Information processing systems and methods

Abstract

To support users in smoothly completing tasks. [Solution] The information processing system (1) includes a storage unit (110) that stores a personal information DB (111), a task information DB (112), and a reminder management DB (113), and a control unit (120) that includes a registration unit (121), an estimation unit (122) that estimates the emotions of users assigned to incomplete task information, an adjustment unit (123) that adjusts the settings for reminders to users in the task information based on the emotion estimation results, and a reminder execution unit (124).

Description

Technical Field

[0001] The present disclosure relates to an information processing system and method.

Background Art

[0002] Generally, tasks with deadlines are assigned as "tasks" to users who are in charge of business operations. And an information processing system for managing tasks as information in a database sends a reminder notification to the user assigned to the task information before the deadline if the task information registered in the database has not been completed by the deadline.

[0003] Patent Document 1 discloses a technology related to a schedule management system for sending a reminder notification to a corresponding user about a registered schedule. The schedule management system according to Patent Document 1 senses the situation of the user and calculates an evaluation value from the sensed result. And the schedule management system sends a reminder notification to the user when the evaluation value is equal to or greater than a threshold value.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Here, reminder notifications from the information processing system are effective in helping users complete tasks by the deadline. However, the frequency and content of reminder notifications for task information can have different effects on task progress and completion depending on the user's psychological state. In other words, depending on the user's psychological state, even if the task content is the same, a higher frequency of reminders may promote task completion, or conversely, hinder it. Similarly, depending on the user's psychological state, even if the task content is the same, the content of the reminder may affect the user's performance in completing the task. Therefore, reminder settings that take the user's psychological state into consideration are required.

[0006] The purpose of this disclosure is to provide an information processing system and method for supporting the smooth execution of tasks by users, in light of the above-mentioned issues. [Means for solving the problem]

[0007] The information processing system described herein includes an estimation unit that estimates the emotions of a user assigned to incomplete task information, and an adjustment unit that adjusts the settings for reminders to the user in the task information based on the results of the emotion estimation.

[0008] The information processing method relating to this disclosure involves a computer estimating the emotions of a user assigned to incomplete task information, and adjusting the reminder settings for the user in the task information based on the results of the emotion estimation. [Effects of the Invention]

[0009] This disclosure will help users perform tasks smoothly. [Brief explanation of the drawing]

[0010] [Figure 1] This block diagram shows the overall configuration of the reminder system, including the information processing system, related to this disclosure. [Figure 2] This block diagram shows the configuration of a reminder server, which is an example of an information processing system related to this disclosure. [Figure 3] This block diagram shows the configuration of the information processing terminal related to this disclosure. [Figure 4] This flowchart shows the process for adjusting reminder settings related to this disclosure. [Figure 5] This flowchart shows the process for adjusting reminder settings related to this disclosure. [Figure 6] This flowchart shows the flow of the reminder notification process related to this disclosure. [Figure 7] This block diagram shows the overall configuration of the reminder system, including the information processing system, related to this disclosure. [Figure 8] Block diagram showing the configuration of the reminder server related to this disclosure. [Figure 9] This block diagram shows the configuration of an information processing terminal, which is an example of the information processing system related to this disclosure. [Figure 10] This block diagram shows the overall configuration of the reminder system, including the information processing system, related to this disclosure. [Modes for carrying out the invention]

[0011] In the following, specific embodiments of this disclosure will be described in detail with reference to the drawings. In each drawing, the same elements are denoted by the same reference numerals, and redundant explanations will be omitted where necessary for clarity.

[0012] (Embodiment 1) The information system according to this embodiment 1 estimates the emotions of users assigned to incomplete task information on the server side, and adjusts the reminder settings for the user in the task information based on the emotion estimation result. This supports the smooth execution of tasks by the user.

[0013] Figure 1 is a block diagram showing the overall configuration of the reminder system 1000, which includes the information processing system 1 according to this disclosure. The reminder system 1000 comprises a reminder server 100, information processing terminals 200-1 to 200-n, and biometric information measuring devices 300-1 to 300-n. Hereinafter, n is a natural number. The reminder server 100, information processing terminals 200-1 to 200-n, and biometric information measuring devices 300-1 to 300-n are each connected to communicate via a communication network N. Hereinafter, the communication network N is a wired, wireless, or both type of communication network. The communication network N may include, for example, the Internet. Each of the information processing terminals 200-1 to 200-n shall have equivalent functions. Therefore, in the following description, information processing terminals 200-1 to 200-n may be simply referred to as "information processing terminal 200". Furthermore, each of the biological information measuring devices 300-1 to 300-n shall have equivalent functions. Therefore, in the following description, biological information measuring devices 300-1 to 300-n may be simply referred to as "biological information measuring device 300". In addition, each of users U1 to Un shall be assigned a task with at least a deadline as task information. Each of users U1 to Un shall process and complete the task information assigned to them using the information processing terminal 200, etc. At least some of users U1 to Un may be persons belonging to an organization such as a company. Therefore, in the following description, users U1 to Un may be simply referred to as "user U".

[0014] The reminder system 1000 is an information processing system that is assigned to each of the users U1 to Un and sends reminder notifications to the information processing terminals 200 and the like of the assigned user U for the unfinished task information registered in the database described later. Here, "unfinished" refers to a state where the status of the task information is not marked as "completed", meaning that the deadline of the task information has passed, or the deadline of the task information has not passed and the task is in progress, that is, it is being processed. Note that the number of users to be reminded may be at least one or more. Therefore, the reminder system 1000 may be provided with at least one set of information processing terminals 200 and biological information measuring devices 300 and a reminder server 100. Also, the reminder server 100 is an example of the information processing system 1 according to the present embodiment. Therefore, it can be said that the reminder system 1000 includes the information processing system 1.

[0015] The biological information measuring device 300 is a device that measures the biological information of the user U who is the measurement target. The biological information measuring device 300 may continuously measure the biological information at regular intervals. That is, the biological information measuring device 300 may constantly monitor the biological information of the user U. Here, the biological information includes, but is not limited to, biomarkers such as heart rate, skin conductance response, and movement. For example, the biological information measuring device 300 may measure measurement data of a plurality of channels and biological information using sensors for measuring electroencephalogram (EEG (Electro Encephalo Graphy)), electrocardiogram (ECG (Electro CardioGram)), and the like. For example, the biological information measuring device 300 may be an electroencephalograph or an electrocardiogram measuring device.

[0016] Alternatively, the biometric information measuring device 300 may be installed in close proximity to each user U, or it may be a wearable terminal attached to each user U. In the example in Figure 1, the biometric information measuring device 300-1 measures the biometric information of user U1. Similarly, the biometric information measuring device 300-n measures the biometric information of user Un. For example, the biometric information measuring device 300-1 includes the biometric information measured from user U1, along with user U1's identification information and measurement date and time, etc., in a registration request and sends the registration request to the reminder server 100 via the communication network N. The reminder system 1000 may also include a dedicated biometric information analysis server that collects and analyzes the biometric information measured from each user U by each biometric information measuring device 300-1 to 300-n via the communication network N. In that case, the biometric information analysis server sends the analysis results and measurement results for each user U, as well as a registration request including user U's identification information and measurement date and time, etc., to the reminder server 100 via the communication network N.

[0017] Alternatively, for example, the biometric information measuring device 300-1 may be connected to the information processing terminal 200-1 used by user U1 via short-range wireless or wired communication. In this case, the biometric information measuring device 300-1 may transmit the measured biometric information, etc., to the information processing terminal 200-1. The information processing terminal 200-1 may then transmit a registration request, including the biometric information received from the biometric information measuring device 300-1, the identification information of user U1, and the measurement date and time, etc., to the reminder server 100 via the communication network N.

