Granted Patent B2

US 12,619,670 · App. 18/548,930 · Granted May 5, 2026

Inventor: Mao Katsuhara (Tokyo, JP)

Assignee: SONY GROUP CORPORATION

G06F16/9535A61B5/165

Abstract

Claims (181)

1 . A content recommendation system, comprising:

a processor configured to:

acquire first chronological vital data that is vital data of a user, wherein the first chronological vital data of the user is continuously and chronologically sensed by a vital sensor;

generate first chronological vital-feature-amount data based on the first chronological vital data;

generate, based on the first chronological vital-feature-amount data, a first estimated emotion value, wherein the first estimated emotion value is a first estimated value of a first emotion of the user;

acquire a target emotion value based on a user input through a user interface terminal apparatus, wherein the target emotion value indicates an emotion that is a target of the user;

select, from a content library, a plurality of pieces of content, wherein the plurality of pieces of content is selected to reach the target emotion value from the first estimated emotion value;

generate context information regarding the user;

narrow down the selected plurality of pieces of content to at least one piece of content based on the context information; and

recommend the at least one piece of content to the user interface terminal apparatus.

2 . The content recommendation system according to claim 1 , wherein the processor is further configured to acquire the first chronological vital data and generate the first estimated emotion value before the acquisition of the target emotion value.

3 . The content recommendation system according to claim 1 , wherein the processor is further configured to:

obtain newest vital-feature-amount data based on a change in previous vital-feature-amount data of the first chronological vital-feature-amount data; and

generate a second estimated emotion value based on the newest vital-feature-amount data.

4 . The content recommendation system according to claim 1 , wherein

the processor is further configured to store the at least one piece of content in the content library,

the at least one piece of content is stored such that a corresponding estimated emotion value of a plurality of estimated emotion values reaches a respective target emotion value of a plurality of target emotion values,

the corresponding estimated emotion value reaches the respective target emotion value based on a respective piece of content of the at least one piece of content,

the plurality of target emotion values includes the target emotion value, and

the plurality of estimated emotion values includes the first estimated emotion value.

5 . The content recommendation system according to claim 4 , wherein

the content library is a two-dimensional matrix that includes the plurality of estimated emotion values and the plurality of target emotion values,

the respective piece of content is registered in a portion of the content library, and

the portion of the content library corresponds to a point of intersection of a first line corresponding to the target emotion value and a second line corresponding to the first estimated emotion value.

6 . The content recommendation system according to claim 1 , wherein the processor is further configured to:

store the plurality of pieces of content in the content library, wherein

the plurality of pieces of content is stored such that a corresponding estimated emotion value of a plurality of estimated emotion values reaches a respective target emotion value of a plurality of target emotion values,

the corresponding estimated emotion value reaches the respective target emotion value based on a respective piece of content of the plurality of pieces of content, and

at least one piece of the context information of a plurality of pieces of the context information is associated with a respective piece of content of the plurality of pieces of content; and

narrow down the selected plurality of pieces of content to the at least one piece of content based on the association of the at least one piece of the context information to the respective piece of content.

7 . The content recommendation system according to claim 1 , wherein the processor is further configured to:

obtain second chronological vital-feature-amount data based on the recommended at least one piece of content;

generate a second estimated emotion value based on the second chronological vital-feature-amount data, wherein the second estimated emotion value is a second estimated value of a second emotion of the user; and

update the content library for the user based on registration of the recommended at least one piece of content in the content library, wherein

the at least one piece of content is registered such that the first estimated emotion value reaches the second estimated emotion value, and

the first estimated emotion value reaches the second estimated emotion value based on the at least one piece of content.

8 . The content recommendation system according to claim 1 , wherein the processor is further configured to:

obtain second chronological vital-feature-amount data based on the recommended at least one piece of content;

generate a second estimated emotion value based on the second chronological vital-feature-amount data, wherein the second estimated emotion value is a second estimated value of a second emotion of the user;

select, from the content library, content to reach the target emotion value from the second estimated emotion value, wherein the plurality of pieces of content one of includes or excludes the content; and

recommend the selected content to the user interface terminal apparatus.

