Service proposal system, service proposal method, and service proposal program

Abstract

To provide a service proposal system, a method, and a program which make a potential need of a user to be explicit, propose a service corresponding to the need, and increase a profit of a service providing facility.SOLUTION: A service proposal system includes a service proposal device, a user conversation input device, a user conversation output device, a result output device, and a measurement apparatus. The proposal device includes: a voice conversion unit; a conversation patten storage unit for storing conversation pattern data; a needs classification storage unit for storing needs classification data; a conversation generation unit for generating conversation to the user on the basis of the conversation pattern data, the conversation data, and classified potential needs; a conversation analysis unit for selecting a candidate of an inquiry result and a measurement apparatus; an inquiry result determination unit for determining the inquiry result; a service storage unit for storing one or a plurality of services; and a service selection unit for selecting a service suitable to the user from among the one or more services on the basis of the inquiry result.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a service proposal system, a service proposal method, and a service proposal program. [Background Art]

[0002] With the growing health consciousness in recent years, accommodation facilities such as hotels, hot bath facilities and the like have increasingly provided services aimed at fatigue recovery and health promotion. As services that enhance the effects of fatigue recovery and health promotion, in addition to conventional services such as hot spring therapy, esthetics and massage, exercise therapies such as Pilates and yoga, aroma treatment, dietary therapy and the like are also provided, for example. In addition, the number of business hotels equipped with hot bath facilities is increasing, making these services more easily accessible. By providing such services, accommodation facilities and hot bath facilities can increase their occupancy rate, average customer spend, and repeat rate, thereby leading to an increase in the hotel's revenue.

[0003] Patent Document 1 and Patent Document 2 disclose a method of providing information about accommodation facilities that offer services aimed at fatigue recovery and health promotion. It is desirable that services aimed at fatigue recovery and health promotion be selected according to the user's mental and physical conditions. However, the methods disclosed in Patent Document 1 and Patent Document 2 do not select services according to the user's mental and physical conditions. [Prior Art Documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2018-112888 [Patent Document 2] Japanese Unexamined Patent Application Publication No. 2017-173918 [Patent Document 3] Japanese Unexamined Patent Application Publication No. 2001-175671 [Patent Document 4] Japanese Unexamined Patent Application Publication No. 2014-112285 [Patent Document 5] WO2018 / 225429 publication [Patent Document 6] Japanese Patent Publication No. 2015-195014 [Patent Document 7] Japanese Patent Publication No. 2019-061302 [Patent Document 8] Japanese Patent Publication No. 2019-137673 [Non-patent literature]

[0005] [Non-Patent Document 1] Stephen W. Porges, "An Introduction to Polyvagal Theory: Transforming Mind and Body Through Safety and Connection," Shunjusha, 2018. [Overview of the project] [Problems that the invention aims to solve]

[0006] Patent Document 3 discloses a method by which a user can answer a questionnaire about their health condition and select an appropriate hot spring therapy facility based on their answers. Patent Document 4 discloses a system that provides a program to improve one's physical condition while staying at the accommodation. The method disclosed in Patent Document 3 is limited to hot spring therapy facilities. The system disclosed in Patent Document 4 is intended for users who wish to participate in a program to improve their physical condition. Neither the methods disclosed in Patent Document 3 nor Patent Document 4 can be easily used by users staying at accommodation facilities for tourism or business purposes.

[0007] Patent Document 5 discloses an information processing device that uses biosensors such as body temperature sensors, vein sensors, pulse sensors, heart rate sensors, respiration sensors, sweat sensors, electroencephalogram sensors, excretion prediction sensors, and blood glucose sensors to detect biological information, recognize the user's potential desires, search for word-of-mouth information tailored to those desires, and present it to the user.

[0008] Furthermore, Patent Document 6 discloses a method for measuring activity levels, stress levels, blood pressure values, heart rate, etc., estimating the user's fatigue level, and generating and displaying facility information for services that help recover from fatigue.

[0009] Furthermore, Patent Document 7 discloses a technology that estimates the user's internal state using thermometers, heart rate monitors, and electrocardiographs to identify the user's health condition, and then determines and presents the content of the service to be provided accordingly.

[0010] While Patent Documents 5, 6, and 7 disclose technologies for acquiring and analyzing various biometric information of users and determining and adjusting the service content presented to the user, it is easy to imagine situations where acquiring and analyzing a user's biometric information alone would not allow for understanding the user's potential needs. Therefore, the technology is technically insufficient without being combined with some other technology, and there are also problems in that the application scenarios are not clearly disclosed.

[0011] In view of the above problems, the present invention aims to provide a service proposal system, a service proposal method, and a service proposal program that make users' latent needs for services apparent, propose services that meet those needs, and increase the revenue of facilities that provide those services. [Means for solving the problem]

[0012] A first aspect of the present invention is a service proposal system comprising: a service proposal device; a user conversation input device that receives conversations transmitted from a user; a user conversation output device that outputs conversations transmitted to the user; one or more measuring instruments that measure the user's physical condition; and a result output device that displays a service selected based on a conversation between the service proposal device and the user, or the conversation between the service proposal device and the user and the measurement results from one or more measuring instruments. The service proposal device comprises: a speech conversion unit that converts the user's voice data transmitted from the user conversation input means into text-formatted conversation data by speech recognition; a conversation pattern storage unit that stores conversation pattern data, which is a machine learning model constructed using assumed patterns of conversations between service providers and users at service provision facilities; a needs classification storage unit that stores needs classification data, which is a machine learning model constructed using patterns of conversations with users, tagged with potential needs and services; and a service proposal device that uses text-formatted conversation data to select one or more candidates for the medical interview results by natural language processing and record them in the service provision information. The gist of the system is that it comprises: a conversation analysis unit that selects one or more measuring instruments corresponding to one or more candidates for the medical interview results; a conversation generation unit that generates a conversation to the user based on conversation pattern data, conversation data, medical interview results, data from the start of the conversation with the user up to the time the conversation data is received, a conversation generated by the conversation generation unit, and a judgment result by the result judgment unit; a medical interview result determination unit that determines the medical interview result based on one or more candidates for the medical interview results selected by the conversation analysis unit and the measurement results from one or more measuring instruments; a service storage unit that stores service information describing one or more services provided by the service provider; a service selection unit that selects a service suitable for the user from one or more services based on one or more candidates for the medical interview results or the medical interview result; a result judgment unit that judges the signals transmitted from one or more measuring instruments using reference values ​​described in a reference correspondence table stored in a reference storage unit and transmits the judgment result to the conversation generation unit; and a reference storage unit that stores a reference correspondence table describing reference values ​​for the measurement results measured by the measuring instruments.

[0013] In the first aspect of the present invention, the response expression device that expresses emotion such that the service proposal device has an emotion may further be provided based on a conversation with a user.

[0014] In the first aspect of the present invention, the one or more services may include at least one of a procedure, a warm bath / sauna, a meal, exercise, environment / climate effect, and biofeedback training.

[0015] In the first aspect of the present invention, the biofeedback training may include at least one of heart rate fluctuation biofeedback, myoelectric biofeedback, psychogenic sweating biofeedback, peripheral skin temperature biofeedback, and neurofeedback.

[0016] In the first aspect of the present invention, the potential needs may be classified into any one of "peace of mind", "performance improvement", "fatigue recovery", "autonomic nerve balance adjustment", "improvement of blood and lymph flow", and "recovery improvement through good sleep".

[0017] In the first aspect of the present invention, the one or more measuring instruments may measure at least one of electroencephalography, sympathetic nerve measurement, ventral vagus nerve measurement, and dorsal vagus nerve measurement.