[0018] The information processing terminal 200 is an information processing device used by the user U to process tasks corresponding to task information. In the example of FIG. 1, the information processing terminal 200-1 is used by the user U1, and hereinafter, similarly, the information processing terminal 200-n is shown as being used by the user Un. However, it is not necessary for there to be one information processing terminal 200 per user U, and one information processing terminal 200 may be shared by multiple users U. Also, one user U may use multiple information processing terminals 200. In these cases, the information processing terminal 200 shall identify the user U using it based on login information. Note that the detailed configuration of the information processing terminal 200 will be described later.

[0019] Note also that the information processing terminal 200 is assumed to be communicably connected, either wired or wirelessly, to various peripheral devices such as a camera, a microphone, an input device for operation information, a display device, a speaker, etc., which have a configuration not shown in the figure. Note also that all or part of the above peripheral devices may be built into the information processing terminal 200. The camera captures the face, movements, etc. of the user U and outputs the captured image data to the information processing terminal 200. Here, the image data is, for example, a general image format such as JPEG (Joint Photographic Experts Group) or PNG (Portable Network Graphics) of a predetermined image size, but is not limited to these. The microphone acquires the speech and tone of voice of the user U as audio data and outputs the acquired audio data to the information processing terminal 200. Here, the audio data is uncompressed audio data or compressed audio data in an audio file format such as WAV (Waveform Audio Format) or AIFF (Audio Interchange File Format). However, the audio file format is not limited to these. The input device is a keyboard, a mouse, etc. The input device acquires the operation information of the keyboard and mouse by the user U and outputs the acquired operation information to the information processing terminal 200. The display device displays the display information input from the information processing terminal 200 on the screen. The speaker outputs the audio data input from the information processing terminal 200.

[0020] Figure 2 is a functional block diagram showing the configuration of a reminder server 100, which is an example of the information processing system 1 according to this disclosure. The reminder server 100 is an information processing device that manages personal information, task information, and reminder setting information for users U assigned to incomplete task information. The "reminder setting information" is an example of "reminder-related settings". The reminder server 100 also performs reminder notification processing for users U assigned to incomplete task information based on the reminder setting information. The reminder server 100 may be implemented as a computer system with distributed or redundant functions using multiple computer devices. The reminder server 100 comprises a storage unit 110, a control unit 120, and an IF (Interface) unit 130.

[0021] The storage unit 110 includes, for example, a non-volatile storage device such as a hard disk or flash memory, and a memory such as RAM (Random Access Memory), i.e., a volatile storage device. The storage unit 110 stores a personal information database (DB) 111, a task information database 112, and a reminder management database 113. The personal information database 111, task information database 112, and reminder management database 113 can be said to correspond to storage areas managed by database management software. Furthermore, the task information database 112 may include the reminder management database 113.

[0022] Personal Information DB111 is a database that manages user information, biometric data, operation history, personality information, etc., for each user U. User information, biometric data, operation history, personality information, etc., may also be called personal information. User information may include identification information that identifies each user U, personal information such as name, and organizational attribute information such as department, position, and job title. User information also includes the recipient of reminder notifications, i.e., destination information. Destination information may include, but is not limited to, the email address of user U, identification information and address information of the information processing terminal 200 used by user U, the login ID of user U, and account information for information systems such as SNS (Social Networking Service).

[0023] The biometric information set is a collection of biometric information and measurement date and time, etc., measured by the biometric information measuring device 300 described above. The biometric information set is associated with personal information corresponding to the identification information of user U included in the registration request for biometric information, etc., received from the biometric information measuring device 300. The biometric information set may also include at least one or both of the following: image data of user U's facial expression captured during operation of the information processing terminal 200, or voice data of user U recorded during operation of the information processing terminal 200. The image data and voice data are associated with the date and time when they were captured or recorded.

[0024] The operation history may include input information from input devices such as the keyboard and mouse, recorded when each user U operates the information processing terminal 200. The input information from input devices may also include finger pressure information during keyboard input. Furthermore, the operation history associates the above-mentioned input information with the date and time it was recorded.

[0025] Personality information should include information that each user U has self-analyzed by answering questionnaires, etc., as well as information that indicates user U's personality as evaluated and analyzed by related parties such as user U's superiors, colleagues, and subordinates.

[0026] Task Information DB112 is a database that manages the content, progress, and processing history of task information assigned to each user U. For example, task information may include task ID, task name, task content, assignee, completion deadline, completion date or completion flag, category, affiliated project, stakeholders, importance or priority, remarks, etc. The assignee is user information such as the user ID to which the task information is assigned. The completion deadline may also be called the scheduled completion date and time of the task information. Stakeholders are the user information of the assignee's superiors, colleagues, subordinates, etc., or users belonging to the affiliated project. Furthermore, task information may include multiple subtasks. Subtask information may include subtask ID, subtask name, subtask content, completion deadline, completion date or completion flag, etc. A subtask is a milestone that specifically subdivides a task. For example, if the task is a presentation, subtasks may include information gathering, graph creation, document creation, proofreading, presentation, etc. Task information may also include the level of interest of the assignee user U in the task content, the assignee's usual work content, etc.

[0027] The progress status is information indicating the degree of progress and status of task information for each task ID. The progress status may also be able to identify whether the corresponding task information is incomplete. The processing history includes task information for which the completion date has been entered or the completion flag is turned on, and at least the task ID. Note that the task information managed in the task information DB112 is not limited to what is described above.

[0028] The reminder management DB113 is a database that manages reminder settings for user U, who is the person in charge of the task information managed in the task information DB112, i.e., reminder setting information. The reminder management DB113 may, for example, manage the task ID or subtask ID in association with the reminder setting information and the reminder history. The task ID or subtask ID uniquely corresponds to the information contained in the task information DB112 mentioned above. In addition, the reminder management DB113 may further associate the task ID or subtask ID with the destination information for the reminder notification. The destination information is the destination information for user U contained in the personal information DB111 for the person in charge whose user information is associated with the task ID or subtask ID in the task information DB112. The reminder setting information includes the frequency, number and interval of reminders, and the content of the reminder. The reminder setting information may also include the scheduled date and time of the reminder. The content of the reminder may include text information included in the reminder notification, operation instruction information to operate the information processing terminal 200 that receives the reminder notification, etc. Text information is part of the display information shown on the screen by the information processing terminal 200 that received the reminder notification. Action instruction information is information that instructs the information processing terminal 200 on what action to take upon receiving the reminder notification. The action may be, for example, a pop-up display, an alarm sound, or a voice message. If the information processing terminal 200 is a portable information terminal, the action may be vibration of the information processing terminal 200. The reminder history may include the date and time of the reminder notification, the content of the reminder notification, etc.

[0029] The control unit 120 is a control device that controls each component of the reminder server 100. The control unit 120 is a processor such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), FPGA (Field-Programmable Gate Array), or quantum processor (quantum computer control chip). For example, the control unit 120 loads a program from the storage unit 110 into memory and executes the program. The program is a computer program that implements the processing of the information processing method according to this disclosure, although its configuration is not shown. As a result, the control unit 120 realizes the functions of the registration unit 121, estimation unit 122, adjustment unit 123, and reminder execution unit 124. Some or all of the registration unit 121, estimation unit 122, adjustment unit 123, and reminder execution unit 124 may be realized by hardware other than the control unit 120, for example, by a general-purpose or dedicated circuit implemented in a semiconductor device.

[0030] When the registration unit 121 receives a registration request from an information processing terminal 200 or a biometric information measuring device 300, it registers the received information and setting information generated in response to the registration request in the personal information DB 111, task information DB 112, or reminder management DB 113, depending on the information contained in the registration request.

