input unit 13, an output unit 14, and a communication unit 15.
  • the control unit 11 includes at least one processor, at least one dedicated circuit, or a combination of these.
  • the processor is a general-purpose processor such as a CPU (central processing unit) or a GPU (graphics processing unit), or a dedicated processor specialized for a specific process.
  • the dedicated circuit is, for example, an FPGA (field-programmable gate array) or an ASIC (application specific integrated circuit).
  • the control unit 11 executes processes related to the operation of the information processing device 10 while controlling each part of the information processing device 10.
  • the memory unit 12 includes at least one semiconductor memory, at least one magnetic memory, at least one optical memory, or a combination of at least two of these.
  • the semiconductor memory is, for example, a random access memory (RAM) or a read only memory (ROM).
  • the RAM is, for example, a static random access memory (SRAM) or a dynamic random access memory (DRAM).
  • the ROM is, for example, an electrically erasable programmable read only memory (EEPROM).
  • the memory unit 12 functions, for example, as a main memory device, an auxiliary memory device, or a cache memory.
  • the memory unit 12 stores data used in the operation of the information processing device 10 and data obtained by the operation of the information processing device 10.
  • the input unit 13 includes at least one input interface.
  • the input interface is, for example, a physical key, a capacitive key, a pointing device, or a touch screen that is integrated with a display.
  • the input interface may also be, for example, a sound sensor that accepts voice input, or a camera that accepts gesture input.
  • the input unit 13 accepts an operation to input data used in the operation of the information processing device 10.
  • the input unit 13 may be connected to the information processing device 10 as an external input device.
  • any method such as USB (Universal Serial Bus), HDMI (registered trademark) (High-Definition Multimedia Interface), or Bluetooth (registered trademark) can be used.
  • the output unit 14 includes at least one output interface.
  • the output interface is, for example, a display that outputs information as a video.
  • the display is, for example, an LCD (liquid crystal display) or an organic EL (electro luminescence) display.
  • the output unit 14 displays and outputs data obtained by the operation of the information processing device 10.
  • the output unit 14 may be connected to the information processing device 10 as an external output device.
  • any method such as USB, HDMI (registered trademark), or Bluetooth (registered trademark) can be used.
  • the communication unit 15 includes at least one external communication interface.
  • the communication interface may be either a wired or wireless communication interface.
  • the communication interface is, for example, a LAN (Local Area Network) interface or a USB (Universal Serial Bus).
  • the communication interface is, for example, an interface compatible with mobile communication standards such as LTE (Long Term Evolution), 4G (4th generation), or 5G (5th generation), or an interface compatible with short-range wireless communication such as Bluetooth (registered trademark).
  • the communication unit 15 receives data used in the operation of the information processing device 10, and transmits data obtained by the operation of the information processing device 10.
  • the functions of the information processing device 10 are realized by executing a program according to this embodiment on a processor equivalent to the information processing device 10. That is, the functions of the information processing device 10 are realized by software.
  • the program causes a computer to execute the operations of the information processing device 10, thereby causing the computer to function as the information processing device 10. That is, the computer functions as the information processing device 10 by executing the operations of the information processing device 10 in accordance with the program.
  • the program can be recorded on a computer-readable recording medium.
  • Computer-readable recording media include non-transitory computer-readable media, such as a magnetic recording device, an optical disc, a magneto-optical recording medium, or a semiconductor memory.
  • the program can be distributed, for example, by selling, transferring, or lending a portable recording medium, such as a DVD (digital versatile disc) or a CD-ROM (compact disc read only memory), on which the program is recorded.
  • the program can also be distributed by storing the program in the storage of an external server and transmitting the program from the external server to other computers.
  • the program can also be provided as a program product.
  • Some or all of the functions of the information processing device 10 may be realized by a dedicated circuit equivalent to the control unit 11. In other words, some or all of the functions of the information processing device 10 may be realized by the hardware of the information processing device 10 itself.
