State extrapolation device, state extrapolation program, and state extrapolation method
AssigneeClarion Co., Ltd.
InventorTomohiro Nakamura
Life of this patent
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Abstract
An object of the present invention is to more appropriately extrapolate a sign of a state that may affect a movement of a user. A state extrapolation device according to the present invention includes a vital sign acquisition unit that acquires a vital sign of a user, and a sign detection unit that uses a learned model that has learned, as training data, sign data about the vital sign related to a predetermined physical condition abnormality, and detects a sign by determining whether or not the vital sign of the user corresponds to a sign of the predetermined physical condition abnormality.
Claims11
A state extrapolation device comprising:
- a vital sign acquisition unit that acquires a vital sign of a user;
- a sign detection unit that uses a learned model that has learned, as training data, sign data about the vital sign related to a predetermined physical condition abnormality, and detects a sign by determining whether or not the vital sign of the user corresponds to a sign of the predetermined physical condition abnormality;
- a training data generation unit that generates the training data as the training data including a vital sign of the user;
- a sign model generation unit that causes the learned model to learn the training data generated by the training data generation unit;
- and
- a state detection unit that detects an occurrence state of the predetermined physical condition abnormality of the user, wherein
- the training data generation unit generates, when the state detection unit detects the occurrence state, the training data by using first information being the vital sign of the user provided with a label in a predetermined period before the occurrence state, and second information being the vital sign of the user in the predetermined period when the occurrence state is not detected.
A product comprising programs stored in a non-transitory computer readable medium causing a computer to execute a state extrapolation procedure, the program causing the computer to function as a control means, and
- causing the control means to perform:
- a vital sign acquisition step of acquiring a vital sign of a user;
- a sign detection step of using a learned model that has learned, as training data, sign data about the vital sign related to a predetermined physical condition abnormality, and detecting a sign by determining whether or not the vital sign of the user corresponds to a sign of the predetermined physical condition abnormality;
- a training data generation step that generates the training data as the training data including a vital sign of the user;
- a sign model generation step that causes the learned model to learn the training data generated by the training data generation unit;
- and
- a state detection step that detects an occurrence state of the predetermined physical condition abnormality of the user, wherein
- the training data generation step generates, when the state detection step detects the occurrence state, the training data by using first information being the vital sign of the user provided with a label in a predetermined period before the occurrence state, and second information being the vital sign of the user in the predetermined period when the occurrence state is not detected.
A state extrapolation method causing a computer to execute a state extrapolation procedure, the computer including a control means, the state extrapolation method comprising:
- by the control means,
- a vital sign acquisition step of acquiring a vital sign of a user;
- a sign detection step of using a learned model that has learned, as training data, sign data about the vital sign related to a predetermined physical condition abnormality, and detecting a sign by determining whether or not the vital sign of the user corresponds to a sign of the predetermined physical condition abnormality;
- a training data generation step that generates the training data as the training data including a vital sign of the user;
- a sign model generation step that causes the learned model to learn the training data generated by the training data generation unit;
- and
- a state detection step that detects an occurrence state of the predetermined physical condition abnormality of the user, wherein
- the training data generation step generates, when the state detection step detects the occurrence state, the training data by using first information being the vital sign of the user provided with a label in a predetermined period before the occurrence state, and second information being the vital sign of the user in the predetermined period when the occurrence state is not detected.
Dependencies are inferred from the claim text.