[0031] The estimation unit 122 estimates the emotions of user U assigned to incomplete task information. Specifically, the estimation unit 122 searches the task information DB 112 for task information where the completion date is not entered or the completion flag is off, and identifies the user information assigned as the person in charge to the task information that matches the search. Alternatively, the estimation unit 122 may search the task information DB 112 for incomplete task information by referring to the progress status. Or, the estimation unit 122 may search the reminder management DB 113 for incomplete task information. Then, the estimation unit 122 estimates the emotions of user U corresponding to the user information based on at least one of the biometric information group or operation history included in the identified user information from the personal information DB 111.

[0032] For example, the estimation unit 122 may estimate user U's emotions based on a set of biological information, using physiological biometrics as an evaluation scale. Specifically, the estimation unit 122 may analyze biological information such as heart rate, skin conduction response, electroencephalogram, and electrocardiogram measurement data measured from user U to generate models of user U's concentration level, mental fatigue level, stress level, etc., and estimate the mental state, i.e., user U's emotions, from the models. If the set of biological information is image data or audio data, the estimation unit 122 may estimate user U's emotions based on the set of biological information by processing described later.

[0033] Furthermore, the estimation unit 122 may estimate user U's emotions based on user U's operation history. Specifically, the estimation unit 122 may identify input information from an input device during the time period when user U was processing the retrieved task information, or during the time period immediately before or after that time period, in user U's operation history. For example, if the operation history contains a string related to the relevant task information in the file name, the estimation unit 122 may identify the time period when that file was being edited as the time period when user U was processing the retrieved task information. Alternatively, if the operation history includes a specific application used to process the relevant task information, the estimation unit 122 may identify the time period when that application was used as the time period when user U was processing the retrieved task information. Alternatively, the estimation unit 122 may identify image data and voice data of user U during the time period identified from user U's operation history as user U's biometric information from the biometric information group in the personal information DB 111. Therefore, it can be said that the input information etc. identified by the estimation unit 122 includes at least one or both of user U's operation history or biometric information.

[0034] The estimation unit 122 then analyzes user U's behavior, key input content, finger pressure during key input, typing speed, facial expressions, voice tone, and voice from the identified input information using an AI (Artificial Intelligence) based motion prediction algorithm. Specifically, the estimation unit 122 may use methods such as neural networks, support vector machines, decision trees, and k-nearest neighbors as the AI-based motion prediction algorithm. Here, the estimation unit 122 may estimate user U's emotions from the identified input information. For example, the estimation unit 122 may use an identification method based on a learning model generated by machine learning the combinations of each input information item and the corresponding emotions in advance, for emotion estimation based on key input content, finger pressure during key input, typing speed, facial expressions, voice tone, and voice.

[0035] Furthermore, the estimation unit 112 may perform emotion estimation of user U based on user U's voice. In this case, known voice-based emotion recognition techniques may be used for voice-based emotion estimation. For example, for voice-based emotion estimation, statistical quantities (mean, variance, slope, etc.) of features such as pitch (frequency) and volume extracted multiple times in a time series may be calculated, and the emotion contained in the voice may be estimated by estimating the emotion category to which the feature vector belongs and its coordinate value in the emotion space from the multidimensional feature vector converted from the voice signal. Here, the machine learning methods described above may be used for emotion estimation based on the feature vector. Then, the estimation unit 122 may estimate user U's emotion based on the above analysis results.

[0036] Furthermore, the estimation unit 122 may analyze the user's emotional state by analyzing the user's typing speed and key input content during the processing of specific task information from the operation history. For example, the estimation unit 122 may estimate the emotional state based on typing speed and rhythm. For instance, fast typing speeds often indicate concentration and positive emotions, while slow typing may indicate negative emotions such as high stress or difficulty in processing the task information being processed. Also, if the typing rhythm changes at regular intervals, it may indicate stable emotions, while irregular rhythms may indicate anxiety or impatience. The estimation unit 122 may also use keystroke dynamics technology to measure the time each key is held down and estimate the emotional state. For example, long key press times may indicate fatigue or stress. Additionally, a high error rate may indicate that the user is experiencing stress. Therefore, the estimation unit 122 should take these factors into account when estimating the emotional state of user U based on typing speed and key input content. In this context, typing speed refers to an indicator that measures how many characters can be entered within a certain amount of time. For example, it measures the number of characters that can be entered per minute (WPM: Words Per Minute). For instance, if user U can enter 50 words per minute, their typing speed is 50 WPM.

[0037] Furthermore, the estimation unit 122 may estimate user U's emotions based on a combination of user U's biometric information and operation history. In addition, the estimation unit 122 may estimate user U's emotions by adding user U's personality information to at least one of the biometric information and operation history.

[0038] Furthermore, the estimation unit 122 may estimate user U's emotion as one of several levels in a predetermined index indicating user U's psychological state in response to task information. Specifically, the estimation unit 122 may estimate user U's emotion level using the aforementioned biometric information group or operation history. For example, the estimation unit 122 may determine positive emotion on a three-level scale, or negative emotion on a three-level scale. In this case, for example, the estimation unit 122 estimates a larger number representing the level of positive emotion as user U's positive emotion towards task information increases. Alternatively, the estimation unit 122 estimates a larger number representing the level of negative emotion as user U's negative emotion towards task information increases. Alternatively, the emotion levels may be set to three levels: "negative" as level 1, "positive and non-negative" as level 2, and "positive" as level 3. Alternatively, the degree from positive to negative may be used as an index of user U's psychological state. For example, if the emotional level is set on a scale of 1 to 10, levels 1 to 5 may represent positive emotions, and levels 6 to 10 may represent negative emotions. In this case, level 1 represents a higher level of positive emotion than level 5, and level 10 represents a higher level of negative emotion than level 6. Note that the emotional level is not limited to this example, as long as there are two or more levels. Alternatively, the estimation unit 112 may simply estimate the level that indicates the user U's emotion towards the task information is at least one level of positive or negative emotion. Alternatively, the estimation unit 122 may estimate the levels of the user U's positive and negative emotions towards the task information as numerical values.

[0039] User U's emotions towards task information may include, for example, the following: If User U repeatedly writes and deletes while editing a file related to specific task information, it is possible that User U is having difficulty processing that task. In this case, the estimation unit 122 may simply estimate User U's emotions towards the specific task information as "negative" without classifying them into levels. Conversely, if User U does not repeatedly write and delete while editing a file related to specific task information, it may simply be estimated as "positive." Alternatively, the level of emotion may be classified according to the editing time and the number of characters repeatedly edited when writing and deleting are repeatedly performed on the file related to the specific task information. For example, if the editing time and number of characters are below a predetermined value, the estimation unit 122 may estimate a higher level of positive emotion, and if they are above the predetermined value, it may estimate a higher level of negative emotion compared to when they are below the predetermined value. This allows the settings related to reminders to be adjusted to appropriate information according to the level. Furthermore, when estimating the level of emotion based on User U's voice, for example, a trained model that has been machine-learned may be used. For example, an emotion level estimation AI model can be used that takes a multidimensional feature vector converted from an audio signal as input and outputs a level of positive or negative emotion. The input data of the multidimensional feature vector converted from the audio signal and the output data of the emotion level are used as training data. Machine learning is then performed on the emotion level estimation AI model using this training data. As a result, the estimation unit 122 may use the trained model of the emotion level estimation AI model that has undergone machine learning to estimate the emotion level based on the user U's voice. In this way, the settings related to reminders can be adjusted to appropriate information according to the level.

[0040] Furthermore, the estimation unit 122 may estimate user U's emotions at the time new task information is assigned to user U. In other words, the estimation unit 122 may estimate user U's emotions from biometric information measured at the time new task information is assigned to user U or from acquired operation history in the most recent time period. This allows for a more accurate estimation of user U's emotions regarding the assigned task information.