  • Step S101 The control unit 11 of the information processing device 10 acquires environmental information related to the work content of the staff.
  • the control unit 11 acquires position information on the facility floor plan, staff posture information, and time information.
  • the position information on the facility floor plan can be obtained over time, for example, by observing the position of the staff using beacons placed in the facility, understanding changes in the staff's walking speed and direction of travel from a terminal worn or carried by the staff, and comparing these with the information on the facility floor plan.
  • Information on the facility floor plan requires information on places that are structurally unwalkable, such as the layout of the facility's walls.
  • the facility floor plan may be, for example, a wall map.
  • the information on the facility floor plan may also include semantic information on places where staff perform specific tasks, such as baths and dining rooms.
  • Staff posture information can be obtained from sensing data acquired from a terminal worn or carried by the staff.
  • Sensing data includes acceleration information, angular velocity information, and magnetic information.
  • Staff posture can be obtained from acceleration information and angular velocity information.
  • Angular velocity information may include drift error, but the drift error can be corrected by using magnetic information in addition.
  • environmental information may include information that can be acquired from nurse calls, excretion sensors, voice information from nursing record support, IoT vital sign measuring devices, or existing work content estimation software. Including more information in the environmental information makes it possible to understand the situation the subject is in, the support currently required, etc., and the accuracy of work content estimation can be further improved.
  • the control unit 11 may use the input unit 13 to acquire sensing data such as acceleration information, angular velocity information, and magnetic information from a terminal worn or carried by the staff member.
  • the terminal worn or carried by the staff member may be a smartphone, and may be hung from the neck. To further improve accuracy, it is preferable to place the terminal close to the torso, for example by placing the terminal in a breast pocket or by fastening a smartphone holder around the waist.
  • the control unit 11 may acquire location information of the terminal worn or carried by the staff member using a beacon placed in the facility.
  • the control unit 11 may acquire observation data from sensors placed in the facility as environmental information.
  • the control unit 11 uses such environmental information as explanatory variables. For example, the control unit 11 extracts a group of data from the past few minutes that is highly relevant to a certain task as explanatory variables.
  • the data group includes at least position information on the facility floor plan and staff posture information at a certain time.
  • the environmental information used by the control unit 11 may include a data group relating to position information on the facility floor plan, staff posture information, and time information.
  • the amount of data in the data group need only be sufficient to estimate the task that was being performed up to a certain point in time, and is not limited to data from the past few minutes, and may be a longer or shorter period of time.
  • Step S102 The control unit 11 estimates multiple work content candidates related to the work that the staff has been performing up to that point in time based on the environmental information. For example, the control unit 11 may generate a learning model as shown in the flowchart of FIG. 3, and estimate multiple work content candidates by inputting the environmental information acquired in step S101 into such a learned learning model.
  • the control unit 11 acquires environmental information related to the staff's work content acquired in the past (step S201) and the work content performed by the staff at that time (step S202).
  • the control unit 11 generates a work content estimation model using the acquired environmental information and work content as teacher data (step S203).
  • the learning model may be, for example, a machine learning model built based on a decision tree.
  • Machine learning models built based on a decision tree include, but are not limited to, Light GBM, XGBoost, etc.
  • the learning model may be a model generated based on a machine learning algorithm such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), or other deep learning.
  • CNN Convolutional Neural Network
  • RNN Recurrent Neural Network
  • the number of estimated work content candidates can be set to 7 or less, and preferably 5 or less.
  • the number of posted work content candidates estimated using such a learning model can be set to a value that is favorable in terms of ease of selection for users.
  • the estimated work content candidates may be selected from a work classification table that classifies the work content into large, medium, and small, for example, according to the granularity of the work content.
  • the work content may be classified into multiple hierarchical categories as illustrated in FIG. 4.
  • a major category may include at least one medium category.
  • a medium category may include at least one minor category.
