Method for creating physical condition variation prediction model, physical condition variation prediction system, physical condition variation prediction method, physical condition variation prediction model, and method for creating regularity identification model

A physical condition variation prediction method for predicting variation in a physical condition of a subject on a bed, the physical condition variation prediction method comprising:

• determining a bed rest state of the subject on the basis of biological information of the subject acquired by a sensor;
• acquiring a state trend corresponding to a trend of the bed rest state per unit time;
• identifying a regularity included in temporal fluctuation of the state trend;
• and
• inputting the regularity into a physical condition variation prediction model to predict variation in a physical condition of the subject, wherein
• the physical condition variation prediction model is a learned model obtained by learning, by supervised machine learning using teaching data obtained by associating the regularity identified for a subject for teaching data and physical condition variation information indicating variation in a physical condition of the subject for teaching data, a correlation between the regularity and the physical condition variation information of the subject for teaching data.

A method for creating a regularity identification model, the method comprising:

• acquiring biological information of a subject on a bed by a sensor;
• determining a bed rest state of the subject on the basis of the biological information of the subject;
• acquiring a state trend corresponding to a trend of the bed rest state per unit time;
• and
• creating, by machine learning using the state trend as training data, a regularity identification model configured to identify a predetermined regularity included in temporal fluctuation of the state trend.