[0041] Furthermore, the estimation unit 122 may estimate user U's emotions multiple times while the task information is incomplete. For example, the estimation unit 122 may estimate user U's emotions multiple times using measured biometric information and acquired operation history while user U is processing specific task information. This makes it possible to understand changes and trends in user U's emotional level during processing specific task information. Therefore, the reminder settings described later can be adjusted more appropriately.

[0042] Furthermore, the estimation unit 122 may estimate the user's emotions by taking into account the completion status of task information previously handled by the user. The completion status here refers to actual processing information regarding task information, such as the processing content of completed task information, the relationship between reminder notifications and processing dates, and the relationship between the deadline and the actual completion date. Specifically, the estimation unit 122 may refer to the processing history of the task information DB 112, identify past task information related to the task information that the user U is currently processing, i.e., incomplete, and estimate the user's emotions regarding the task information currently being processed by taking into account the completion status of the identified past task information. For example, the estimation unit 122 may identify past task information that is similar to the task information currently being processed in terms of task content, category, affiliated project, stakeholders, or importance. Then, the estimation unit 122 may estimate the user's emotions regarding the task information currently being processed by taking into account the difference between the deadline and the actual completion date of the identified past task information, the progress in response to reminder notifications, etc. For example, if the actual completion date of a identified past task was earlier than the deadline, it can be inferred that the user felt good about that task. Therefore, in such cases, the estimation unit 122 may infer that user U's emotions regarding the task currently being processed are positive, or that the level of positive emotion is higher. Conversely, if the actual completion date of a identified past task was close to or after the deadline, the estimation unit 122 may infer that user U's emotions are negative, or that the level of negative emotion is higher. The estimation unit 122 may also infer user U's emotions from user U's emotions or the progression of emotions when user U checked the reminder notification for the identified past task, or from the progression of user U's emotions in the past regarding the task currently being processed. Alternatively, the estimation unit 122 may refer to the personal information DB 111 and infer user U's emotions at the time based on user U's biometric information or operation history during the processing period of the identified past task. The estimation unit 122 then takes into account the estimation results of user U during the processing period of the identified past task information to estimate user U's emotions in the currently processing task information.This may improve the accuracy of estimating user U's emotions in relation to the assigned task information. However, the emotion estimation process is not limited to these methods, and known emotion estimation techniques may also be used.

[0043] The adjustment unit 123 adjusts the reminder settings for user U in the task information based on the emotion estimation results by the estimation unit 122. Specifically, the adjustment unit 123 updates the reminder setting information in the reminder management DB 113 for the relevant task information based on the emotion estimation results by the estimation unit 122. For example, the adjustment unit 123 may determine the initial setting of the reminder setting information based on the emotion estimation results at the time new task information is assigned to user U, and register the determined initial setting as reminder setting information in the reminder management DB 113. The adjustment unit 123 may also update the reminder management DB 113 to change the reminder setting information based on the emotion estimation results of user U in incomplete task information. Furthermore, the adjustment unit 123 may update the reminder management DB 113 to change the reminder setting information in incomplete task information based on the continuously estimated changes in user U's emotions. Furthermore, the adjustment unit 123 may adjust the reminder setting information to include all the information registered in the task information, or information focused on some important points, based on the emotion estimation result.

[0044] In particular, the adjustment unit 123 determines whether the emotional level in the estimation result is above a predetermined threshold, and adjusts the reminder settings to change at least one of the number of reminders or the content of the reminders according to the determination result. By adjusting the number of reminders and the content of the reminders in consideration of the user's emotions in this way, it is possible to support the user in performing tasks in line with their psychological state.

[0045] For example, if the threshold is negative emotion level 3, the adjustment unit 123 determines whether user U's emotional level to the newly assigned task information is negative emotion level 3 or higher. If the estimated emotional level of user U is negative emotion level 3, the adjustment unit 123 determines that user U's emotional level is negative emotion level 3 or higher. Also, if the estimated emotional level of user U is "positive" or "other than positive and negative," the adjustment unit 123 may determine that user U's emotional level is less than negative emotion level 3. Similarly, if the estimated emotional level of user U is negative emotion level 1 or 2, the adjustment unit 123 also determines that user U's emotional level is less than negative emotion level 3.

[0046] For example, if the estimated emotion of user U to newly assigned task information is "positive," the adjustment unit 123 should determine the initial settings for the reminder settings information to either reduce the number of reminders or increase the frequency and interval compared to when the estimated emotion is "negative," and register this in the reminder management DB 113. In this case, since user U's psychological state is positive towards the task information, setting the timing of the reminder notification earlier than the default can encourage user U to complete the task. In this case, the adjustment unit 123 should also adjust the reminder settings information by adding wording that urges user U to submit or report quickly. In these cases, since user U's psychological state to the assigned task information is positive, slightly increasing the burden on user U can encourage user U to complete the task.

[0047] On the other hand, if the estimated emotion of user U to the newly assigned task information is "negative," the adjustment unit 123 may decide on an initial setting that uses more polite language for the reminder notification text compared to when the estimation result is "positive," and register it in the reminder management DB 113. For example, if the task information is document creation, the adjustment unit 123 may elaborate on the content of the reminder notification by including information about the user who will review the document in the text. Alternatively, if the estimated emotion is "negative," the adjustment unit 123 may decide on an initial setting that extracts some important points and register it in the reminder management DB 113. Alternatively, if the estimated emotion is "negative," the adjustment unit 123 may decide on an initial setting that reveals information such as the people involved in the relevant task information, for example, that there are people waiting for the completion of the relevant task information, and register it in the reminder management DB 113.

[0048] Alternatively, if the estimated emotion is "negative," the adjustment unit 123 may determine the initial settings for subdivided reminder setting information so that reminder notifications are sent for each completion deadline of the subtask unit of the task information, compared to when the estimated emotion is "positive," and register this information in the reminder management DB 113. For example, if the task information is document creation, the deadline for creating the first draft of the document, i.e., the deadline for requesting review from a supervisor, may be set as subtask 1, and the deadline for revising the document may be set as subtask 2. In this way, the adjustment unit 123 may set tasks for sending multiple reminder notifications from the task information as subtasks and determine the subtasks as the initial settings for the reminder setting information. In these cases, since the psychological state of user U to whom the relevant task information is assigned is negative, the hurdle for task completion can be lowered to support user U in performing the task. Furthermore, the adjustment unit 123 may also adjust the reminder setting information to change at any time between the start and completion of processing the relevant task information by user U, based on the estimated emotion of user U at that time, not limited to the initial settings.

[0049] Furthermore, the set of emotional levels estimated multiple times within a certain period shall be called the emotional psychological state or simply the emotional state. In this case, if negative emotions exceeding a threshold occur consecutively multiple times in the estimation results, the emotional psychological state may be considered "negative." Similarly, if positive emotions exceeding a threshold occur consecutively multiple times in the estimation results, the emotional psychological state may be considered "positive." Here, if the adjustment unit 123 indicates that the emotional psychological state in the multiple estimation results has transitioned from a first state to a second state, and that the second state has been maintained for a certain period of time, it may adjust the settings related to the reminder. For example, let's say the first state is "positive" and the second state is "negative." In this case, suppose the adjustment unit 123 determines from the multiple estimation results that user U's emotional psychological state has transitioned from "positive" to "negative," and that the "negative" psychological state has been maintained for several hours. In such a case, the adjustment unit 123 may adjust the reminder setting information for the relevant task information to lower the hurdle for task completion as described above.

