Abstract: A training device including a motion data acquisition unit that acquires first motion data related to a target motion, a first generation unit that generates pseudo first motion data by using a first generation model, a determination unit that calculates a determination loss indicating a degree of deviation between the first motion data and the pseudo first motion data using a determination model, a relevance calculation unit that reconfigures the target motion by a combination of basis motions and calculate a degree of relevance between the target motion and the basis motions, a regularization loss calculation unit that calculates a regularization loss indicating a degree of deviation between motion data related to the basis motions and the pseudo first motion data, and an adversarial training processing unit that adversarially trains the first generation model and the determination model using the determination loss and the regularization loss.

Abstract: An estimation device that includes a detection unit that detects a terminal stance period from time-series data of sensor data based on a physical quantity related to movement of a foot measured by a sensor provided at a foot portion, a feature amount extraction unit that extracts a feature amount from an angular waveform in a coronal plane during the terminal stance period, and a presumption unit that estimates a degree of pronation/supination of the foot by using the feature amount extracted from the angular waveform in the coronal plane.

Abstract: Provided is a pelvic inclination estimation device including a communication unit that acquires feature amount data including a feature amount to be used for estimation of a pelvic inclination, the feature amount being extracted from a gait waveform of a spatial acceleration and a spatial angular velocity included in sensor data related to movement of a foot of a subject, a storage unit that stores an estimation model that outputs an estimation value related to the pelvic inclination according to an input of the feature amount included in the feature amount data, an estimation unit that inputs a feature amount included in the acquired feature amount data to the estimation model and estimate a pelvic inclination of the subject according to the estimation value output from the estimation model, and an output unit that outputs information associated to the pelvic inclination of the subject.

Abstract: An estimation device that includes a detection unit that detects a terminal stance period from time-series data of sensor data based on a physical quantity related to movement of a foot measured by a sensor provided at a foot portion, a feature amount extraction unit that extracts a feature amount from an angular waveform in a coronal plane during the terminal stance period, and a presumption unit that estimates a degree of pronation/supination of the foot by using the feature amount extracted from the angular waveform in the coronal plane.

Abstract: An estimation device that includes a detection unit that detects a terminal stance period from time-series data of sensor data based on a physical quantity related to movement of a foot measured by a sensor provided at a foot portion, a feature amount extraction unit that extracts a feature amount from an angular waveform in a coronal plane during the terminal stance period, and a presumption unit that estimates a degree of pronation/supination of the foot by using the feature amount extracted from the angular waveform in the coronal plane.

Abstract: Provided is a waist swinging estimation device including a communication unit that acquires feature amount data including a feature amount extracted from a gait waveform of a spatial acceleration and a spatial angular velocity included in sensor data regarding a movement of a foot of a subject and used for estimation of waist swinging that is an index regarding a movement of a waist, a storage unit that stores an estimation model that outputs an estimated value regarding the waist swinging according to an input of a feature amount included in the feature amount data, an estimation unit that inputs a feature amount included in the acquired feature amount data to the estimation model, and estimate waist swinging of the subject according to an estimated value regarding the waist swinging output from the estimation model, and an output unit that outputs information according to waist swinging of the subject.

Abstract: A data conversion device including a feature amount calculation unit that normalizes posture data estimated in each frame constituting moving image data including a synchronization target motion into an angular representation, and calculates a feature amount in an embedded space by inputting the posture data normalized into the angular representation to an encoder, a distance calculation unit that calculates a distance between a feature amount calculated in each frame constituting reference moving image data and a feature amount calculated in each frame constituting synchronization target moving image data, a synchronization processing unit that calculates an optimal path for each frame based on the calculated distance and synchronizes the synchronization target moving image data with the reference moving image data by aligning timings of frames connected by the optimal path, and an output unit that outputs the synchronization target moving image data synchronized with the reference moving image data.

Abstract: Provided is a pelvic inclination estimation device including a communication unit that acquires feature amount data including a feature amount to be used for estimation of a pelvic inclination, the feature amount being extracted from a gait waveform of a spatial acceleration and a spatial angular velocity included in sensor data related to movement of a foot of a subject, a storage unit that stores an estimation model that outputs an estimation value related to the pelvic inclination according to an input of the feature amount included in the feature amount data, an estimation unit that inputs a feature amount included in the acquired feature amount data to the estimation model and estimate a pelvic inclination of the subject according to the estimation value output from the estimation model, and an output unit that outputs information associated to the pelvic inclination of the subject.

Abstract: A feature-amount generation device that includes an extraction unit that generates a gait waveform for one gait cycle from time-series data of sensor data related to a motion of a foot, extracts a feature amount from the generated gait waveform, and extracts a gait phase cluster by integrating a plurality of temporally continuous gait phases from each of which a feature amount is extracted, and a generation unit that generates a feature amount of the gait phase cluster using a preset feature-amount constitutive expression, and generates feature-amount data in which the plurality of gait phases constituting the gait phase cluster and the feature amount of the gait phase cluster are associated with each other.

