Device and method for sequential posture identification and autonomic function information acquisition
Abstract:
A wearable device attached to a subject includes an accelerometer that measures acceleration information, and a biological sensor that measures biological signal information of the subject. From the measured acceleration information and biological signal information, first feature data corresponding to a first predetermined period and second feature data corresponding to a second predetermined period are extracted. By machine learning based on the first feature data, a dynamic/static activity identification model, a dynamic-activity identification model, and a static-activity identification model, for the subject, are generated. By combination of results of determination based on each of the identification models, a posture and an activity of the subject are identified and correspondence information, which associates the identified posture and activity with the biological signal information of the subject, is generated.
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