[0050] On the other hand, the first state is defined as "negative," and the second state as "positive." In this case, the adjustment unit 123 determines, based on multiple estimation results, that user U's emotional psychological state shifted from "negative" to "positive," and that this "positive" psychological state was maintained for several hours. In such cases, the adjustment unit 123 may adjust the reminder settings by changing the timing of the reminder notification for the relevant task information earlier, reducing the number of reminder notifications, or adding wording to the reminder content that urges submission or reporting to be expedited. In these cases, it is considered that user U has overcome the peak of processing the relevant task information, and as described above, by slightly increasing the burden on user U, it is possible to promote user U's task completion. Therefore, the adjustment unit 123 can flexibly adjust reminders based on the transition of user U's emotions, based on multiple estimation results. It should also be noted that the above emotional psychological state can be applied to emotional levels.

[0051] Furthermore, the estimation unit 122 may estimate the user U's level of tension. The estimation unit 122 estimates that user U is in a state of tension when the heart rate velocity among user U's biometric information is above a predetermined speed. The adjustment unit 123 may adjust the reminder setting information for the relevant task information based on the estimation result of user U's level of tension, by including operational instruction information other than screen display, such as voice notifications and changes in keyboard operation, which are displayed as pop-up screens on the screen of the information processing terminal 200. For example, if user U is in a state of tension, the adjustment unit 123 may assume that user U's concentration is scattered. In this case, it is advisable to adjust the reminder setting information for the relevant task information by adding operational instruction information for voice notifications. Alternatively, in this case, the adjustment unit 123 may adjust the reminder setting information for the relevant task information by adding operational instruction information that is displayed as a pop-up screen on the screen of the information processing terminal 200 at a position where user U's gaze is focused, along with a warning sound, and that does not accept other terminal operations until the pop-up screen is checked. Furthermore, if user U is under stress, the adjustment unit 123 may assume that user U is rushing to process the task. In this case, it is advisable to adjust by adding an action instruction to reduce the key input depth to the reminder setting information for the relevant task. Also, if user U is under stress, the adjustment unit 123 may assume that user U is panicking and not calm. In this case, it is advisable to adjust by adding an action instruction to display a pop-up for final confirmation to the reminder setting information for the relevant task.

[0052] The reminder execution unit 124 refers to the reminder management DB 113 to identify the task information to be reminded and sends a reminder notification based on the reminder setting information to the destination information of user U to whom the identified task information is assigned. Specifically, the reminder execution unit 124 identifies a task ID or subtask ID for which the timing of the reminder notification is set to be a predetermined period before the completion deadline of the task information, based on the reminder setting information in the reminder management DB 113. Then, the reminder execution unit 124 identifies the user information set as the person in charge for the identified task ID or subtask ID from the task information DB 112. Then, the reminder execution unit 124 identifies the destination information included in the identified user information from the personal information DB 111. Then, the reminder execution unit 124 generates a reminder notification message that includes the reminder content included in the reminder setting information for the identified task ID or subtask ID and sends the reminder notification message to the destination information via the communication network N. Furthermore, when user U completes the assigned task information, the reminder execution unit 124 registers the completion date and time in the task information DB 112, or updates the completion flag to ON. In this case, the reminder execution unit 124 also registers in the progress status and processing history that the corresponding task information in the task information DB 112 has been completed. In addition, in this case, the reminder execution unit 124 may also delete the information related to the corresponding task information from the reminder management DB 113 and move it to the processing history, etc., in the task information DB 112.

[0053] The IF unit 130 is an interface circuit that communicates between the reminder server 100 and the outside world. Specifically, the IF unit 130 communicates with information processing terminals 200-1 to 200-n and biological information measuring devices 300-1 to 300-n via the communication network N. The IF unit 130 may be implemented as a general-purpose or dedicated circuit implemented in a semiconductor device, for example. Alternatively, the IF unit 130 may be implemented as a combination of the above-mentioned communication circuit and software that controls the communication processing.

[0054] Figure 3 is a block diagram showing the configuration of an information processing terminal 200 according to this disclosure. The information processing terminal 200 comprises a storage unit 210, a control unit 220, and an IF unit 230. The storage unit 210 includes, for example, a non-volatile storage device such as a hard disk or flash memory, and a memory such as RAM, i.e., a volatile storage device. The storage unit 210 stores behavioral information 211 and biological information 212.

[0055] Behavioral information 211 includes user U's image data, sound data, and operation information, etc. Behavioral information 211 may also include information indicating user U's actions, analyzed from the image data, sound data, and operation information, etc. Each piece of data and information in behavioral information 211 is associated with the date and time of acquisition.

[0056] Biological information 212 is biological information measured by the biological information measuring device 300 from user U. Biological information 212 shall include the date and time of measurement.

[0057] The control unit 220 is a control device that controls each component of the information processing terminal 200. The control unit 220 is, for example, a processor such as a CPU, GPU, FPGA, or quantum processor. For example, the control unit 220 loads a program from the storage unit 210 into memory and executes the program. The program, although not shown in the diagram, is a computer program that implements various processes in the information processing terminal 200 according to this disclosure. As a result, the control unit 220 realizes the functions of the acquisition unit 221, the transmission / reception unit 222, and the display control unit 223. Some or all of the functions of the acquisition unit 221, the transmission / reception unit 222, and the display control unit 223 may be realized by hardware other than the control unit 220, for example, by general-purpose or dedicated circuits implemented in a semiconductor device.

[0058] The acquisition unit 221 acquires image data from the camera, capturing the user U's face, movements, etc. The acquisition unit 221 also acquires sound data, including the user U's voice, from the microphone. The acquisition unit 221 also acquires user U's operation information from the input device. The acquisition unit 221 registers the acquired image data, sound data, and operation information as activity information 211 in the storage unit 210, associating them with the acquisition date and time. The acquisition unit 221 also acquires user U's biological information from the biological information measuring device 300, and registers the acquired biological information as biological information 212 in the storage unit 210, associating the measurement date and time with the acquired biological information.

[0059] The transmitting / receiving unit 222 transmits the behavioral information 211 and biometric information 212 registered in the storage unit 210 to the reminder server 100 via the communication network N. The transmitting / receiving unit 222 may transmit data or information each time the acquisition unit 221 acquires data or information, or each time data or information is registered in the storage unit 210. Alternatively, the transmitting / receiving unit 222 may periodically transmit untransmitted data or information from the storage unit 210.

[0060] Furthermore, the transmitting / receiving unit 222 receives reminder notifications from the reminder server 100 via the communication network N. The transmitting / receiving unit 222 then outputs display information, such as messages, included in the received reminder notification to the display control unit 223. If the received reminder notification includes operation instruction information, the transmitting / receiving unit 222 outputs the operation instruction information to the appropriate output destination. For example, if the operation instruction information includes a pop-up display, the transmitting / receiving unit 222 outputs the pop-up display instruction information to the display control unit 223. If the operation instruction information includes an alarm sound or voice message, the transmitting / receiving unit 222 outputs the alarm sound or voice message to the speaker via the IF unit 230. If the operation instruction information includes vibration, the transmitting / receiving unit 222 outputs a vibration instruction to the IF unit 130.

[0061] The display control unit 223 controls the display device to display the display information received from the transmitting / receiving unit 222. When the display control unit 223 receives instruction information for a pop-up display from the transmitting / receiving unit 222, it controls the display device to display a pop-up.

