System and method for predicting lucidity level

1. A system configured to predict a lucidity level of a subject, the system comprising:

one or more activity sensors configured to generate output signals conveying information related to physical activity of the subject;

one or more physiological sensors configured to generate output signals conveying information related to physiological parameters of the subject;

a user interface configured to receive information related to a mood of the subject and information related to a cognitive state of the subject; and

one or more hardware processors configured by machine-readable instructions to:

generate an electronic lucidity model for the subject based on previous physical activity information, previous physiological parameter information, previous mood information, and previous cognitive state information; and

predict the lucidity level of the subject based on the electronic lucidity model and one or more of current physical activity information, current physiological parameter information, current mood information, or current cognitive state information.

2. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to communicate the predicted lucidity level to a caregiver of the subject, the communication including an explanation of which of the current physical activity information, the current physiological parameter information, the current mood information, and/or the current cognitive state information influenced the predicted lucidity level.

3. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to adjust the electronic lucidity model based on the predicted lucidity level and a future cognitive state of the subject during a period of time that corresponds to the predicted lucidity level.

4. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions such that the electronic lucidity model is generated via a multiple linear regression classifier where the previous physical activity information, the previous physiological parameter information, the previous mood information, and the previous cognitive state information are inputs to the multiple linear regression classifier and the predicted lucidity level is an output.

5. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions such that predicting the lucidity level comprises generating a predicted lucidity level score.

6. The system of claim 1 , wherein:

the one or more activity sensors include one or more of a motion sensor, a geolocation sensor, a sleep sensor, a clock, instrumented household appliances, a camera, a wearable activity tracker, or a smartphone; and

the one or more physiological sensors include one or more of a heart rate monitor, a blood pressure monitor, a blood glucose monitor, or a hydration monitor.

7. A method for predicting a lucidity level of a subject with a prediction system, the prediction system comprising one or more activity sensors, one or more physiological sensors, a user interface, and one or more hardware processors, the method comprising:

generating, with the one or more activity sensors, output signals conveying information related to physical activity of the subject;

generating, with the one or more physiological sensors, output signals conveying information related to physiological parameters of the subject;

receiving, with the user interface, information related to a mood of the subject and information related to a cognitive state of the subject;

generating, with the one or more hardware processors, an electronic lucidity model for the subject based on previous physical activity information, previous physiological parameter information, previous mood information, and previous cognitive state information; and

predicting, with the one or more hardware processors, the lucidity level of the subject based on the electronic lucidity model and one or more of current physical activity information, current physiological parameter information, current mood information, or current cognitive state information.

8. The method of claim 7 , further comprising:

communicating, with the one or more hardware processors, the predicted lucidity level to a caregiver of the subject, the communication including an explanation of which of the current physical activity information, the current physiological parameter information, the current mood information, and/or the current cognitive state information influenced the predicted lucidity level.

9. The method of claim 7 , further comprising:

adjusting, with the one or more hardware processors, the electronic lucidity model based on the predicted lucidity level and a future cognitive state of the subject during a period of time that corresponds to the predicted lucidity level.

10. The method of claim 7 , further comprising:

generating the electronic lucidity model via a multiple linear regression classifier where the previous physical activity information, the previous physiological parameter information, the previous mood information, and the previous cognitive state information are inputs to the multiple linear regression classifier and the predicted lucidity level is an output.

11. The method of claim 7 , wherein predicting the lucidity level further comprises:

generating a predicted lucidity level score.

12. The method of claim 7 , wherein:

the one or more activity sensors include one or more of a motion sensor, a geolocation sensor, a sleep sensor, a clock, instrumented household appliances, a camera, a wearable activity tracker, or a smartphone; and

the one or more physiological sensors include one or more of a heart rate monitor, a blood pressure monitor, a blood glucose monitor, or a hydration monitor.

13. A system configured to predict a lucidity level of a subject, the system comprising:

means for generating output signals conveying information related to physical activity of the subject;

means for generating output signals conveying information related to physiological parameters of the subject;

means for receiving information related to a mood of the subject and information related to a cognitive state of the subject;

means for generating an electronic lucidity model for the subject based on previous physical activity information, previous physiological parameter information, previous mood information, and previous cognitive state information; and

means for predicting the lucidity level of the subject based on the electronic lucidity model and one or more of current physical activity information, current physiological parameter information, current mood information, or current cognitive state information.

14. The system of claim 13 , further comprising:

means for communicating the predicted lucidity level to a caregiver of the subject, the communication including an explanation of which of the current physical activity information, the current physiological parameter information, the current mood information, and/or the current cognitive state information influenced the predicted lucidity level.

15. The system of claim 13 , further comprising:

means for adjusting the electronic lucidity model based on the predicted lucidity level and a future cognitive state of the subject during a period of time that corresponds to the predicted lucidity level.

16. The system of claim 13 , wherein the means for generating the electronic lucidity model are further configured such that the electronic lucidity model is generated via a multiple linear regression classifier where the previous physical activity information, the previous physiological parameter information, the previous mood information, and the previous cognitive state information are inputs to the multiple linear regression classifier and the predicted lucidity level is an output.

17. The system of claim 13 , wherein the means for predicting the lucidity level are further configured such that predicting the lucidity level comprises generating a predicted lucidity level score.

18. The system of claim 13 , wherein:

the means for generating output signals conveying information related to physical activity of the subject include one or more of a motion sensor, a geolocation sensor, a sleep sensor, a clock, instrumented household appliances, a camera, a wearable activity tracker, or a smartphone; and

the means for generating output signals conveying information related to physiological parameters of the subject include one or more of a heart rate monitor, a blood pressure monitor, a blood glucose monitor, or a hydration monitor.