  • the number of categories belonging to the minor category is the greatest, and the number of categories belonging to the medium category is fewer than the number of categories belonging to the minor category.
  • the number of categories belonging to the major category is even fewer than the number of categories belonging to the medium category.
  • the major categories may be categories that classify the work performed by staff by type of service.
  • the major categories may include, for example, caregiving, nursing, rehabilitation, nursing support, food and nutrition, indirect tasks, common tasks, other tasks, or non-tasks.
  • the major categories may include measurement error as a category to classify the work performed by staff when it cannot be classified into any category.
  • the major categories are not limited to these examples and may include various categories.
  • Medium categories may be categories that classify the work performed by staff according to the purpose or situation of the work.
  • Medium categories may include, for example, waking up or going to bed, changing positions, changing clothes and grooming, moving users, excretion, eating, cleanliness, environmental maintenance, laundry, going out, recreation, transportation, medical treatment, drug management, taking vital signs, examinations, and direct influence on physical functions. They may also include physical therapy, occupational therapy, speech-language-hearing therapy, care plans, nutritional management, meals, hygiene management, staff movement, meetings, office cleaning, understanding users or patients, information sharing, record-keeping, confirmations, dealing with visitors, other services, other tasks, and breaks.
  • the intermediate categories may include, for example, the following categories under the major category of care: getting up or going to bed, changing positions, changing clothes and grooming, moving the user, excretion, eating, cleaning, improving the environment, laundry, going out, recreation, or transportation.
  • the categories under the major category of nursing may include medical treatment, drug management, taking vital signs, examinations, or direct intervention in physical functions.
  • the categories under the major category of rehabilitation may include physical therapy, occupational therapy, or speech-language-hearing therapy.
  • the categories under the major category of care support may include care plans.
  • the categories under the major category of meals and nutrition may include nutritional management, meals, and hygiene management.
  • the categories under the major category of indirect work may include staff transportation, meetings, or office cleaning.
  • the categories under the major category of common work may include understanding the user or patient, sharing information, record-keeping, confirmation, dealing with visitors, or other services.
  • the categories under the major category of non-work may include breaks.
  • Subcategories can be more detailed divisions of the work performed by staff.
  • the minor categories may include, for example, assistance with getting up or assistance with going to sleep as categories belonging to the medium category of getting up or going to sleep.
  • Categories belonging to the medium category of changing position may include changing position or adjusting reclining.
  • Categories belonging to the medium category of changing clothes and grooming may include assistance with changing clothes or assistance with grooming.
  • Categories belonging to the medium category of moving users may include wheelchair guidance, walking assistance, transfer assistance or standing assistance.
  • Categories belonging to the medium category of excretion may include excretion assistance, diaper changing or hand washing assistance.
  • Categories belonging to the medium category of eating may include eating assistance, drinking water assistance, serving food, clearing the table or cooking assistance.
  • Categories belonging to the medium category of cleanliness may include bathing assistance, foot bath assistance, washing assistance, wiping, genital cleaning, oral care, earwax removal, nail clipping, shaving, hair washing, hand washing assistance or gargling assistance.
  • Categories in the environmental maintenance subcategory may include changing sheets, collecting trash, cleaning rooms, checking users' belongings, adjusting room temperature, controlling humidity, adjusting lighting, or ventilation.
  • Categories in the laundry subcategory may include washing or collecting laundry.
  • Categories in the going out subcategory may include shopping on behalf of users or accompanying them on the shopping trip.
  • Categories in the recreation subcategory may include exercises, oral exercises, music, picture-story shows, or cooking.
  • Categories in the transportation subcategory may include transportation or assistance with boarding and disembarking.
  • the minor categories may include, for example, as categories belonging to the medical procedure major category, tracheal suction, wound care, ointment application, disinfection, drug application, intravascular pressure monitoring, intravenous drip injection, gastrostomy management, urinary management, enema, or oxygen therapy.
  • categories belonging to the drug management major category they may include oral medication, tube medication, medication distribution, instillation, injection, suppository administration, or inventory check.