[0062] The IF unit 230 is an interface circuit that enables communication between the information processing terminal 200 and the outside world. Specifically, the IF unit 130 communicates with the reminder server 100 via the communication network N. Furthermore, the IF unit 230 may also communicate with the biometric information measuring device 300 via short-range wireless communication or wired communication. The IF unit 130 also outputs captured images and the like received from the connected camera to the storage unit 110 via the control unit 120. The IF unit 130 also outputs sound data received from the connected microphone to the storage unit 110 via the control unit 120. The IF unit 130 also outputs input information received from the connected input device to the control unit 120. The IF unit 130 also outputs display information received from the control unit 120 to the display device. The IF unit 130 also outputs sound data received from the control unit 120 to the speaker. Furthermore, the IF unit 130 outputs the operation instruction information received from the control unit 120 to the vibration circuit. The IF unit 130 may be implemented, for example, by a general-purpose or dedicated circuit implemented in a semiconductor device. Alternatively, the IF unit 130 may be implemented by a combination of the above-mentioned communication circuit and software that controls the communication process.

[0063] Figure 4 is a flowchart showing the flow of the reminder setting adjustment process when new task information is assigned to user U as per this disclosure.

[0064] For example, User U's supervisor registers new task information, including its contents, completion deadline, and assigned person, as User U, on the information processing terminal. In response, the information processing terminal sends a registration request, including the task information and assigned person, to the reminder server 100 via the communication network N. In response, the registration unit 121 of the reminder server 100 acquires the task information to which User U has been assigned (S101). The registration unit 121 then registers the acquired task information in the task information DB 112. The registration unit 121 then registers the initial reminder settings for the acquired task information in the reminder management DB 113 (S102).

[0065] Furthermore, user U, who has been assigned the above task information, confirms via the information processing terminal 200 that new task information has been assigned to them, in response to contact from their supervisor or notification from the reminder server 100 regarding the person in charge of the task information. Around this time, the biometric information measuring device 300 measures user U's biometric information and transmits the measured biometric information, measurement date and time, and user U's identification information to the information processing terminal 200. In response, the acquisition unit 221 of the information processing terminal 200 acquires user U's biometric information from the biometric information measuring device 300. Also, when user U confirms the assigned task information, the acquisition unit 221 acquires user U's image data, sound data, and behavioral information 211 such as operation information. Then, the transmitting / receiving unit 222 of the information processing terminal 200 transmits a registration request, including the behavioral information 211 and biometric information 212, to the reminder server 100 via the communication network N. Furthermore, the biometric information measuring device 300 may send a registration request, including the measured biometric information, to the reminder server 100 via the communication network N without going through the information processing terminal 200. In this case, the transmitting / receiving unit 222 of the information processing terminal 200 shall send a registration request, including the behavioral information 211, to the reminder server 100 via the communication network N.

[0066] Accordingly, the registration unit 121 of the reminder server 100 obtains a registration request including user U's biometric information and behavioral information from the information processing terminal 200 via the communication network N (S103). Alternatively, the registration unit 121 may obtain a registration request including user U's biometric information from the biometric information measuring device 300 via the communication network N, and a registration request including user U's behavioral information from the information processing terminal 200 via the communication network N. Then, the registration unit 121 registers the biometric information and behavioral information obtained in step S103 into user U's personal information DB 111 (S104).

[0067] Next, after steps S102 and S104, the estimation unit 122 estimates user U's emotions from the personal information DB 111 (S105). At this point, user U has just been assigned new task information and has become aware of it, so the estimation unit 122 estimates user U's emotions assigned to the incomplete task information. Then, the adjustment unit 123 adjusts the reminder settings corresponding to the retrieved task information based on the emotion estimation result (S106). For example, the adjustment unit 123 adjusts by determining the changes to the reminder setting information according to whether the emotion estimation result is "positive," "negative," or "other than positive and negative." After that, the adjustment unit 123 updates the reminder management DB 113 with the adjusted reminder setting information (S107). Then, the reminder server 100 finishes the reminder setting adjustment process.

[0068] Figure 5 is a flowchart showing the flow of the reminder setting adjustment process when task information assigned to user U under this disclosure is being processed.

[0069] For example, suppose user U is using the information processing terminal 200 to perform operations related to task information assigned to them. Around this time, as described above, the biometric information measuring device 300 measures user U's biometric information, and the acquisition unit 221 of the information processing terminal 200 acquires user U's image data, sound data, and behavioral information 211 such as operation information. Then, as described above, the transmitting / receiving unit 222 of the information processing terminal 200 sends a registration request including the behavioral information 211 and biometric information 212 to the reminder server 100 via the communication network N. Alternatively, as described above, the biometric information measuring device 300 may send a registration request including the measured biometric information, etc., to the reminder server 100 via the communication network N without going through the information processing terminal 200. In this case, the transmitting / receiving unit 222 of the information processing terminal 200 will send a registration request including the behavioral information 211 to the reminder server 100 via the communication network N.

[0070] In response to these, the registration unit 121 of the reminder server 100 obtains a registration request including the biometric information and behavioral information of user U, similar to step S103 described above (S201). Then, the registration unit 121 registers the biometric information and behavioral information obtained in step S201 into the user U's personal information DB 111 (S202).

[0071] Subsequently, the estimation unit 122 determines whether user U is processing task information based on the behavior information (S203). For example, the estimation unit 122 identifies user U's behavior information registered in the personal information DB 111 in step S202 from the personal information DB 111. Then, the estimation unit 122 refers to the task information DB 112 and, for example, determines whether user U is processing specific task information based on the operation history in the behavior information, such as the file name being edited or the application being used.

[0072] In step S203, if it is determined that user U is processing task information (YES in S203), the estimation unit 122 estimates the changes in user U's emotions from the personal information database 111 (S204). For example, the estimation unit 122 searches the personal information database 111 for a certain period of time from the present to a predetermined time ago for user U's biometric information and operation history. At this time, the estimation unit 122 may also search the personal information database 111 for the biometric information and operation history at the time when user U was processing task information within that period. Then, the estimation unit 122 estimates the changes in user U's emotions by performing various analyses on the retrieved biometric information and operation history for that period, as described above. Note that the estimation unit 122 may estimate emotions at a single point in time, not just the changes in emotions over a certain period.

[0073] Then, the adjustment unit 123 adjusts the reminder settings corresponding to the retrieved task information based on the estimation results of the emotional transition (S205). For example, if the adjustment unit 123 indicates that the emotional level transition in multiple estimation results has moved from the first level to the second level and the second level has been maintained for a certain period of time, it may adjust the settings by determining the changes to the reminder setting information as described above, according to the trend of the transition. After that, the adjustment unit 123 updates the reminder management DB 113 with the adjusted reminder setting information (S206). Then, the reminder server 100 terminates the reminder setting adjustment process.

[0074] Furthermore, if it is determined in step S203 that user U is not currently processing task information (NO in S203), the reminder server 100 terminates the reminder setting adjustment process.

[0075] Figure 6 is a flowchart showing the flow of the reminder notification process according to this disclosure. First, the reminder execution unit 124 of the reminder server 100 determines at a predetermined timing whether or not there is task information to be reminded in the task information DB 112 (S301). The predetermined timing may be, for example, a regular interval. If it is determined in step S301 that there is no task information to be reminded, the reminder execution unit 124 executes step S301 again after a certain period of time.

[0076] In step S301, if it is determined that there is task information to be reminded, the reminder execution unit 124 identifies user U, who is responsible for the relevant task information (S302). Specifically, the reminder execution unit 124 may identify user U by referring to the reminder management DB 113 and the task information DB 112.

[0077] Then, the estimation unit 122 estimates the emotions of user U from the personal information database 111 (S303). For example, the estimation unit 122 estimates the emotions of user U from the personal information database 111 based on the latest biometric data set or operation history, or biometric data set and operation history, etc., of the identified user U. Alternatively, the estimation unit 122 may estimate the emotions of user U from the personal information database 111 based on multiple biometric data sets or operation history, or biometric data set and operation history, etc., of the identified user U over a certain period. Specifically, the estimation unit 122 estimates the emotions of user U in the same manner as in step S107 or S204 described above.