[0018] In the first aspect of the present invention, the sympathetic nerve measurement and the dorsal vagus nerve measurement may be measured by at least one measurement among heart rate measurement, heart rate fluctuation measurement, electromyography measurement, fingertip sweating measurement (psychogenic sweating measurement), fingertip (or nose) temperature measurement (peripheral skin temperature measurement), respiratory rate measurement, and respiratory method (abdominal or thoracic breathing) measurement.

[0019] In the first aspect of the present invention, the ventral vagus nerve measurement may be measured by measurement of respiratory variation of heart rate.

[0020] In the first aspect of the present invention, the service proposal device may further comprise: a user information storage unit that stores user information in a database form; a user data storage unit that stores usage history data when the user uses the service proposal system; and a user information management unit that records the user's usage history when the user uses the service proposal system and accepts user registration so that the usage history can be read out in the next use.

[0021] In the first aspect of the present invention, the service providing facility may be any one of a hotel / inn, a hot bath facility, a spa / treatment clinic, a nursing care / welfare facility, and a sports facility including e-sports.

[0022] A second aspect of the present invention is a service proposal method in a service proposal system that stores conversation pattern data, which is a machine learning model constructed using assumed patterns of conversations between service providers and users in a service provision facility; needs classification data, which is a machine learning model constructed using patterns of conversations with users tagged with potential needs and services; a reference correspondence table that lists one or more reference values ​​for each of the one or more services provided by the service provision facility and each of the one or more measurement results measured by each of the one or more measuring instruments; and service provision information that lists information about the one or more services provided by the service provision facility. The process includes: a speech conversion step that converts the user's voice data into text-formatted conversation data using speech recognition; a conversation analysis step that uses the text-formatted conversation data to select one or more candidate medical interview results using natural language processing and selects one or more measuring instruments corresponding to each of the one or more candidate medical interview results described in the service information provided; a conversation generation step that generates a conversation for the user based on conversation pattern data, conversation data, medical interview results, conversation data from the start of the conversation with the user up to the time the conversation data is received, conversations generated by the conversation generation unit, and judgment results by the result judgment unit; a medical interview result determination step that determines the medical interview result based on one or more candidate medical interview results selected in the conversation analysis step and measurement results from one or more measuring instruments; a service selection step that selects a service suitable for the user from one or more services based on one or more candidate medical interview results or the medical interview result; and a result judgment step that judges the signals transmitted from one or more measuring instruments using reference values ​​described in the reference correspondence table stored in the reference storage unit and transmits the judgment result to the conversation generation unit.The gist of it is that it is equipped with the following features.

[0023] A third aspect of the present invention is a service proposal system comprising: a service proposal device; a user conversation device that receives conversations initiated by a user; a user conversation output device that outputs conversations initiated to a user; one or more measuring instruments that measure the user's physical condition; a result output device that displays a service selected based on a conversation between the service proposal device and the user, or a conversation between the service proposal device and the user and measurement results from one or more measuring instruments; and an input device that receives input from a user. The system includes conversation pattern data, which is a machine learning model constructed using assumed patterns of conversations between service providers and users at a service provision facility; needs classification data, which is a machine learning model constructed using patterns of conversations with users tagged with potential needs and services; a reference correspondence table that lists one or more reference values ​​for one or more services provided by the service provision facility and for each of the one or more measurement results measured by each of the one or more measuring instruments; and a service proposal system that stores service provision information that lists information about one or more services provided by the service provision facility. The gist of the system is to provide a computer with the following functions: a speech conversion function that converts user voice data into text-based conversation data using speech recognition; a conversation analysis function that uses the text-based conversation data to process and classify the user's potential needs from needs classification data using natural language processing, and uses this to obtain a medical interview result; a conversation generation function that generates a conversation for the user based on conversation pattern data, conversation data, medical interview results, conversation data from the start of the conversation with the user up to the time the conversation data is received, conversations generated by the conversation generation unit, and judgment results from the result judgment unit; a medical interview result determination function that determines the medical interview result based on one or more candidate medical interview results selected by the conversation analysis function and measurement results from one or more measuring instruments; a service selection function that selects a service suitable for the user from one or more services based on one or more candidate medical interview results or the medical interview result; and a result judgment function that judges signals transmitted from one or more measuring instruments using reference values ​​listed in a reference correspondence table stored in a reference storage unit, and transmits the judgment result to the conversation generation unit. [Effects of the Invention]

[0024] According to the present invention, it is possible to provide a service proposal system, a service proposal method, and a service proposal program that make users' latent needs for services apparent, propose services that meet those needs, and increase the revenue of facilities that provide those services. [Brief explanation of the drawing]

[0025] [Figure 1] This is a schematic diagram showing an example of the overall configuration of a service proposal system according to the first embodiment of the present invention. [Figure 2] This is a block diagram showing an example of the configuration of the service proposal device according to this embodiment. [Figure 3] This table, according to this embodiment, shows the services proposed by the service provider facility for each of the interview results, and the contents of the measurements taken before and after the service proposal. [Figure 4] This table shows the combination of the results of the medical interview, vital signs measurement before the service proposal, the service content, and vital signs measurement after the service provision, according to this embodiment. [Figure 5] This table shows an example of a conversation between the service proposal system according to this embodiment and the user. [Figure 6] This table shows another example of the service proposal system according to this embodiment and the interaction between the system and the user. [Figure 7] This is a flowchart illustrating the operation of the service proposal system according to this embodiment. [Figure 8] This table shows yet another example of the service proposal system according to this embodiment and the interaction between the system and the user. [Figure 9] This table shows yet another example of the service proposal system according to this embodiment and the interaction between the system and the user. [Figure 10] This table shows a service proposal system according to a modified version of the first embodiment, and an example of a conversation with the user. [Figure 11]This table shows a modified version of the first embodiment of the service proposal system and another example of a conversation with the user. [Figure 12] This is a block diagram showing an example of the configuration of a service proposal device according to a second embodiment of the present invention. [Modes for carrying out the invention]

[0026] Next, embodiments of the present invention will be described with reference to the drawings. In the drawings of the embodiments, identical or similar parts are denoted by the same or similar reference numerals. However, the drawings are schematic.

[0027] Furthermore, the embodiments are illustrative of apparatus and methods for realizing the technical concept of the present invention, and the technical concept of the present invention does not limit the configuration, arrangement, layout, etc., of each component to those described below. The technical concept of the present invention can be modified in various ways within the technical scope defined by the claims described in the patent claims.

[0028] (First Embodiment) A service suggestion system according to the first embodiment of the present invention will be described below. Figure 1 shows an example of the configuration of the service suggestion system 10 according to this embodiment. The service suggestion system 10 shown in Figure 1 consists of a microphone 101, a speaker 102, a display 103, a service suggestion device 104, an input device 105, and a measuring instrument 106.

[0029] The service suggestion system 10 engages in natural conversation with the user, uses natural language processing to identify the user's latent needs, and proposes services that meet those needs. The service suggestion system 10 is installed in accommodation facilities such as hotels and hot spring facilities, and for users staying at the facility where the service suggestion system 10 is installed, a service that meets the user's needs is selected and proposed from among the services that the facility can provide.

[0030] The services proposed by the service proposal system according to the present invention are services aimed at fatigue recovery and health promotion, such as reducing fatigue, stress, physical and mental ailments, managing physical condition, and improving performance.

[0031] The service proposal device 104 is a variety of electronic computer (computational resource), such as a personal computer (PC), mainframe, workstation, or cloud computing system.