  • categories belonging to the vital signs measurement major category they may include temperature measurement, SpO2 measurement, pulse measurement, blood pressure measurement, weight measurement, or vital signs measurement.
  • categories belonging to the medical examination major category they may include attending medical examinations or accompanying the patient to hospital.
  • categories belonging to the direct influence on bodily functions major category they may include massage or functional recovery.
  • categories belonging to the physical therapy major category they may include range of motion training, heat therapy, walking training, standing training, stair climbing, exercise training, or physical therapy assistance.
  • the categories belonging to the medium category of occupational therapy may include occupational tasks, calculation tasks, cognitive tasks, memory tasks, artistic tasks, play tasks, or occupational therapy assistance.
  • the categories belonging to the medium category of speech-language-hearing therapy may include expression training, auditory comprehension training, swallowing function evaluation, indirect swallowing training, or direct swallowing training.
  • the categories belonging to the medium category of care plans may include care plan creation, conferences, monitoring, or assessment.
  • the categories belonging to the medium category of nutritional management may include nutritional care plan creation, conferences, monitoring, nutritional assessment, nutritional screening, or nutrition and dietary consultation.
  • the categories belonging to the medium category of school lunches may include menu creation, cooking, meal number management, or food procurement.
  • the categories belonging to the medium category of hygiene management may include physical condition management, food management, or facility management.
  • subcategories may include moving, waiting, or transporting as categories belonging to the medium category of staff movement.
  • Categories belonging to the medium category of meetings may include morning assemblies, evening assemblies, or meetings.
  • Categories belonging to the medium category of office cleaning may include cleaning common areas or tidying up.
  • the minor categories may include, for example, categories belonging to the medium category of understanding users or patients, such as calling out, listening, watching over, checking on the user's status, or responding to nurse calls.
  • Categories belonging to the medium category of information sharing may include contacting, handing over, telephone or faxing.
  • Categories belonging to the medium category of record creation may include record creation, calculation, or printing and copying.
  • Categories belonging to the medium category of confirmation may include record confirmation, work confirmation, or equipment confirmation.
  • Categories belonging to the medium category of visitor support may include family support or visitor support.
  • Subcategories may include common tasks such as preparation, tidying up or hand washing.
  • Step S103 The control unit 11 displays and outputs a user interface screen including the multiple work content candidates estimated in step S102 on the output unit 14, and presents it to the user.
  • the control unit 11 may output the multiple work content candidates along with their respective estimated likelihoods, and present them to the user in order of highest estimated likelihood in association with time information.
  • the control unit 11 may output the estimated likelihood of each work content candidate, and the presentation order of the multiple work content candidates may be based on the estimated likelihood.
  • the presentation destination may be a terminal worn or carried by the staff member.
  • the presentation destination may be a terminal used by that person.
  • Step S104 If the user selects one of the multiple work content candidates presented in step S103, the control unit 11 determines the selected work content as the work content of the staff member. If there is no correct option among the multiple presented work content candidates, the control unit 11 may accept input of the correct work content from the user. In this way, the work content information of the staff member determined based on feedback from the user (correct work content) may be used as training data to re-train the work content estimation model (machine learning model). The more this technology is used in caregiving, nursing, medical care, and other settings, the more the accuracy of work content estimation will improve, and the work estimation technology can be further improved.
  • the control unit 11 may cause the output unit 14 to display the user interface screen 300 of FIG. 5.
  • the user interface screen 300 shown in FIG. 5 is a screen for selecting the work content.
  • the user interface screen 300 may include all or part of the multiple work content candidates estimated in step S102.
  • the user interface screen 300 may display the work content candidates one by one alongside the radio buttons 301-303 so that the user can select one. In this case, the work content candidates may be displayed from the top in descending order of estimated likelihood. If the optimal work content candidate is not displayed, the user may be able to select the radio button 304 and enter it into the text field 305.