9 . The content recommendation system according to claim 1 , wherein the processor is further configured to:

generate a plurality of estimated emotion values in chronological order, wherein the plurality of estimated emotion values includes the first estimated emotion value; and

select, from the content library, content to reach the target emotion value from a newest estimated emotion value among the plurality of estimated emotion values, wherein

the newest estimated emotion value is reached from a previous estimated emotion value of the plurality of estimated emotion values, and

the plurality of pieces of content includes the content.

10 . The content recommendation system according to claim 9 , wherein

the processor is further configured to store the at least one piece of content in the content library,

the at least one piece of content is stored such that the newest estimated emotion value reaches the target emotion value, and

the newest estimated emotion value reaches the target emotion value based on the at least one piece of content.

11 . The content recommendation system according to claim 9 , wherein

the processor is further configured to store the at least one piece of content of the plurality of pieces of content in the content library,

the at least one piece of content is stored such that:

each of a plurality of previous estimated emotion values reaches a corresponding newest estimated emotion value of a plurality of newest estimated emotion values, wherein

the each of the plurality of previous estimated emotion values reaches the corresponding newest estimated emotion value based on the at least one piece of content, and

the plurality of estimated emotion values includes the plurality of previous estimated emotion values and the plurality of newest estimated emotion values; and

the corresponding newest estimated emotion value reaches a respective target emotion value of a plurality of target emotion values, wherein the plurality of target emotion values includes the target emotion value.

12 . The content recommendation system according to claim 11 , wherein

the content library is a three-dimensional matrix that includes the plurality of previous estimated emotion values, the plurality of newest estimated emotion values, and the plurality of target emotion values,

the at least one piece of content is registered in a portion of the content library, and

the portion of the content library is corresponding to a point of intersection of a first line corresponding to a previous estimated emotion value of the plurality of previous estimated emotion values a second line corresponding to the corresponding newest estimated emotion value, and a third line corresponding to the respective target emotion value.

13 . The content recommendation system according to claim 1 , wherein the processor is further configured to:

calculate a probability of the user having the first emotion in a specific emotional state; and

set the probability as the first estimated emotion value.

14 . The content recommendation system according to claim 13 , wherein the probability corresponds to a value that quantifies a state of the user having the emotion in the specific emotional state.

15 . The content recommendation system according to claim 13 , wherein

the probability includes a first probability and a second probability, and

the processor is further configured to:

calculate the first probability of the user having a second emotion in a first specific emotional state;

calculate the second probability of the user having a third emotion in a second specific emotional state; and

generate the first estimated emotion value based on the first probability and the second probability.

16 . The content recommendation system according to claim 15 , wherein

the first specific emotional state is an arousal state,

the first probability is a probability of the user having the second emotion in the arousal state,

the second specific emotional state is a pleasure state of valance, and

the second probability is a probability of the user having the third emotion in the pleasure state.

17 . The content recommendation system according to claim 13 , wherein

the user interface terminal apparatus displays a first target-input user interface,

the first target-input user interface is a Graphical User Interface (GUI) displayed for the user to input the target emotion value,

the first target-input user interface includes, in a single-axis direction, a first plurality of different areas,

each of the first plurality of different areas corresponds to a respective probability of each of a first probability in the specific emotional state and a second probability in the specific emotional state,

one of the first plurality of different areas is selectable by the user to input the respective probability of a corresponding area of the first plurality of different areas, and

the respective probability is input to the user interface terminal apparatus as the target emotion value.

18 . The content recommendation system according to claim 17 , wherein

the user interface terminal apparatus displays a second target-input user interface,

the second target-input user interface displays a second plurality of different areas in a matrix in a biaxial direction,

a first area of the second plurality of different areas corresponds to a combination of a third probability and a fourth probability,

a second area of the second plurality of different areas corresponds to a combination of the third probability and a fifth probability,

a third area of the second plurality of different areas corresponds to a combination of a sixth probability and the fifth probability,

a fourth area of the second plurality of different areas corresponds to a combination of the sixth probability and the fourth probability,

the third probability and the sixth probability are probabilities of the user having a second emotion in a first specific emotional state,

the fourth probability and the fifth probability are probabilities of the user having a third emotion in a second specific emotional state, and

one of the second plurality of different areas is selectable by the user to input, to the user interface terminal apparatus, as the target emotion value.

19 . The content recommendation system according to claim 17 , wherein

the user interface terminal apparatus acquires the generated first estimated emotion value, and

the first target-input user interface displays an object that represents the first estimated emotion value on a first area of the first plurality of different areas.