[0032] The microphone 101 is connected to the service proposal device 104 and is a device that acquires the voice spoken by the user as analog audio data, converts it into digital audio data, and transmits it to the service proposal device 104. In this embodiment, the microphone 101 is used as a device to receive conversations transmitted from the user to the service proposal device 104, but the user conversation input device that receives conversations transmitted from the user may be a means of receiving characters entered by the user rather than receiving the voice spoken by the user, for example, a character input means such as a touch panel or keyboard.

[0033] The speaker 102 is connected to the service proposal device 104 and outputs the conversation that the service proposal device 104 sends to the user as audio. In this embodiment, the speaker 102 is used as a means to output the conversation that is sent to the user, but as a user conversation output device that outputs the conversation that is sent to the user, for example, a display may be used and the conversation that is sent to the user may be displayed as text on the display.

[0034] The display 103 is connected to the service suggestion device 104 and is a result output device that displays the service selected based on the conversation between the service suggestion device 104 and the user, the instructions for using the measuring instrument 106, and the measurement results from the measuring instrument 106.

[0035] The input device 105 is connected to the service proposal device 104 and is a device that receives input from the user, such as a keyboard, touch panel, or mouse. In this embodiment, the input device 105 is assumed to be a keyboard.

[0036] The measuring device 106 is connected to the service proposal device 104 and is a vital sensor that measures the user's physical condition, and is a device that performs at least one of the following measurements: electroencephalogram (EEG), sympathetic nerve measurement, ventral vagal nerve measurement, and dorsal vagal nerve measurement.

[0037] The service proposal system 10 may further include a response expression device. The response expression device is a device that expresses emotions so that the service proposal system 104 has emotions, based on a conversation between the service proposal system 104 and the user. Specifically, for example, the response expression device may be a robot in the shape of a person or an animal, and the robot may perform actions such as changing facial expressions and adding gestures so as to communicate with the user. Instead of including a response expression device, for example, a person may be displayed on the display 103, and the person on the display 103 may perform actions such as changing facial expressions so as to converse with the user.

[0038] Figure 2 is a block diagram showing the configuration of the service proposal device 104. The service proposal device 104 is equipped with a CPU 201 for executing various calculations, storage 202 for storing processing programs, RAM 203 for storing data, etc., a storage unit 204 for storing various data and calculation results, and an I / O (input / output interface) 205, etc. The I / O 205 is an interface, buffer, etc. for communication (transmission and reception).

[0039] Furthermore, the block diagram in Figure 2 shows the functional units within the CPU 201. When each functional unit of the CPU 201 is implemented by software, the CPU 201 implements these functions by executing instructions from the program, which is the software that implements each function. Specifically, it includes a conversation generation unit 206, a conversation analysis unit 207, a service selection unit 208, a speech conversion unit 211, an output unit 213, a result determination unit 214, a medical interview result determination unit 216, and the like.

[0040] Furthermore, the block diagram in Figure 2 shows the configuration within the memory unit 204. In detail, it includes a service memory unit 209, a conversation pattern memory unit 210, a needs classification memory unit 212, a reference memory unit 215, and the like.

[0041] The voice conversion unit 211 converts the user's voice data transmitted from the microphone 101 into text-based conversation data using speech recognition.

[0042] At the start of a conversation with the user, the conversation generation unit 206 uses conversation pattern data stored in the conversation pattern storage unit 210 to generate a conversation for the user through natural language processing and outputs the conversation from the speaker 102. After the start of a conversation with the user, the conversation generation unit 206 uses at least one of the following to generate a conversation for the user through natural language processing and outputs the conversation from the speaker 102: conversation pattern data stored in the conversation pattern storage unit 210, conversation data converted into text format by the speech conversion unit 211, one or more candidate medical interview results and one or more measuring instruments selected by the conversation analysis unit 207, the medical interview result determined by the medical interview result determination unit 216, the service selected by the service selection unit 208 and one or more measuring instruments corresponding to the service, conversation data from the start of the conversation with the user up to the time conversation data is received and the conversation generated by the conversation generation unit 206, and a signal based on the judgment result by the result judgment unit 214. Instead of generating a conversation for the user and outputting it from the speaker 102, the conversation generation unit 206 may generate content to be displayed on the display for the user and output it to the display 103 via the output unit 213.

[0043] The conversation analysis unit 207 uses the conversation data converted into text format by the speech conversion unit 211 and, through natural language processing, selects one or more candidate questionnaire results from the needs classification data stored in the needs classification storage unit 212, which shows the correspondence between conversation patterns and needs, and between needs and services, thereby revealing and classifying the user's latent needs. Furthermore, the conversation analysis unit 207 selects one or more services and one or more measuring instruments corresponding to each of the one or more candidate questionnaire results, as described in the service information stored in the service storage unit 209 (described later).

[0044] The medical interview result determination unit 216 determines the medical interview result when the user's potential needs are made apparent and classified, based on one or more candidate medical interview results selected by the conversation analysis unit 207 and the measurement results from one or more measuring instruments corresponding to each of the one or more candidate medical interview results transmitted from the result judgment unit 214.

[0045] Based on one or more candidate medical interview results selected by the conversation analysis unit 207 and the medical interview result determination unit 216, the service selection unit 208 selects a service suitable for the user and one or more measuring instruments corresponding to the service from among the one or more services listed in the service information provided, which is stored in the service storage unit 209 (described later).

[0046] The service memory unit 209 stores service information containing details about one or more services that a service provider that has installed the service proposal system 10 can provide. The service information includes the type, name, and relationship to the classification of needs of one or more services that the service provider that has installed the service proposal system 10 can provide, as well as the location, time, and cost of the service provided at the service provider. Not all service providers that have installed the service proposal system 10 provide the same services; the services that can be provided differ from one service provider to another.

[0047] Furthermore, the service information also includes information about one or more measuring instruments used in determining the medical interview result from one or more candidates selected by the conversation analysis unit 207. The information about the measuring instruments includes the type of instrument, its name, its relationship to the classification of needs, and how to use it.

[0048] The conversation pattern storage unit 210 stores conversation pattern data, which is a machine learning model used by the conversation generation unit 206 when performing natural language processing. The conversation pattern data is a pre-trained model, and in this embodiment, it is constructed using expected patterns of conversations between service providers and users in a service provision facility. In this embodiment, a service provider in a service provision facility is a person who interacts with users staying at the service provision facility to make the users' potential needs apparent, classifies those needs, and provides services to the users according to the classified needs.

[0049] The needs classification storage unit 212 stores needs classification data, which is a machine learning model used by the conversation analysis unit 207 when performing natural language processing. The needs classification data is a pre-trained model, and in this embodiment, it is constructed using assumed patterns of conversations between service providers and users at a service provision facility, tagged with potential needs and services provided by the service provision facility.

[0050] The output unit 213 outputs the interview results obtained by the conversation analysis unit 207, the service selected by the service selection unit 208, the measurement results obtained by the measuring instrument 106, etc., to the display 103.

[0051] The result determination unit 214 evaluates the signal transmitted from the measuring instrument 106 and transmits the evaluation result to the conversation generation unit 206 and the medical interview result determination unit 216. When a measurement result is transmitted from the measuring instrument 106, the result determination unit 214, for example, compares the measurement result with a reference value and determines the trend of the measurement result based on the comparison between the measurement result and the reference value listed in the reference correspondence table stored in the reference storage unit 215.

[0052] The reference memory unit 215 stores a reference correspondence table that lists reference values ​​for the measurement results measured by the measuring instrument 106. The reference value is standard data corresponding to the type of measuring instrument 106 and the measurement location on the user's body. By comparing this with the measurement results measured by the measuring instrument 106, it is possible to understand the trends in the user's physical and mental state.