Abstract: A data processing device that includes a classification unit that classifies at least one piece of living-body information data into at least one group based on an attribute of at least one user, the at least one piece of living-body information data including a sensor value relating to a living body of the user, and a measurement time and a measurement position of the sensor value, and a learning unit that generates, for each of the group, a model for estimating interpolation data for interpolating a deficit of the living-body information data using a correlation among the sensor value included in the living-body information data, the measurement time, and the measurement position.

Abstract: A data processing device that includes a classification unit that classifies at least one piece of living-body information data into at least one group based on an attribute of at least one user, the at least one piece of living-body information data including a sensor value relating to a living body of the user, and a measurement time and a measurement position of the sensor value, and a learning unit that generates, for each of the group, a model for estimating interpolation data for interpolating a deficit of the living-body information data using a correlation among the sensor value included in the living-body information data, the measurement time, and the measurement position.

Abstract: A data processing device that includes a classification unit that classifies at least one piece of living-body information data into at least one group based on an attribute of at least one user, the at least one piece of living-body information data including a sensor value relating to a living body of the user, and a measurement time and a measurement position of the sensor value, and a learning unit that generates, for each of the group, a model for estimating interpolation data for interpolating a deficit of the living-body information data using a correlation among the sensor value included in the living-body information data, the measurement time, and the measurement position.

Abstract: An index value estimation device including a data acquisition unit that acquires feature amount data including a feature amount extracted from sensor data related to a motion of a foot of a user and used for estimating an index value indicating a knee state of the user, a storage unit that stores an estimation model that outputs an index value according to an input of the feature amount data, an estimation unit that estimates an output obtained by inputting the acquired feature amount data to the estimation model as an index value indicating the knee state of the user, and an output unit that outputs information about the estimated index value indicating the knee state of the user.

Abstract: An information processing system includes an identification unit configured to identify unique information on shoes using at least part of a captured image of the shoes, and a setting unit configured to set an association between an acquisition device configured to acquire the unique information and a module device attached to the shoes based on the unique information.

Abstract: A mobile terminal detects a self-device being located at a predetermined location, and stops reception of sensing information from a module device that transmits the sensing information, if being located at the predetermined location is detected. A fixed device receives the sensing information from the module device, and transmits the sensing information to a cloud server.

Abstract: Please delete the Abstract of the Disclosure, and replace it with the following: A feature-amount generation device that includes an extraction unit that generates a gait waveform for one gait cycle from time-series data of sensor data related to a motion of a foot, extracts a feature amount from the generated gait waveform, and extracts a gait phase cluster by integrating a plurality of temporally continuous gait phases from each of which a feature amount is extracted, and a generation unit that generates a feature amount of the gait phase cluster using a preset feature-amount constitutive expression, and generates feature-amount data in which the plurality of gait phases constituting the gait phase cluster and the feature amount of the gait phase cluster are associated with each other.

Abstract: Provided is a pelvic inclination estimation device including a communication unit that acquires feature amount data including a feature amount to be used for estimation of a pelvic inclination, the feature amount being extracted from a gait waveform of a spatial acceleration and a spatial angular velocity included in sensor data related to movement of a foot of a subject, a storage unit that stores an estimation model that outputs an estimation value related to the pelvic inclination according to an input of the feature amount included in the feature amount data, an estimation unit that inputs a feature amount included in the acquired feature amount data to the estimation model and estimate a pelvic inclination of the subject according to the estimation value output from the estimation model, and an output unit that outputs information associated to the pelvic inclination of the subject.

Abstract: Provided is a waist swinging estimation device including a communication unit that acquires feature amount data including a feature amount extracted from a gait waveform of a spatial acceleration and a spatial angular velocity included in sensor data regarding a movement of a foot of a subject and used for estimation of waist swinging that is an index regarding a movement of a waist, a storage unit that stores an estimation model that outputs an estimated value regarding the waist swinging according to an input of a feature amount included in the feature amount data, an estimation unit that inputs a feature amount included in the acquired feature amount data to the estimation model, and estimate waist swinging of the subject according to an estimated value regarding the waist swinging output from the estimation model, and an output unit that outputs information according to waist swinging of the subject.

Abstract: An index value estimation device including a data acquisition unit that acquires feature amount data including a feature amount extracted from sensor data related to a motion of a foot of a user and used for estimating an index value indicating a knee state of the user, a storage unit that stores an estimation model that outputs an index value according to an input of the feature amount data, an estimation unit that estimates an output obtained by inputting the acquired feature amount data to the estimation model as an index value indicating the knee state of the user, and an output unit that outputs information about the estimated index value indicating the knee state of the user.

Abstract: Provided is a gait information generation device including an acquisition unit that acquires gait data including time-series data of a foot position of a subject, a detection unit that detects a start point and an end point of a gait cycle from the time-series data of the foot position included in the gait data, a calculation unit that calculates a first movement amount component related to the start point and a second movement amount component related to the end point, a gait information generation unit that generates gait information about a gait movement path of the subject using the calculated first movement amount component and the calculated second movement amount component, and an output unit that outputs the generated gait information.