20 . The content recommendation system according to claim 19 , wherein

the target emotion value is input to the user interface terminal apparatus based on the user input,

the user input corresponds to swipe from the first area to a second area of the first plurality of different areas, and

the second area includes the target emotion value.

21 . The content recommendation system according to claim 17 , wherein

the first target-input user interface displays a pictogram in each of the first plurality of different areas, and

the pictogram represents the specific emotional state of a respective area of the first plurality of different areas.

22 . The content recommendation system according to claim 1 , wherein the content library is generated by an information processing apparatus that

acquires a plurality of first pieces of chronological vital data of a plurality of subjects in a controlled environment, wherein

the plurality of first pieces of chronological vital data includes the first chronological vital data,

a set of pieces of chronological vital data of the plurality of first pieces of chronological vital data is continuously and chronologically sensed by a respective vital sensor of a plurality of vital sensors,

each of the plurality of vital sensors is associated with a respective subject of the plurality of subjects, and

the plurality of vital sensors includes the vital sensor;

generate a plurality of first pieces of chronological vital-feature-amount data of the plurality of subjects based on the plurality of first pieces of chronological vital data of the plurality of subjects, wherein the plurality of first pieces of chronological vital-feature-amount data includes the first chronological vital-feature-amount data;

generate a plurality of first estimated emotion values of the plurality of subjects based on the plurality of first pieces of chronological vital-feature-amount data of the plurality of subjects, wherein the plurality of first estimated emotion values includes the first estimated emotion value;

control each of the plurality of subjects to experience a piece of content of the plurality of pieces of content in the controlled environment;

generate a plurality of second pieces of chronological vital-feature-amount data of the plurality of subjects based on a plurality of second pieces of chronological vital data of the plurality of subjects, wherein the plurality of second pieces of chronological vital data of the plurality of subjects is acquired based on the experience of the piece of content by the respective subject;

a plurality of second estimated emotion values based on the plurality of second pieces of chronological vital-feature-amount data of the plurality of subjects; and

register the piece of content in the content library based on the plurality of first estimated emotion values and the plurality of second estimated emotion values.

23 . The content recommendation system according to claim 1 , wherein

the vital sensor is included in a wearable device, and

the vital sensor acquires, as the vital data, at least one of data of brain waves, pulse waves, a pulse, a blood pressure, a blood flow, sweating, breathing, a temperature by brain wave measurement, plethysmography, skin conductance measurement, laser Doppler, image-capturing by an RGB camera, or image-capturing by a thermographic camera.

24 . The content recommendation system according to claim 1 , wherein the processor is further configured to generate the context information based on at least one of the first chronological vital-feature-amount data, environment data of an environment of the user, or an activity state of the user.

25 . The content recommendation system according to claim 1 , wherein the processor is further configured to generate the first estimated emotion value based on the first chronological vital-feature-amount data and the context information.

26 . A content recommendation method, comprising:

acquiring chronological vital data that is vital data of a user, wherein the chronological vital data of the user is continuously and chronologically sensed by a vital sensor;

generating chronological vital-feature-amount data based on the chronological vital data;

generating, based on the chronological vital-feature-amount data, an estimated emotion value, wherein the estimated emotion value is an estimated value of an emotion of the user;

acquiring a target emotion value based on a user input through a user interface terminal apparatus, wherein the target emotion value indicates an emotion that is a target of the user;

selecting, from a content library, a plurality of pieces of content, wherein the plurality of pieces of content is selected to reach the target emotion value from the estimated emotion value;

generating context information regarding the user;

narrowing down the selected plurality of pieces of content to at least one piece of content based on the context information; and

recommending the at least one piece of content to the user interface terminal apparatus.