[0053] In this embodiment, potential needs refer to physical and / or mental care or activities that the user requires for fatigue recovery or health promotion, which the user is unaware of or, even if aware of, does not consider to be the primary purpose of visiting a service facility.

[0054] More specifically, potential needs are defined as any of the following: "peace of mind," "performance enhancement," "fatigue recovery," "autonomic nervous system balance adjustment," "improved blood and lymphatic circulation," or "enhanced recovery through good sleep." "Peace of mind" means relaxing and restoring mental safety and security. "Performance enhancement" means improving performance through stress care, biofeedback training, proper diet, rest, exercise, etc. "Fatigue recovery" means recovering from physical fatigue through proper diet, rest, exercise, etc. "Autonomic nervous system balance adjustment" means adjusting the balance of the autonomic nervous system through biofeedback training, proper rest, exercise, etc. "Improved blood and lymphatic circulation" means regulating blood and lymphatic flow through biofeedback training, exercise, manual therapy, etc. "Enhanced recovery through good sleep" means improving the quality of sleep and enhancing the body's ability to recover through biofeedback training, exercise, diet, manual therapy, etc.

[0055] Furthermore, in this embodiment, a service provision facility is a facility where the service proposal system 10 is installed and which can provide services to users staying at the service provision facility. Examples of service provision facilities include hotels and inns, hot spring facilities, spas and treatment centers, nursing and welfare facilities, and sports facilities including e-sports, but service provision facilities are not limited to these. When a service provision facility provides a service, measurements are taken in advance using the measuring instrument 106 to identify and classify the user's potential needs, and to quantify the degree of effectiveness of the service on those potential needs in order to enhance its effectiveness. After the service provision facility has provided the service, measurements are taken again using the measuring instrument 106 to confirm the effectiveness of the service on those potential needs.

[0056] In this embodiment, vital sensing by the measuring device 106 includes at least one of the following: electroencephalography (EEG), sympathetic nerve measurement, ventral vagal nerve measurement, and dorsal vagal nerve measurement. Sympathetic nerve measurement and dorsal vagal nerve measurement are measured by at least one of the following: heart rate measurement, heart rate variability measurement, electromyography (EMG), fingertip sweat measurement (psychogenic sweat measurement), fingertip (or nasal) temperature measurement (peripheral skin temperature measurement), respiratory rate measurement, and respiratory mode (abdominal or thoracic). Ventral vagal nerve measurement is measured by measuring respiratory variability of heart rate. Regarding ventral vagal nerve measurement, see Non-Patent Literature 1.

[0057] In this embodiment, the services provided by the service provider include at least one of the following: manual therapy, hot baths / saunas, meals, exercise, environmental / climate design, and biofeedback training. The biofeedback training includes at least one of the following: heart rate variability biofeedback, electromyography biofeedback, psychogenic sweating biofeedback, peripheral skin temperature biofeedback, and neurofeedback.

[0058] Manual therapy includes aesthetics, massage, and aromatherapy, with expected effects such as muscle relaxation and respiratory regulation. Hot baths and saunas are expected to have respiratory regulation and ventral vagal nerve activation. Diet includes supplements such as 5-deazaflavin compounds described in Patent Document 8, with expected effects such as changes in body temperature, secretion of neurotransmitters, and resulting mental stability through emotions and past recollections. Exercise includes yoga and Pilates, with expected effects such as muscle relaxation and respiratory regulation. Environmental and climate effects are expected to have mental stability through emotions and the recall of past emotional experiences. Biofeedback using heart rate variability measurement is expected to have respiratory regulation and ventral vagal nerve activation. Biofeedback using electromyography is expected to have muscle relaxation and respiratory regulation. Biofeedback using fingertip sweat measurement is expected to have sympathetic nerve tension relaxation. The expected effects of biofeedback using fingertip temperature measurement include parasympathetic nervous system activation. The expected effects of neurofeedback can be adjusted by the frequency band of brain waves to be enhanced or suppressed, the placement of electrodes to acquire brain waves, the connectivity between those sites, and the phase relationship. A wide range of effects are expected, including relaxation, sleep induction, and performance improvement.

[0059] Figure 3 shows the potential needs mentioned above, namely the results of the medical interview, the measurements taken with measuring device 106, and the services proposed by the service provider, as well as the expected changes resulting from each service.

[0060] For each questionnaire result, the service provider proposes one or more services. The user selects one or a combination of the proposed services. Depending on the questionnaire result and the corresponding service combination, vital signs are measured by the measuring device 106 before and after the service is provided. An example of a combination of questionnaire results, vital signs measurement before service provision, service content, and vital signs measurement after service provision is shown in Figure 4.

[0061] Next, the general flow of an example of a conversation between the service proposal system 10 according to this embodiment and an actual user will be described below with reference to Figures 5, 6, 8, and 9. Figures 5, 6, 8, and 9 are tables showing the conversation between the service proposal system 10 according to this embodiment and an actual user, as well as the status of the measuring instrument, display, and service, arranged in chronological order from top to bottom.

[0062] The following describes an example shown in Figure 5. The example shown in Figure 5 is an example in which a user suffering from severe shoulder stiffness uses the service suggestion system 10 according to this embodiment. The service suggestion system 10 is installed at service provision facility A, and the user is currently staying at service provision facility A.

[0063] First, the user makes an input from the input device 105 to initiate the provision of a service by the service proposal system 10. The service may be initiated by, for example, the user pressing a start button connected to the service proposal system 10, or by the user touching a touch panel. Alternatively, the service may be initiated by the service proposal system 10 being equipped with a camera, temperature sensor, etc., and detecting through the camera, temperature sensor, etc., that the user is positioned in front of the display of the service proposal system 10, or by the user inputting voice into the microphone 101.

[0064] The service suggestion device 104 speaks to the user via the speaker 102. Specifically, for example, the service suggestion device 104 might ask the user, "Is there anything that's been bothering you lately?"

[0065] If the user responds, "I have severe shoulder stiffness," the service suggestion device 104 asks the user, "Okay, let's measure the electromyography of your shoulder. I will now show you how to attach the electromyograph. Is that alright?" If the user responds with an affirmative answer such as, "Yes, please," the device displays instructions on how to attach the electromyograph on a display or similar. After the user has attached the electromyograph, the service suggestion device 104 tells the user, "It's connected successfully. Please try to relax as much as possible. We will now begin the measurement," and the measurement begins.

[0066] Once the measurement is complete, the measurement results are displayed on a screen, and at the same time, one or more services that match the user's needs are displayed on the screen, and the service suggestion device 104 tells the user, "The services displayed are what we recommend for you." If the services displayed on the screen are, for example, "manual therapy," "hot bath / sauna," "meals to relieve stiff shoulders," or "training to relax muscles," the service suggestion device 104 asks the user, "Which service would you like to receive?" If the user answers, "I would like to have meals to relieve stiff shoulders," the procedure, time, cost, etc. for receiving that service are displayed on the screen.

[0067] After the user has received the service, the service suggestion device 104 is informed that the service is complete. The service suggestion device 104 then asks the user, "Now, let's measure the electromyography of your shoulder again to confirm the effect. I will show you how to attach the electromyograph again. Is that alright?" If the user responds affirmatively, the device displays instructions on how to attach the electromyograph on the display or other screen. After the user attaches the electromyograph, the service suggestion device 104 tells the user, "It's connected successfully. Please try to relax as much as possible. We will now begin the measurement," and the measurement begins. The measurement results are displayed on the display or other screen along with the measurement results before the service, and the service suggestion device 104 tells the user, "As a result of the service, your electromyography values ​​are as follows."