[0078] Then, the adjustment unit 123 adjusts the reminder settings corresponding to the relevant task information based on the emotion estimation result (S304). For example, the adjustment unit 123 may make the adjustment by determining the changes to the reminder setting information, similar to steps S108 or S205 described above. Then, the adjustment unit 123 updates the reminder management DB 113 with the adjusted reminder setting information. After that, the reminder execution unit 124 determines whether the relevant task information is a target for a reminder in the adjusted settings (S305).

[0079] If the task information in step S305 is determined not to be subject to a reminder, the reminder execution unit 124 suspends the reminder notification (S307). At this time, the registration unit 121 may register the date and time of the suspension of the reminder notification in the reminder history of the reminder setting information corresponding to the task information in the reminder management DB 113. Alternatively, the adjustment unit 123 may readjust the reminder setting information in response to the suspension of the reminder notification and update the reminder management DB 113 with the readjusted reminder setting information.

[0080] On the other hand, if the relevant task information is determined to be a reminder target in step S305, the reminder execution unit 124 sends a reminder notification to user U's information processing terminal 200 based on the adjusted reminder settings (S306). The registration unit 121 may register the date and time of sending the reminder notification in step S306, its content, etc., in the reminder history of the reminder management DB 113. By utilizing the reminder history, it is possible to improve the accuracy of estimating user U's emotions regarding future task information and adjusting reminder settings.

[0081] In accordance with step S306, for example, the information processing terminal 200 receives a reminder notification from the reminder server 100 via the communication network N and performs processing according to the received reminder notification. For example, the information processing terminal 200 displays display information such as a message included in the reminder notification on the display device. Alternatively, if the reminder notification includes operation instruction information, the information processing terminal 200 displays a pop-up on the display device, outputs an alarm sound or voice message from the speaker, and performs vibration, etc., as described above.

[0082] This allows user U, who has been reminded, to receive appropriate reminders about incomplete tasks that are tailored to their emotional state. Therefore, for user U who is working on tasks, the content and frequency of reminders can be appropriately changed according to user U's psychological state, thereby enhancing the effectiveness of the reminders. This enables efficient task management and supports user U in smoothly completing tasks.

[0083] In other words, since reminder settings can be customized according to the estimated emotions of user U, effective and personalized task management tailored to individual needs can be achieved. Furthermore, it is possible to identify a series of mental states that significantly affect user U's behavioral performance, such as concentration, mental fatigue, and stress levels, analyze these mental states, and provide reminders for planned schedules necessary for task completion.

[0084] Furthermore, the reminder execution unit 124 or registration unit 121 should update the task information DB 112 with the progress of the task information each time user U makes progress in processing the task information, and after completion. This allows for analysis of the time required from immediately after the reminder notification until user U starts processing the task information, the processing time, and whether or not the completion deadline was met. The progress status can then be used as the completion status of task information that user U has handled in the past.

[0085] Therefore, as described above, the estimation unit 122 may estimate the user's emotions by taking into account the achievement status of task information that the user U has previously handled. For example, the estimation unit 122 can estimate whether the currently assigned task information is in an area where the user U is good or bad, based on the past achievement status of task information similar to the category and content of the task information assigned to the user U. Therefore, the adjustment unit 123 can adjust the reminder settings for the task information currently assigned to the user U more appropriately based on the emotion estimation result that takes into account the achievement status of task information that the user U has previously handled. For example, the reminder execution unit 124 can send reminder notifications at a frequency that is more individually optimized for the user U.

[0086] Furthermore, if task information includes multiple subtasks, it is possible to implement detailed and highly accurate reminder settings, such as adjusting the granularity of reminder notifications to the subtask level according to the user's emotions or emotional changes. This enables effective reminder notifications for the user and effectively supports task completion.

[0087] (Embodiment 2) The information system according to this second embodiment estimates the emotions of the user assigned to the incomplete task information on the information processing terminal side, and adjusts the reminder settings for the user in the task information based on the emotion estimation result. This supports the smooth execution of tasks by the user, similar to the first embodiment described above.

[0088] Figure 7 is a block diagram showing the overall configuration of the reminder system 1000a, which includes the information processing systems 11 to 11n according to this disclosure. The reminder system 1000a is a modified version of the reminder system 1000 described above. Therefore, the following explanation will focus on the differences from Embodiment 1 described above, and illustrations and explanations of equivalent content will be omitted as appropriate.

[0089] The reminder system 1000a comprises a reminder server 100a, information processing terminals 200a-1 to 200a-n, and biometric information measuring devices 300-1 to 300-n. Each of the reminder server 100a, information processing terminals 200a-1 to 200a-n, and biometric information measuring devices 300-1 to 300-n is connected to communicate via a communication network N. Each of the information processing terminals 200a-1 to 200a-n is assumed to have equivalent functions. Therefore, in the following description, information processing terminals 200a-1 to 200a-n may be simply referred to as "information processing terminal 200a". Furthermore, information processing terminal 200a-1 is an example of the information processing system 11 according to this embodiment. Similarly, hereafter, information processing terminal 200a-n is an example of the information processing system 1n according to this embodiment. Therefore, in the following explanation, each of the information processing systems 11 to 1n may be simply referred to as "information processing system 11".

[0090] Figure 8 is a block diagram showing the configuration of the reminder server 100a according to this disclosure. Compared to the reminder server 100 shown in Figure 2 above, the reminder server 100a has the estimation unit 122 and adjustment unit 123 removed, and the provision unit 125 and update unit 126 added. The other configurations of the reminder server 100a are the same as those of the reminder server 100.

[0091] The control unit 120 loads a program containing the various processes of the reminder server 100a described herein from the storage unit 110 into memory and executes the program. This enables the control unit 120 to implement the functions of the registration unit 121, the provision unit 125, the update unit 126, and the reminder execution unit 124. Note that some or all of the registration unit 121, the provision unit 125, the update unit 126, and the reminder execution unit 124 may be implemented in hardware separate from the control unit 120, such as a general-purpose or dedicated circuit implemented in a semiconductor device.

[0092] The provision unit 125 provides search results by performing searches and other operations in response to search requests from the information processing terminal 200a to the personal information DB 111, task information DB 112, or reminder management DB 113, and transmitting the search results to the requesting information processing terminal 200a. The update unit 126 updates the personal information DB 111, task information DB 112, or reminder management DB 113 in response to update requests from the information processing terminal 200a, and transmits the update results to the requesting information processing terminal 200a.

[0093] Figure 9 is a block diagram showing the configuration of an information processing terminal 200a-1, which is an example of the information processing system 11 according to this disclosure. Compared to the information processing terminal 200 in Figure 3 described above, the information processing terminal 200a-1 has been modified by changing the transmitting / receiving unit 222 to a transmitting / receiving unit 222a, and adding an estimation unit 224 and an adjustment unit 225. The other configurations of the information processing terminal 200a-1 are assumed to be the same as those of the information processing terminal 200.

[0094] The control unit 220 loads a program implementing the information processing method according to this disclosure from the storage unit 210 into memory and executes the program. This enables the control unit 220 to realize the functions of the acquisition unit 221, the transmission / reception unit 222a, the display control unit 223, the estimation unit 224, and the adjustment unit 225. Note that some or all of the acquisition unit 221, the transmission / reception unit 222a, the display control unit 223, the estimation unit 224, and the adjustment unit 225 may be implemented in hardware separate from the control unit 220, for example, in a general-purpose or dedicated circuit implemented in a semiconductor device.