  • the control unit 11 accepts an input such as a click operation on the OK button 306 of the user interface screen 300 of FIG.
  • the control unit 11 determines the work content corresponding to the selected radio button 301-303 as the work content of the staff member. Furthermore, when the control unit 11 receives an input such as a click on the end button 307 on the user interface screen 300 in FIG. 5, the control unit 11 ends the work recording.
  • the work recording technology estimates multiple candidates for the work content that the staff member has performed up to that point based on the environmental information related to the work content of the staff member, and presents the multiple estimated work content candidates in association with time information.
  • the user only needs to select an appropriate one from the presented work content candidates.
  • the work is complex and it is difficult to estimate only one correct work content.
  • there are many similar tasks, such as excretion assistance and toilet cleaning, laundry and laundry collection it is also difficult to correctly distinguish between them and estimate only one correct work content.
  • the usability of this technology is increased by presenting several candidates rather than narrowing down the work content candidates estimated from the environmental information to one.
  • the work recording technology according to this embodiment by presenting multiple work content candidates, the efficiency of the work recording work of the staff member is improved and the work recording technology is improved.
  • the user can simply view the multiple work content candidates in order from top to bottom, which can further improve the efficiency of work recording work.
  • estimation accuracy can be improved if the environmental information includes posture information in addition to position information and time information on the facility floor plan. Furthermore, the higher the total estimated likelihood value for the multiple work content candidates presented, the higher the probability that the correct answer will be included in the options.
  • the number of presented tasks is three or more, preferably five or more, and at most about seven.
  • the number of presented task candidates may be determined based on the total value of the estimated likelihoods for the multiple task candidates.
  • the number presented may be set so that the total value of the estimated likelihoods is equal to or greater than a predetermined percentage.
  • the predetermined percentage is preferably 99% or more, but may be 95% or more, 90% or more, 80% or more, or a lower percentage, or may be changed as appropriate.
  • Such a predetermined percentage of the total value of the estimated likelihoods may be optimized so that a more correct task candidate is selected.
  • the control unit 11 may issue an alert by sound or vibration.
  • the information processing device sequentially estimates candidates for work content that the staff has been performing up to a certain point in time.
  • the control unit 11 extracts an appropriate data group and performs the estimation, it is considered that the estimated work content candidate will not change while one work content is being performed.
  • a work content candidate with a predetermined estimated likelihood or higher is switched, it is highly likely that the staff has just finished a certain work content.
  • control unit 11 may temporarily suspend the switching of the presented work content candidate, and continue to display the work content candidate immediately before the switch on the output unit 14, and issue an alert by sound or vibration.
  • the predetermined estimated likelihood may be, for example, 20% or more. However, the predetermined estimated likelihood may be less than 20% or more than 20%.
  • an alert may be issued with sound and vibration.
  • the specified time may be, for example, five minutes. However, it may be less than five minutes or more than five minutes. In this way, each time the work reaches a certain point, the user can check the estimated result and send feedback, thereby making it possible to accurately record what work has been performed up to that point.
  • the environmental information may include at least one of staff attendance information and work schedule information. By using this information, it is possible to estimate candidate work contents with greater accuracy. If special work contents or work contents not included in the work schedule information are estimated, an alert may be issued, for example, by sound or vibration, to attract more attention.
  • the work recording technology may retrain the machine learning model using information on the work content of staff members determined based on feedback from users as training data. This will improve the accuracy of work content estimation as this technology is used in caregiving, nursing, medical care, and other settings, and the work recording technology can be further improved.
  • a method using machine learning has been exemplified as a method for estimating multiple work content candidates.
  • preprocessing may be performed on the acquired environmental information.
  • the method used for estimation is not limited to machine learning.
  • multiple work content candidates may be estimated using statistical methods such as a multiple regression model or a Kalman filter.
  • control unit 11 may analyze or compile statistics on the records of staff work content and output the results in a visualized form such as a graph.

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