[0068] The operation of the service proposal system 10 in the interaction between the service proposal system 10 and an actual user, as shown in Figure 5, is described below.

[0069] First, the service proposal system 10 receives input from the user to initiate a service proposal by the service proposal system 10. Methods for receiving input from the user to initiate service provision include receiving it via the input device 105, receiving it via a touch panel connected to the service proposal system 10, and receiving it via the speaker 102.

[0070] Next, the conversation generation unit 206 generates a conversation for the user, which is then output from the service proposal device 104 via the speaker 102. In the example in Figure 6, the user is asked, "Is there anything that's been bothering you lately?" When the microphone 101 receives the user's voice saying, "I have really bad shoulder pain," the voice conversion unit 211 converts the user's voice into text-based conversation data, which is then transmitted to the conversation analysis unit 207 and the conversation generation unit 206.

[0071] In the conversation analysis unit 207, based on the conversation data transmitted from the speech conversion unit 211, one or more candidates for the medical interview result are selected, and further, one or more measuring instruments corresponding to each of the one or more candidates for the medical interview result are selected from the service information stored in the service storage unit 209. In this case, since the user's response is "I have severe stiff shoulders," it is determined that one or more candidates for the medical interview result is "improvement of blood and lymph flow." An electromyograph is selected as one or more measuring instruments corresponding to each of the one or more candidates for the medical interview result, as described in the service information stored in the service storage unit 209.

[0072] The result that one or more candidates for the medical interview result is "blood and lymph flow" and that an electromyograph is selected as one or more measuring instruments is transmitted to the conversation generation unit 206. In the conversation generation unit 206, a conversation is generated for the user based on the conversation pattern data, conversation data, and one or more candidates for the medical interview result stored in the conversation pattern storage unit 210, and the service suggestion device 104 asks the user via the speaker 102, "Now, let's measure the electromyography of your shoulder. I will now show you how to attach the electromyograph. Is that alright?"

[0073] The user's voice saying "Yes, please" is converted into text-based conversation data by the voice conversion unit 211 and transmitted to the conversation analysis unit 207 and the conversation generation unit 206. The conversation analysis unit 207 determines that the user's "Yes, please" does not contain any of the user's potential needs. The conversation generation unit 206 generates display content for explaining how to attach the electromyograph to the user, based on the conversation pattern data, conversation data, interview results, and the conversation to the user, "Now, let's measure the electromyography of your shoulder. I will now show you how to attach the electromyograph. Is that alright?", and outputs it to the display 103 via the output unit 213.

[0074] After the user attaches the electromyograph, a completion signal indicating that the attachment is complete is transmitted from the electromyograph to the conversation generation unit 206 via the result determination unit 214. Based on the conversation data prior to the time the conversation data was received, the conversation generated by the conversation generation unit 206, and the completion signal, the conversation generation unit 206 generates a conversation for the user, and the service proposal device 104 informs the user, "It's connected successfully. Please try to relax as much as possible. We will now begin the measurement."

[0075] Once the measurement is complete, the measurement results are transmitted from the electromyograph to the result determination unit 214. The trend of the measurement results is determined based on a comparison of the measurement results with the reference values ​​listed in the reference correspondence table stored in the reference storage unit 215, and the measurement results and the determined trend are transmitted to the interview result determination unit 216.

[0076] The medical interview result determination unit 216 determines the medical interview result when the user's potential needs are made apparent and classified, based on one or more candidate medical interview results selected by the conversation analysis unit 207 and the measurement results from one or more measuring instruments corresponding to each of the one or more candidate medical interview results transmitted from the result judgment unit 214. In this case, the medical interview result is determined to be "improvement of blood and lymph flow."

[0077] Based on conversation pattern data, questionnaire results, conversation data prior to the reception of conversation data, conversations generated by the conversation generation unit 206, measurement results, and determined trends, the conversation generation unit 206 displays on the display 103 the type, name, location, time, cost, measurement results, and determined trends of one or more services that match the questionnaire results from among the services that service provision facility A can provide, which are stored in the service storage unit 209. The conversation generation unit 206 generates a conversation for the user and, via the speaker 102, tells the user, "The displayed service is what we recommend for you." Subsequently, the conversation generation unit 206 generates another conversation for the user and, via the speaker 102, asks the user, "Which service would you like to receive?"

[0078] In response to the user's statement, "I would like to eat a meal that will relieve my stiff shoulders," the voice conversion unit 211 and the conversation analysis unit 207 display the procedure, time, cost, etc., for receiving that service on the display 103.

[0079] When the service proposal system 10 receives input from the user indicating that the service has been completed after receiving the service, the conversation generation unit 206 generates a conversation for the user based on the conversation data prior to the time the interview results and conversation data were received, and the conversation generated by the conversation generation unit 206. The conversation is then transmitted to the user via speaker 102, asking, "Now, let's measure the electromyography of your shoulder again to confirm the effect. I will show you how to attach the electromyograph again. Is that alright?" If the user responds with an affirmative answer, the procedure for starting measurement with the electromyograph is repeated, and the measurement begins. Once the measurement is complete, the result judgment unit 214 judges the trend of the measurement results again, and the measurement results and the judged trend are transmitted to the conversation generation unit 206. The conversation generation unit 206 generates a conversation for the user, and the measurement results and the trend of the measurement results are displayed on display 103 along with the measurement results and the trend of the measurement results before receiving the service. The conversation is then transmitted to the user via speaker 102, saying, "As a result of the service, the electromyography values ​​are as follows," and the operation of the service proposal system 10 ends.

[0080] The following describes an example shown in Figure 6. The example shown in Figure 6 is an example in which a user who has trouble sleeping at night uses the service suggestion system 10 according to this embodiment. The service suggestion system 10 is installed in service provision facility B, and the user is currently staying at service provision facility B. In the case shown in Figure 5, where the user tends to have severe stiff shoulders, the response to the service suggestion device 104 asking the user "Is there anything that has been bothering you lately?" is "I have severe stiff shoulders," so the result of the questionnaire is "improvement of blood and lymph flow," and a service corresponding to the questionnaire result is provided. In the example shown in Figure 6, the response to the service suggestion device 104 asking the user "Is there anything that has been bothering you lately?" is "I can't sleep well at night," so the result of the questionnaire is "improvement of recovery power through good sleep," and the services provided corresponding to the questionnaire result are "exercise, yoga" and "neurofeedback to increase sleep induction brainwaves," and brainwave measurements are taken before and after the service.

[0081] Next, the operation of the service proposal system according to this embodiment will be explained with reference to Figure 7. Figure 7 is a flowchart for explaining the operation of the service proposal system 10, and shows the operation of the service proposal system 10 in the example shown in Figure 5.

[0082] In step S701, the service proposal system 10 receives input from the user to initiate the provision of a service by the service proposal system 10.

[0083] In step S702, the conversation generation unit 206 generates a conversation for the user and outputs "Is there anything that's been bothering you lately?" via the speaker 102.

[0084] In step S703, the microphone 101 receives the user's voice saying, "My shoulders are really stiff," and transmits it to the voice conversion unit 211. The voice conversion unit 211 converts it into text-based conversation data and transmits it to the conversation analysis unit 207 and the conversation generation unit 206.

[0085] In step S704, the conversation analysis unit 207 selects one or more candidate medical interview results based on the conversation data, and further selects one or more measuring instruments.

[0086] In step S705, the conversation generation unit 206 generates a conversation for the user based on the conversation pattern data, conversation data, and the medical interview results, and outputs the following voice message from the speaker 102: "Now, let's measure the electromyography of your shoulder. I will now show you how to attach the electromyograph. Is that alright?"

