Abstract: An estimation device that includes an acquisition unit that acquires sensor data measured in accordance with walking of the user, and physical data of the user, a storage unit that stores an estimation model and the physical data, the estimation model outputting care-related information in response to inputs of a feature quantity extracted from the sensor data and the physical data, an estimation unit that inputs the feature quantity extracted from the sensor data of the user and the physical data into the estimation model to estimate the care-related information of the user, and an output unit that outputs the estimated care-related information of the user.

Abstract: A knee pain risk estimation device includes a feature amount construction unit that constructs a feature amount related to a sign variable to be used for estimation of a knee pain risk indicating a risk of having a medical examination in a future due to knee pain, a sign variable estimation unit that inputs the feature amount to a sign variable estimation model to estimate at least one of the sign variables, and performs a principal component analysis on the estimated at least one of the sign variables to generate a principal component vector, a knee pain risk estimation unit that estimates a knee pain risk index, and generates knee pain risk information regarding the knee pain risk by using the estimated knee pain risk index, and an output unit that outputs the generated knee pain risk information.

Abstract: Provided is a learning device including a data acquisition unit that acquires a data set including a plurality of training data, a generation unit that includes a generation model that outputs pseudo data, a discrimination unit that includes a discrimination model that discriminates whether the input data is either the training data or the pseudo data according to an input of either the training data or the pseudo data, a management unit that sets a first hyperparameter to be used for updating the discrimination model based on a preset hyperparameter, and a second hyperparameter to be used for updating the generation model, and a learning processing unit that updates the discrimination model using the first hyperparameter and updates the generation model using the second hyperparameter.

Abstract: Provided is a motion data generation device including an acquisition unit that acquires a plurality of pieces of motion data to be data converted, a conversion data choosing unit that groups the plurality of pieces of motion data for each motion class that is a target motion for data augmentation, a data conversion unit that sets at least one piece of the motion data grouped for the each motion class for reference data, sets at least one piece of the motion data different from the reference data among the grouped motion data for data to be converted, and generates extension motion data in which the data to be converted is synchronized with reference to motion timing of the reference data, and an output unit that outputs the generated extension motion data.

Abstract: To estimate the body condition according to the attributes on the basis of sensor data measured while a user is walking, this estimation device comprises: a feature amount extraction unit that extracts, from a walking waveform extracted from time-series data of sensor data based on the movement of user's legs, a feature amount according to user's attributes in a section in which features of the body condition of the user according to the user's attributes are exhibited; and an estimation unit that estimates the user's body condition using the feature amount extracted according to the user's attributes.

Abstract: A training device includes an acquisition unit that acquires a data set of raw data and correct answer data, a feature amount calculation unit that calculates a feature amount using the raw data, a model construction unit that constructs an encoding model that outputs a code related to the feature amount in response to an input of the raw data and an estimation model that outputs an estimation result related to the raw data in response to an input of the code, and a training processing unit that trains the encoding model and the estimation model in such a way that the estimation result matches the correct answer data based on a relationship between the code and the feature amount.

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: A biometric information processing device includes an extraction unit that extracts a daily measurement value of a common measurement item common to facility measurement data measured in a facility from daily measurement data measured using the sensor data regarding movement of a foot of a user, and a correction unit that corrects a facility measurement value of the common measurement item stored in advance based on the extracted daily measurement value of the common measurement item.

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: 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: 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: 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: 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 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: 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: 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.