27 . A content library generation system, comprising:

a processor configured to:

acquire a plurality of first pieces of chronological vital data of a plurality of subjects in a controlled environment, wherein

a set of pieces of chronological vital data of the plurality of first pieces of chronological vital data is continuously and chronologically sensed by a respective vital sensor of a plurality of vital sensors, and

each of the plurality of vital sensors is associated with a respective subject of the plurality of subjects;

generate a plurality of first pieces of chronological vital-feature-amount data of the plurality of subjects based on the plurality of first pieces of chronological vital data of the plurality of subjects;

generate first estimated emotion values of the plurality of subjects based on the plurality of first pieces of chronological vital-feature-amount data of the plurality of subjects;

control each of the plurality of subjects to experience a piece of content in the controlled environment;

generate a plurality of second pieces of chronological vital-feature-amount data of the plurality of subjects based on a plurality of second pieces of chronological vital data of the plurality of subjects, wherein the plurality of second pieces of chronological vital data of the plurality of subjects is acquired based on the experience of the piece of content by the respective subject;

generate second estimated emotion values based on the plurality of second pieces of chronological vital-feature-amount data of the plurality of subjects;

register the piece of content in a content library based on the first estimated emotion values and the second estimated emotion values;

generate a current estimated emotion value of a subject of the plurality of subjects;

select, from the content library, a plurality of pieces of content, wherein

the plurality of pieces of content is selected to reach a target emotion value of the subject from the current estimated emotion value of the subject, and

the plurality of pieces of content includes the piece of the content;

generate context information regarding the subject;

narrow down the selected plurality of pieces of content to at least one piece of content based on the context information; and

recommend the at least one piece of content to a user interface terminal apparatus associated with the subject.

28 . A method for generating a content library, the method comprising:

by a processor of a content recommendation system:

acquiring a plurality of first pieces of chronological vital data of a plurality of subjects in a controlled environment, wherein

a set of pieces of chronological vital data of the plurality of first pieces of chronological vital data is continuously and chronologically sensed by a respective vital sensor of a plurality of vital sensors, and

each of the plurality of vital sensors is associated with a respective subject of the plurality of subjects;

generating a plurality of first pieces of chronological vital-feature-amount data of the plurality of subjects based on the plurality of first pieces of chronological vital data of the plurality of subjects;

generating first estimated emotion values of the plurality of subjects based on the plurality of first pieces of chronological vital-feature-amount data of the plurality of subjects;

controlling each of the plurality of subjects to experience a piece of content in the controlled environment;

generating a plurality of second pieces of chronological vital-feature-amount data of the plurality of subjects based on a plurality of second pieces of chronological vital data of the plurality of subjects, wherein the plurality of second pieces of chronological vital data of the plurality of subjects is acquired based on the experience of the piece of content by the respective subject;

generating second estimated emotion values based on the plurality of second pieces of chronological vital-feature-amount data of the plurality of subjects;

registering the piece of content in the content library based on the first estimated emotion values and the second estimated emotion values;

generating a current estimated emotion value of a subject of the plurality of subjects;

selecting, from the content library, a plurality of pieces of content, wherein

the plurality of pieces of content is selected to reach a target emotion value of the subject from the current estimated emotion value of the subject, and

the plurality of pieces of content includes the piece of the content;

generate context information regarding the subject;

narrowing down the selected plurality of pieces of content to at least one piece of content based on the context information; and

recommending the at least one piece of content to a user interface terminal apparatus associated with the subject.

29 . A content recommendation system, comprising:

a user interface terminal apparatus configured to display a target-input user interface, wherein

the target-input user interface is a Graphical User Interface (GUI) to receive a target emotion value based on a user input, and

the target emotion value indicates an emotion that is a target of a user; and

a processor configured to:

acquire chronological vital data that is vital data of the user, wherein the chronological vital data of the user is continuously and chronologically sensed by a vital sensor;

generate chronological vital-feature-amount data based on the chronological vital data;

generate, based on the chronological vital-feature-amount data, an estimated emotion value, wherein the estimated emotion value is an estimated value of an emotion of the user;

acquire the target emotion value based on the user input through the user interface terminal apparatus; and

select, from a content library, a plurality of pieces of content, wherein the plurality of pieces of content is selected to reach the target emotion value from the estimated emotion value;

generate context information regarding the user;

narrow down the selected plurality of pieces of content to at least one piece of content based on the context information; and

recommend the at least one piece of content to the user interface terminal apparatus, wherein

the target-input user interface includes, in a single-axis direction, a plurality of different areas,

each of the plurality of different areas corresponds to a respective probability of a first probability in a specific emotional state and a second probability in the specific emotional state, and

one of the plurality of different areas is selectable by the user to input the respective probability of a corresponding area of the plurality of different areas, wherein the respective probability is input to the user interface terminal apparatus as the target emotion value.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (12)