[0087] In step S706, the microphone 101 receives the user's voice saying "Yes, please," and transmits it to the voice conversion unit 211, which converts it into text-based conversation data and transmits it to the conversation analysis unit 207 and the conversation generation unit 206.

[0088] In step S707, the conversation analysis unit 207 determines that the user's response, "Yes, please," does not contain the user's potential needs.

[0089] In step S708, the conversation generation unit 206 generates display content for explaining how to attach the electromyograph to the user, based on the conversation pattern data, conversation data, interview results, and the conversation to the user, "Now, let's measure the electromyography of your shoulder. I will now show you how to attach the electromyograph. Is that alright?", and outputs it to the display 103 via the output unit 213.

[0090] In step S709, the result determination unit 214 receives a completion signal from the electromyograph indicating that the installation is complete and transmits it to the conversation generation unit 206.

[0091] In step S710, the conversation generation unit 206 generates a conversation for the user based on the conversation data from before the time the conversation data was received, the conversation generated by the conversation generation unit 206, and the completion signal, and outputs the following voice message from the speaker 102: "It's connected successfully. Please try to relax as much as possible. Now we will begin the measurement."

[0092] In step S711, the measurement is initiated.

[0093] After the measurement is completed, in step S712, the result determination unit 214 receives the measurement results from the electromyograph, determines the trend of the measurement results based on a comparison of the measurement results with the reference values ​​listed in the reference correspondence table stored in the reference storage unit 215, and transmits the measurement results and the determined trend to the interview result determination unit 216.

[0094] In step S713, the medical interview result determination unit 216 determines the medical interview result.

[0095] In step S714, the conversation generation unit 206, based on conversation pattern data, medical interview results, conversation data prior to the reception of conversation data and conversations generated by the conversation generation unit 206, measurement results and determined trends, displays on the display 103 the type, name, location, time, cost, measurement results, and determined trends of one or more services that match the medical interview results from among the services that service provision facility A can provide, which are stored in the service storage unit 209. It generates a conversation for the user and outputs the following voice lines from the speaker 102: "The displayed service is what we recommend for you." "Which service would you like to receive?"

[0096] In step S715, the microphone 101 receives the user's voice saying, "I want to eat something that will relieve my stiff shoulders," and transmits it to the voice conversion unit 211. The voice conversion unit 211 converts it into text-based conversation data and transmits it to the conversation analysis unit 207 and the conversation generation unit 206.

[0097] In step S716, the conversation generation unit 206 generates display content for the display that shows the user the procedure, time, cost, etc. for receiving the service, based on the conversation pattern data, conversation data, and medical interview results, and outputs it to the display 103 via the output unit 213.

[0098] In step S717, the service proposal system 10 receives input from the user indicating that the service has been received and then completed.

[0099] In step S718, the conversation generation unit 206 generates a conversation for the user based on the medical interview results, conversation data from before the time the conversation data was received, and the conversation generated by the conversation generation unit 206, and outputs the following voice message from the speaker 102: "Now, let's measure the electromyography of your shoulder again to confirm the effect. I will show you how to attach the electromyograph again. Is that alright?"

[0100] In step S719, the microphone 101 receives an audio message indicating the user's affirmative response and transmits it to the voice conversion unit 211, which converts it into text-based conversation data and transmits it to the conversation analysis unit 207 and the conversation generation unit 206.

[0101] In step S720, the conversation generation unit 206 generates display content explaining to the user how to attach the electromyograph and outputs it to the display 103 via the output unit 213.

[0102] In step S721, the result determination unit 214 receives a completion signal from the electromyograph indicating that the installation is complete and transmits it to the conversation generation unit 206.

[0103] In step S722, the conversation generation unit 206 generates a conversation for the user and outputs the following audio from the speaker 102: "It's connected successfully. Please try to relax as much as possible. Now we will begin the measurement."

[0104] In step S723, the measurement is initiated.

[0105] After the measurement is completed, in step S724, the result determination unit 214 receives the measurement results from the electromyograph, determines the trend of the measurement results based on a comparison of the measurement results with the reference values ​​listed in the reference correspondence table stored in the reference storage unit 215, and transmits the measurement results and the determined trend to the conversation generation unit 206.

[0106] In step S725, the conversation generation unit 206 displays the measurement results and the trend of the measurement results together with the trend of the measurement results before receiving the service on the display 103, generates a conversation for the user, and tells the user via the speaker 102, "The electromyography values ​​have become as follows after the service."

[0107] The following describes an example shown in Figure 8. The example shown in Figure 8 is an example in which a user who says "I can't relax" uses the service suggestion system 10 according to this embodiment. The service suggestion system 10 is installed in service provision facility C, and the user is currently staying at service provision facility C.

[0108] In the example shown in Figure 5, the service suggestion device 104 asks the user, "Is there anything that's been bothering you lately?", and the user responds, "I have severe shoulder stiffness." The resulting questionnaire result is "improvement of blood and lymph flow," and the only measurement corresponding to the service was "electromyography." The same applies to the example shown in Figure 6.

[0109] In contrast, in the example shown in Figure 8, the service suggestion device 104 asks the user, "Is there anything that's been bothering you lately?", and the user responds, "I get tired very easily." The candidate results of the consultation are either "fatigue recovery" or "autonomic nervous system balance adjustment," and the measurements corresponding to the service are "electroencephalogram measurement" and "heart rate / heart rate variability measurement (heart rate measurement)."

[0110] In the example shown in Figure 8, the user has selected "EEG measurement" from the options of "Heart rate and heart rate variability measurement (heart rate measurement)". The measurement results and the questionnaire results indicate "fatigue recovery" and "autonomic nervous system balance adjustment". As a service, the user can choose either "EEG training for fatigue recovery (neurofeedback for fatigue recovery)" or "EEG training to regulate the autonomic nervous system (neurofeedback for autonomic nervous system balance adjustment)".

[0111] The example shown in Figure 9 is explained below. In the example shown in Figure 9, the service suggestion device 104 asks the user, "Is there anything that's been bothering you lately?", and the user responds, "I can't seem to find peace of mind." Based on this, the candidate results of the medical interview are "peace of mind" and "autonomic nervous system balance adjustment." The measurements corresponding to the service are "electroencephalogram (EEG) measurement," "heart rate measurement," "fingertip sweat measurement," and "fingertip temperature measurement." Furthermore, the user selects "heart rate measurement," and as a result of the measurement, the medical interview result becomes either "fatigue recovery" or "autonomic nervous system balance adjustment." The user can then choose between "heart rate training for peace of mind (biofeedback using heart rate variability measurement)" or "heart rate training to regulate the autonomic nervous system (biofeedback using heart rate variability measurement)."

[0112] (Modified version of the first embodiment) Examples shown in Figures 10 and 11 are described below. In the examples shown in Figures 5, 6, 8, and 9, the service suggestion device 104 selects candidate medical interview results based on the conversation between the service suggestion device 104 and the user, and then, based on the measurement results, a medical interview result is selected from the selected candidate medical interview results, and a service is suggested based on the medical interview result. In this modified example, the service suggestion device 104 selects candidate medical interview results based on the conversation between the service suggestion device 104 and the user, and then proposes one or more services based on the candidate medical interview results. The user can select a desired service from the one or more services proposed by the service suggestion device 104 before performing measurements with the measuring instrument.