[0095] The transmitting / receiving unit 222a transmits search requests or update requests to the personal information DB 111, task information DB 112, or reminder management DB 113 to the reminder server 100a via the communication network N. The transmitting / receiving unit 222a also receives search results or update results from the personal information DB 111, task information DB 112, or reminder management DB 113 from the reminder server 100a via the communication network N. In addition, the transmitting / receiving unit 222a has the same functions as the transmitting / receiving unit 222 in Figure 3 described above.

[0096] The estimation unit 224 and the adjustment unit 225 have the same functions as the estimation unit 122 and the adjustment unit 123 in Figure 2 described above. However, the estimation unit 224 estimates the emotions of user U using the behavioral information 211 and biometric information 212 stored in the memory unit 210. In addition, the estimation unit 224 estimates the emotions of user U using the search results from the personal information DB 111 and task information DB 112 received by the transmission / reception unit 222a.

[0097] The adjustment unit 225 adjusts the reminder settings for user U in the task information using the search results from the task information DB 112 and reminder management DB 113 received by the transmission / reception unit 222a, and the emotion estimation results from the estimation unit 224. Then, the transmission / reception unit 222a sends an update request, including the adjusted reminder setting information, to the reminder server 100a via the communication network N.

[0098] Furthermore, since the reminder setting adjustment process in this embodiment is generally equivalent to that in Figures 4 and 5 described above, the differences will be explained below. In this embodiment, the registration, search, update, and deletion processes in steps S101 to S109 of Figure 4 to the personal information DB 111, task information DB 112, or reminder management DB 113 shall be interpreted as the transmission of registration requests, search requests, update requests, and deletion requests from the information processing terminal 200a to the reminder server 100a, and the reception of the results of each request. The same applies to steps S201 to S206 of Figure 5.

[0099] Furthermore, the reminder notification process according to this embodiment is generally equivalent to that shown in Figure 6 above, so the differences will be explained in detail below. In step S303 of Figure 6, the emotion estimation process is performed by the estimation unit 224 of the information processing terminal 200a, which estimates the emotion in response to the estimation request from the reminder server 100a. In step S304 of Figure 6, the adjustment process is performed by the adjustment unit 225 of the information processing terminal 200a, and the transmission / reception unit 222a sends an update request including the adjusted reminder setting information to the reminder server 100a.

[0100] Thus, this second embodiment can achieve the same effects as the first embodiment described above.

[0101] (Embodiment 3) The information system according to this third embodiment distributes or provides redundancy of functions between the server and the information processing terminal to achieve the same processing as in the first or second embodiment described above. As a result, it supports the smooth execution of tasks by the user, similar to the first or second embodiment described above.

[0102] Figure 10 is a block diagram showing the overall configuration of the reminder system 1000b, which includes the information processing system 1b according to this disclosure. The reminder system 1000b is a modified version of the reminder system 1000 or 1000a described above. Therefore, the following explanation will focus on the differences from the embodiments 1 or 2 described above, and illustrations and explanations of equivalent content will be omitted as appropriate.

[0103] The reminder system 1000b comprises a reminder server 100b, information processing terminals 200b-1 to 200b-n, and biometric information measuring devices 300-1 to 300-n. Each of the reminder server 100b, information processing terminals 200b-1 to 200b-n, and biometric information measuring devices 300-1 to 300-n is connected to communicate via a communication network N. Each of the information processing terminals 200b-1 to 200b-n is assumed to have equivalent functions. Therefore, in the following description, information processing terminals 200b-1 to 200b-n may be simply referred to as "information processing terminal 200b". The reminder server 100b and information processing terminals 200b-1 to 200b-n are examples of the information processing system 1b according to this embodiment.

[0104] The reminder server 100b shares at least some configurations with the reminder server 100 in Figure 2 and the reminder server 100a in Figure 8. Similarly, the information processing terminal 200b shares some configurations with the information processing terminal 200 in Figure 3 and the information processing terminal 200a-1 in Figure 9. For example, the reminder server 100b may be modified by adding the provision unit 125 and update unit 126 from Figure 8 to the reminder server 100 in Figure 2. The information processing terminal 200b may then have a configuration equivalent to the information processing terminal 200a in Figure 9. In these cases, for example, the reminder server 100b sends the estimation result to the information processing terminal 200b after processing the emotion. The information processing terminal 200b then adjusts the reminder setting information using the received estimation result and sends an update request, including the adjusted reminder setting information, to the reminder server 100b. Alternatively, the information processing terminal 200b may send the estimation result to the reminder server 100b after the emotion estimation process. The reminder server 100b may then adjust the reminder setting information using the received estimation result. Alternatively, the reminder setting adjustment process in Figures 4 and 5 may be performed by the information processing terminal 200b, as in Embodiment 2 described above, to perform both the estimation and adjustment processes. Furthermore, the reminder notification process in Figure 6 may be performed by the reminder server 100b, including the emotion estimation and adjustment processes, as in Embodiment 1 described above. Note that the combination of functional division between the reminder server 100b and the information processing terminal 200b is not limited to these.

[0105] Thus, this third embodiment can also achieve the same effects as the first and second embodiments described above.

[0106] (Other embodiments) Although the above embodiments were described as hardware configurations, the invention is not limited thereto. This disclosure can also be implemented by having the CPU execute computer programs to perform any desired processing.

[0107] In the examples described above, the program includes a set of instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more of the functions described in the embodiments. The program may be stored on a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disc (DVD), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, include temporary computer-readable medium or a communication medium that includes electrically, optically, acoustically or otherwise propagating signals.

[0108] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure are possible, as can be understood by those skilled in the art within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0109] Each drawing is merely illustrative to illustrate one or more embodiments. Each drawing may be associated with one or more other embodiments rather than with only one specific embodiment. As those skilled in the art will understand, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings, for example, to create embodiments not explicitly shown or described. Not all features or steps shown in any one drawing to illustrate an exemplary embodiment are necessarily required, and some features or steps may be omitted. The order of steps shown in any of the drawings may be changed as appropriate. [Explanation of Symbols]

[0110] 1000 Reminder system, N Communication network, 1 Information processing system, 100 Reminder server, 110 Storage unit, 111 Personal information DB, 112 Task information DB, 113 Reminder management DB, 120 Control unit, 121 Registration unit, 122, 224 Estimation unit, 123, 225 Adjustment unit, 124 Reminder execution unit, 130 IF unit, 200 Information processing terminal, 210 Storage unit, 211 Behavioral information, 212 Biological information, 220 Control unit, 221 Acquisition unit, 222 Transmit / receive unit, 223 Display control unit, 230 IF unit, 300 Biological information measuring device, U User

Claims

1. An estimation unit that estimates the emotions of the user assigned to the incomplete task information, An adjustment unit adjusts the settings for reminders to the user in the task information based on the emotion estimation results, An information processing system equipped with the following features.

2. The estimation unit estimates one of a plurality of levels in a predetermined index indicating the user's psychological state in relation to the task information as the emotion. The adjustment unit determines whether the level in the estimation result is above a predetermined threshold, and adjusts the settings to change at least one of the number of reminders or the content of the reminders according to the determination result. The information processing system according to claim 1.

3. The estimation unit estimates the user's emotions multiple times while the task information is incomplete. The adjustment unit adjusts the setting when it indicates that the psychological state of the emotion in the multiple estimation results has transitioned from a first state to a second state, and that the second state has been maintained for a certain period of time. The information processing system according to claim 1 or 2.

4. The estimation unit further takes into account the completion status of tasks previously handled by the user to estimate the emotion. The information processing system according to claim 1 or 2.

5. Computers Estimate the emotions of the user assigned to the incomplete task information. Based on the estimated emotion, adjust the settings for reminders to the user in the task information. Information processing methods.

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