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US 12,700,504 B2Granted
Estimation device, estimation system, estimation method, and recording medium
AssigneeNEC Corporation
InventorsChenhui Huang, Zhenwei Wang, Kenichiro Fukushi, Fumiyuki Nihey, Hiroshi Kajitani, Kentaro Nakahara
Life of this patent
Estimating the term…
Abstract
An estimation device including a feature amount extraction unit that extracts, 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 estimates the physical condition of the user using the feature amount extracted according to the attribute of the user.
Claims12
An estimation device comprising:
- a communication interface;
- a memory storing instructions;
- and
- a processor connected to the at least one memory and configured to execute the instructions to:
- receive, via a communication interface, time-series sensor data including three-axis acceleration and angular velocity from a data acquisition device installed in footwear at a back-of-arch position of a foot of a user;
- convert the received sensor data from a local coordinate system of the data acquisition device to a world coordinate system;
- detect gait events in the converted, received sensor data, the detected gait events including heel-strike events and toe-off events;
- generate, for one gait cycle normalized between consecutive ones of the heel-strike events, a gait waveform of a pitch angle representing rotation about a Y-axis in a coronal plane;
- extract, from the pitch-angle gait waveform, a feature amount according to an attribute of the user selected from gender and age in a section defined as a predetermined sub-range of the normalized gait cycle identified relative to the detected heel-strike and toe-off events, the feature amount comprising at least one of an arithmetic mean or an integral of the pitch angle;
- input the feature amount to an attribute-specific inference model stored in the memory, the model being trained with a data set in which a training feature amount is an explanatory variable and a center of pressure excursion index (CPEI) obtained from a foot pressure distribution measured by a pressure sensor is an objective variable for a plurality of subjects;
- execute the attribute-specific inference model to estimate the CPEI for the user based on the inputted feature amount;
- classify a degree of pronation/supination of a foot of the user based on the estimated CPEI, the classification being determined using thresholds stored in the memory including a pronation threshold and a supination threshold;
- and
- cause an output unit to present the estimated CPEI and the classification among pronation/normal/supination.
11 more elements
An estimation method executed by a computer, the method comprising:
- receiving, via a communication interface, time-series sensor data including three-axis acceleration and angular velocity from a data acquisition device installed in footwear at a back-of-arch position of a foot of a user;
- converting the received sensor data from a local coordinate system of the data acquisition device to a world coordinate system;
- detecting gait events in the converted, received sensor data, the detected gait events including heel-strike events and toe-off events;
- generating, for one gait cycle normalized between consecutive ones of the heel-strike events, a gait waveform of a pitch angle representing rotation about a Y-axis in a coronal plane;
- extracting, from the pitch-angle gait waveform, a feature amount according to an attribute of the user selected from gender and age in a section defined as a predetermined sub-range of the normalized gait cycle identified relative to the detected heel-strike and toe-off events, the feature amount comprising at least one of an arithmetic mean or an integral of the pitch angle;
- inputting the feature amount to an attribute-specific inference model stored in a memory, the model being trained with a data set in which a training feature amount is an explanatory variable and a center of pressure excursion index (CPEI) obtained from a foot pressure distribution measured by a pressure sensor is an objective variable for a plurality of subjects;
- executing the attribute-specific inference model to estimate the CPEI for the user based on the inputted feature amount;
- classifying a degree of pronation/supination of a foot of the user based on the estimated CPEI, the classification being determined using thresholds stored in the memory including a pronation threshold and a supination threshold;
- and
- causing an output unit to present the estimated CPEI and the classification among pronation/normal/supination.
7 more elements
A non-transitory program recording medium storing a program for causing a computer to execute:
- receiving, via a communication interface, time-series sensor data including three-axis acceleration and angular velocity from a data acquisition device installed in footwear at a back-of-arch position of a foot of a user;
- converting the received sensor data from a local coordinate system of the data acquisition device to a world coordinate system;
- detecting gait events in the converted, received sensor data, the detected gait events including heel-strike events and toe-off events;
- generating, for one gait cycle normalized between consecutive ones of the heel-strike events, a gait waveform of a pitch angle representing rotation about a Y-axis in a coronal plane;
- extracting, from the pitch-angle gait waveform, a feature amount according to an attribute of the user selected from gender and age in a section defined as a predetermined sub-range of the normalized gait cycle identified relative to the detected heel-strike and toe-off events, the feature amount comprising at least one of an arithmetic mean or an integral of the pitch angle;
- inputting the feature amount to an attribute-specific inference model stored in the memory, the model being trained with a data set in which a training feature amount is an explanatory variable and a center of pressure excursion index (CPEI) obtained from a foot pressure distribution measured by a pressure sensor is an objective variable for a plurality of subjects;
- executing the attribute-specific inference model to estimate the CPEI for the user based on the inputted feature amount;
- classifying a degree of pronation/supination of a foot of the user based on the estimated CPEI, the classification being determined using thresholds stored in the memory including a pronation threshold and a supination threshold;
- and
- causing an output unit to present the estimated CPEI and the classification among pronation/normal/supination.
7 more elements
Dependencies are inferred from the claim text.