[0113] The example shown in Figure 10 is explained below. In the example shown in Figure 10, the service suggestion device 104 asks the user, "Is there anything that's been bothering you lately?", and the user responds, "I can't find peace of mind." Based on this, the candidate results of the medical interview are "peace of mind" and "autonomic nervous system balance adjustment." The service suggestion device 104 then proposes the following services corresponding to the candidate results: "training using electroencephalography (neurofeedback)," "training using heart rate (biofeedback by measuring heart rate variability)," "training using fingertip sweating (biofeedback by measuring fingertip sweating)," "training using fingertip temperature (biofeedback by measuring fingertip temperature)," and "environmental / climate adjustment." The user selects "training using heart rate."

[0114] In this modified example, the services proposed by the service proposal device 104 are services corresponding to candidate medical interview results selected based on the conversation between the service proposal device 104 and the user. In this modified example, the service proposal device 104 proposes the same or more services as those proposed by the service proposal device 104 in the example shown in the first embodiment. Therefore, the user can select a desired service from the same or more services as those proposed by the service proposal device 104 in the example shown in the first embodiment.

[0115] As shown in the examples in Figures 5, 6, 8, and 9, the service proposal device 104 may be configured to allow the user to choose whether to select candidate medical interview results based on the conversation between the service proposal device 104 and the user, and then, based on the measurement results, select a medical interview result from among the selected candidate results and propose a service based on the medical interview result, or, as in this modified example, propose a service based on candidate medical interview results. For example, in step S701 shown in the flowchart in Figure 7, the service proposal system 10 may receive input from the user to initiate the provision of a service by the service proposal system 10, along with input to select whether the service proposal device 104 proposes a service based on medical interview results or proposes a service based on candidate medical interview results.

[0116] The example shown in Figure 11 is described below. Similar to the example shown in Figure 10, the service proposed by the service proposal device 104 in Figure 11 corresponds to a candidate of the medical interview result selected based on the conversation between the service proposal device 104 and the user. In the example shown in Figure 11, the service proposal device 104 asks the user, "Is there anything that's been bothering you lately?", to which the user responds, "I can't concentrate." Based on this response, the candidate of the medical interview result is "performance improvement," and the service proposal device 104 proposes services corresponding to the candidate of the medical interview result: "EEG training for performance improvement (neurofeedback)," "exercise, yoga," "dietary suggestions for performance improvement (diet)," and "environmental and climate design for performance improvement." In response, the user selects "EEG training."

[0117] (Second embodiment) Figure 12 is a block diagram showing the configuration of the service proposal device 1201 of the service proposal system 1200 according to the second embodiment. Compared with the service proposal device 104 according to the first embodiment shown in Figure 2, the service proposal device 1201 shown in Figure 12 further includes the user information storage unit 1202, user data storage unit 1203, and user information management unit 1204 shown in Figure 2.

[0118] The user information storage unit 1202 stores user information in a database. User information includes, for example, the user's name, age, contact information, gender, height, weight, user ID, and password. The user's user ID and password can be used to retrieve usage history data from the user data storage unit 1203 when the user repeatedly uses the service proposal system 1200 according to this embodiment. The user's age, gender, height, weight, etc., can be used by the result determination unit 214 when selecting reference values ​​when comparing the measurement results from the measuring instrument 106 with reference values ​​listed in the reference correspondence table stored in the reference storage unit 215.

[0119] The user data storage unit 1203 stores usage history data when a user uses the service suggestion system 1200. The usage history data includes the date and time of use by the user, the results of the medical questionnaire, the measurement results, the services used, etc.

[0120] The User Information Management Unit 1204 accepts user registration so that the user's usage history can be recorded and retrieved the next time the user uses the Service Proposal System 1200. The User Information Management Unit 1204 accepts user information input from the user and issues a user ID and password. By being authenticated by the User Information Management Unit 1204 using the user ID and password, the user can use the user usage history data stored in the User Data Storage Unit 1203 when using the Service Proposal System 1200.

[0121] The operation of the service suggestion system 1200 is substantially the same as that of the service suggestion system 10 according to the first embodiment. However, for example, when the service suggestion system 1200 starts providing a service, it can prompt the user to enter a user ID and password, and retrieve the user's past usage history of the service suggestion system 1200. Also, for example, it can prompt the user to use a service they have used in the past from among the services that the service provider facility can offer, which match the results of the medical interview.

[0122] According to the service suggestion system 1200 of this embodiment, users can register and repeatedly use the service suggestion system 1200 to refer to their history of medical interview results, measurement results, etc. This increases users' awareness of their own physical and mental health, encourages regular use of the service suggestion system 1200, and therefore improves the utilization rate and repeat rate of service providers that have installed the service suggestion system 1200.

[0123] As described above, the service provision system according to the present invention is installed in service provision facilities such as hotels and other lodging facilities, and hot spring facilities, where guests can receive services aimed at fatigue recovery and health promotion while staying at the service provision facility. Users can receive such services while staying at the service provision facility.

[0124] As described above, the service proposal system according to the present invention can make users' latent needs regarding fatigue recovery and health promotion apparent through natural conversation with the user, and connect this to the provision of services by service providers. Making users' latent needs regarding fatigue recovery and health promotion apparent through natural conversation with the user is usually achieved, for example, by setting up a counter where counseling can be conducted in a corner of the service provider's facility, and having the counselor and user converse directly while vital signs are being sensed, etc. However, it is not possible to set up a counter where users can converse with a counselor in all service provider's facilities. The service provision system according to this embodiment can be installed in a small space and is therefore possible to install it in many service provider's facilities. Furthermore, since the service provision system according to this embodiment is available at any time, users can use it at their convenience.

[0125] Thus, with the service provision system according to this embodiment, service provision facilities can increase their operating rate, average spending per customer due to the use of services, and repeat customer rate due to an increase in the number of times users use the service, and therefore increase the revenue of the service provision facilities.

[0126] In the first and second embodiments, we described cases where the service proposal content is changed based on vital sensing. However, it is also easy to imagine a form in which the user's emotions (pleasure or displeasure, level of alertness, etc.) are inferred by analyzing vital sensing data, and the service proposal content is changed based on that.

[0127] In the first and second embodiments, the service provider is described as a human being; however, depending on the nature of the service provided, it is easily conceivable that this could be replaced in the future by an AI-equipped robot or the like.

[0128] In the first and second embodiments, the description assumes that the service proposal device is located locally; however, at least some of these functions may be implemented on the cloud.

[0129] As stated above, the present invention naturally includes various embodiments and the like that are not described herein. Therefore, the technical scope of the present invention is determined solely by the inventive features relating to the claims that are reasonable based on the above description. [Explanation of Symbols]

[0130] 10,1200 Service Delivery Systems 101 Microphone 102 speakers 103 displays 104, 1201 Service provision equipment 105 Input device 106 Measuring instruments 201 CPU 202 ROM 203 RAM 204 Storage section 205 I / O (Input / Output Interface) 206 Conversation generation unit 207 Conversation Analysis Department 208 Service Selection Section 209 Service Storage Unit 210 Conversation Pattern Memory Unit 211 Voice Conversion Unit 212 Needs Classification Memory Unit 213 Output section 214 Result judgment section 215 Reference storage section 216 Interview result determination department 1202 User Information Storage Unit 1203 User data storage unit 1204 User Information Management Department

