Estimation device, estimation system, estimation method, and recording medium

Patent metadata

Field	Value
Publication number	US-2024257975-A1
Application number	US-202118560462-A
Country	US
Kind code	A1
Filing date	May 21, 2021
Priority date	May 21, 2021
Publication date	Aug 1, 2024
Grant date	—

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.

First claim

What is claimed is:

1 . An estimation device comprising:
a memory storing instructions; and a processor connected to the at least one memory and configured to execute the instructions to:
extract, from a gait waveform extracted from time series data of sensor data based on a motion of a foot of a user, a feature amount according to an attribute of the user in a section in which a feature of a physical condition according to the attribute of the user appears; and
estimate the physical condition of the user using the feature amount extracted according to the attribute of the user.

2 . The estimation device according to claim 1 , wherein
the processor is configured to execute the instructions to input the feature amount extracted from the gait waveform of the user to an inference model that outputs an estimation result regarding a physical condition according to the attribute according to an input of the feature amount extracted according to the attribute, and estimate the physical condition of the user based on the estimation result output from the inference model.

3 . The estimation device according to claim 1 , wherein
the processor is configured to execute the instructions to extract the feature amount from a gait waveform regarding an angle in a coronal plane, and estimate a degree of pronation/supination of a foot using the feature amount extracted from the gait waveform regarding the angle in the coronal plane.

4 . The estimation device according to claim 3 , wherein
the processor is configured to execute the instructions to input the feature amount extracted from the gait waveform of the user to an inference model trained with a data set in which the feature amount extracted from the gait waveform regarding the angle in the coronal plane is set as an explanatory variable and a center of pressure excursion index obtained from a foot pressure distribution measured by a pressure sensor is set as an objective variable in a section in which a physical condition feature according to the attribute appears for a plurality of subjects, and estimates a degree of pronation/supination of a foot of the user.

5 . The estimation device according to claim 4 , wherein
in a case where the user is a woman, the processor is configured to execute the instructions to extract the feature amount in a female feature amount extraction period including a period immediately after heel strike and a period of single-leg support from the gait waveform regarding an angle in the coronal plane, and input the feature amount extracted in the female feature amount extraction period to a female inference model trained with the feature amount extracted in the female feature amount extraction period for a plurality of female subjects and estimates a degree of pronation/supination of the user, and in a case where the user is a male, the processor is configured to execute the instructions to extract the feature amount in a male feature amount extraction period including a period immediately before toe off and a period immediately before heel strike, and input the feature amount extracted in the male feature amount extraction period to a male inference model trained with the feature amount extracted from the male feature amount extraction period for a plurality of male subjects and estimates a degree of pronation/supination of the user.

6 . The estimation device according to claim 4 , wherein
in a case where the user is an elderly person, the processor is configured to execute the instructions to extract the feature amount in an elderly person feature amount extraction period including a period immediately after heel strike and a period immediately before heel strike from the gait waveform regarding an angle in the coronal plane, and input the feature amount extracted in the elderly person feature amount extraction period to an elderly person inference model trained with the feature amount extracted in the elderly person feature amount extraction period for a plurality of elderly subjects and estimates a degree of pronation/supination of the user, and in a case where the user is a young person, the processor is configured to execute the instructions to extract the feature amount in a young person feature amount extraction period including a period immediately before toe off and a period immediately before heel strike from the gait waveform regarding an angle in the coronal plane, and input the feature amount extracted in the young person feature amount extraction period to a young person inference model trained with the feature amount extracted in the young person feature amount extraction period for a plurality of young subjects and estimate a degree of pronation/supination of the user.

7 . The estimation device according to claim 1 , wherein
the processor is configured to execute the instructions to output a determination result indicating which of pronated/supinated or normal a foot is according to an estimated value of the center of pressure excursion index.

8 . An estimation system comprising:
the estimation device according to claim 1 ; and a data acquisition device that is installed at a foot portion of the user, measures a spatial acceleration and a spatial angular velocity, generates sensor data based on the measured spatial acceleration and the measured spatial angular velocity, and transmits the generated sensor data to the estimation device.

9 . An estimation method executed by a computer, the method comprising:
extracting, from a gait waveform extracted from time series data of sensor data based on a motion of a foot of a user, a feature amount according to an attribute of the user in a section in which a feature of a physical condition according to the attribute of the user appears; and estimating the physical condition of the user using the feature amount extracted according to the attribute of the user.

10 . A non-transitory program recording medium storing a program for causing a computer to execute:
a process of extracting, from a gait waveform extracted from time series data of sensor data based on a motion of a foot of a user, a feature amount according to an attribute of the user in a section in which a feature of a physical condition according to the attribute of the user appears; and a process of estimating the physical condition of the user using the feature amount extracted according to the attribute of the user.

11 . The estimation device according to claim 1 , wherein
the processor is configured to execute the instructions to estimate the physical condition of the user by using the inference model learned by machine learning, and output information to assist the user's decision making to contact a medical institution

Assignees

• Nec Corp

Inventors

• Huang Chenhui
• Wang Zhenwei
• Fukushi Kenichiro
• Nihey Fumiyuki
• Kajitani Hiroshi
• Nakahara Kentaro

Classifications

• A61B5/7275

  Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor · CPC title

• A61B5/7435

  Displaying user selection data, e.g. icons in a graphical user interface · CPC title

• A61B2562/0247

  Pressure sensors · CPC title

• A61B2562/0219

  Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches · CPC title

• A61B5/6807

  Footwear · CPC title