Claims

1. Service proposal device, A user conversation input device that receives conversations initiated by the user, A user conversation output device that outputs a conversation directed to the aforementioned user, One or more measuring devices for measuring the physical condition of the user, A result output device that displays a service selected based on the conversation between the service suggestion device and the user, or the conversation between the service suggestion device and the user and the measurement results from one or more measuring instruments, The service proposal device is equipped with, A speech conversion unit converts the user's voice data transmitted from the user conversation input device into text-formatted conversation data using speech recognition. A conversation pattern storage unit that stores conversation pattern data, which is a machine learning model constructed using expected patterns of conversations between service providers and users at a service provision facility, A needs classification storage unit stores needs classification data, which is a machine learning model constructed using patterns of conversations with the user, tagging potential needs with the services. A conversation analysis unit, using the aforementioned text-formatted conversation data, performs natural language processing to select one or more candidate questionnaire results from the needs classification data stored in the needs classification storage unit, which represent the user's potential needs when they are made apparent and classified, and selects one or more measuring instruments corresponding to each of the one or more candidate questionnaire results described in the service information provided. A conversation generation unit generates a conversation for the user based on at least one of the following: the conversation pattern data, the conversation data, the medical interview results, the conversation data from the start of the conversation with the user up to the time the conversation data is received, the conversation generated by the conversation generation unit, and the judgment result by the result judgment unit. A conversation analysis unit selects one or more candidates for the medical interview result, and a medical interview result determination unit determines the medical interview result based on the measurement results from the one or more measuring instruments. A service storage unit that stores the service information, which contains information about one or more services provided by the service facility, A service selection unit that selects a service suitable for the user from one or more candidates based on the results of the medical interview, or from the one or more services based on the results of the medical interview, The result determination unit determines the signals transmitted from the one or more measuring instruments using the reference values ​​listed in the reference correspondence table stored in the reference storage unit, and transmits the determination result to the conversation generation unit. The reference storage unit stores a reference correspondence table which contains reference values ​​for the measurement results measured by the measuring instrument. A service proposal system characterized by comprising the following features.

2. The service proposal system according to claim 1, further comprising a response expression device that expresses emotions so that the service proposal device has emotions based on the conversation with the user.

3. The service proposal system according to claim 1, characterized in that the one or more services include at least one of the following: manual therapy, hot baths / saunas, meals, exercise, environmental / climate design, and biofeedback training.

4. The service proposal system according to claim 3, characterized in that the biofeedback training includes at least one of the following: heart rate variability biofeedback, electromyography biofeedback, psychogenic sweating biofeedback, peripheral skin temperature biofeedback, and neurofeedback.

5. The service proposal system according to claim 1, characterized in that the aforementioned potential needs are classified into one of the following categories: "peace of mind," "performance enhancement," "fatigue recovery," "autonomic nervous system balance adjustment," "blood and lymph flow," or "recovery through good sleep."

6. The service proposal system according to claim 1, characterized in that the one or more measuring instruments measure at least one of the following: electroencephalogram measurement, sympathetic nerve measurement, ventral vagal nerve measurement, and dorsal vagal nerve measurement.

7. The service proposal system according to claim 6, characterized in that the sympathetic nerve measurement and the dorsal vagus nerve measurement are measured by at least one of the following measurements: heart rate measurement, heart rate variability measurement, electromyography measurement, fingertip sweat measurement for psychogenic sweating, fingertip or nasal temperature measurement for peripheral skin temperature, respiratory rate measurement, and respiratory mode measurement for abdominal or thoracic breathing.

8. The service proposal system according to claim 6, characterized in that the ventral vagal nerve measurement is performed by measuring respiratory variability of heart rate.

9. The service proposal device is A user information storage unit that stores the user's information in a database, A user data storage unit that stores usage history data when the user uses the service proposal system, The service proposal system according to claim 1, further comprising a user information management unit that records the user's usage history when the user uses the service proposal system and accepts the registration of the user so that it can be read the next time the user uses the system.

10. The service proposal system according to claim 1, characterized in that the service provider is one of the following: a hotel or inn, a hot spring facility, a spa or treatment center, a nursing care or welfare facility, or a sports facility including e-sports.

11. The system comprises a service suggestion device, a user conversation device that receives conversations initiated by a user, a user conversation output device that outputs conversations to be sent to the user, an input device that receives input from the user, one or more measuring instruments that measure the user's physical condition, and a result output device that displays a service selected based on the conversation between the service suggestion device and the user, or the conversation between the service suggestion device and the user and the measurement results from the one or more measuring instruments. A service proposal system that stores conversation pattern data, which is a machine learning model constructed using assumed patterns of conversations between service providers and users at a service provision facility; needs classification data, which is a machine learning model constructed using patterns of conversations with users, tagged with potential needs and the services; a reference correspondence table that lists one or more reference values ​​for one or more services provided by the service provision facility and one or more measurement results measured by each of the one or more measuring instruments; and service provision information that describes information about one or more services provided by the service provision facility. A speech conversion step that converts the user's voice data into text-formatted conversation data using speech recognition, A conversation analysis step in which, using the aforementioned text-formatted conversation data, natural language processing is used to select one or more candidate questionnaire results when the user's potential needs are made apparent and classified from the needs classification data, and one or more measuring instruments corresponding to each of the one or more candidate questionnaire results described in the provided service information, A conversation generation step that generates a conversation for the user based on at least one of the following: the conversation pattern data, the conversation data, the medical interview results, the conversation data from the start of the conversation with the user up to the time the conversation data is received, the conversation generated in the conversation generation step, and the judgment result in the result judgment step. A step to determine the medical interview result, in which one or more candidates for the medical interview result selected in the conversation analysis step and the measurement results from the one or more measuring instruments are used to determine the medical interview result, A service selection step in which one or more candidates from the above medical questionnaire results, or a service suitable for the user from among the above one or more services based on the above medical questionnaire results, The result determination step involves determining the signals transmitted from the one or more measuring instruments using reference values ​​listed in a reference correspondence table stored in a reference storage unit, A service proposal method characterized by comprising the following features.

12. The system comprises a service suggestion device, a user conversation device that receives conversations initiated by a user, a user conversation output device that outputs conversations to be sent to the user, one or more measuring instruments that measure the user's physical condition, a result output device that displays a service selected based on the conversation between the service suggestion device and the user, or the conversation between the service suggestion device and the user and the measurement results from the one or more measuring instruments, and an input device that receives input from the user. In a service proposal system that stores conversation pattern data, which is a machine learning model constructed using assumed patterns of conversations between service providers and users at a service provision facility; needs classification data, which is a machine learning model constructed using patterns of conversations with users, tagged with potential needs and the services; a reference correspondence table that lists one or more reference values ​​for one or more services provided by the service provision facility and one or more measurement results measured by each of the one or more measuring instruments; and service provision information that describes information about one or more services provided by the service provision facility, the computer stores: The aforementioned voice data of the user is converted into text-formatted conversation data using speech recognition, and A conversation analysis function that, using the aforementioned text-formatted conversation data, uses natural language processing to select one or more candidate questionnaire results when the user's potential needs are made apparent and classified from the needs classification data, and selects one or more measuring instruments corresponding to each of the one or more candidate questionnaire results described in the provided service information. A conversation generation function that generates a conversation for the user based on at least one of the following: the conversation pattern data, the conversation data, the medical interview results, the conversation data from the start of the conversation with the user up to the time the conversation data is received, the conversation generated by the conversation generation function, and the judgment result by the result judgment function. A medical interview result determination function that determines the medical interview result based on one or more candidates for the medical interview result selected by the conversation analysis function and the measurement results from the one or more measuring devices, A service selection function that selects a service suitable for the user from one or more candidates based on the results of the medical questionnaire, or from the one or more services based on the results of the medical questionnaire, The result determination function determines the signals transmitted from the one or more measuring instruments using reference values ​​listed in the reference correspondence table stored in the reference storage unit, A service proposal program to realize the provision of such features.

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