Method and system for predicting human cognitive performance

• US 20050033122A1
• Filed: 01/15/2004
• Published: 02/10/2005
• Est. Priority Date: 10/30/1998
• Status: Active Grant

• Current Assignee: United States Army (U.S. Department Of Defense)
• Original Assignee: The United States of America As Represented By The Secretary of Agriculture
• Inventors: Wesensten, Nancy Jo, Hall, Stanley W., Redmond, Daniel P., Thomas, Maria L., Belenky, Gregory L., Kamimori, Gary H., Balkin, Thomas J., Thorne, David R., Sing, Helen C.
• Granted Patent: US 7,766,827 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/16 Devices for psychotechnics using teaching or educational appliances G09B1/00 - G09B7/00; Testing reaction times ; Devices for evaluating the psychological state
• CPC Class Codes: A61B 5/4806 Sleep evaluation A61B5/4821 takes precedence; devices for inducing sleep A61M21/02
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

An apparatus and a method for predicting cognitive performance of an individual based on factors including preferably sleep history and the time of day. The method facilitates the creation of predicted cognitive preformance curves that allow an individual to set his/her sleep times to produce higher levels of cognitive performance. The method also facilitates the reconstruction of past cognitive performance levels based on sleep history.

Claims

1. A method comprising:

modeling a circadian rhythm,

calculating a cognitive level of a person based on the person'"'"'s sleep/wake data,

calculating a predicted cognitive performance based on said circadian rhythm and said cognitive level.

2. A system for performing the method according to claim 1, said system comprising:

at least one input device for entering sleep/wake data,

a microprocessor that performs the method of claim 1, and

a display to show the predicted cognitive performance.

3. A computer-readable medium having computer-executable instructions for performing the method recited in claim 1.

4. A method of evaluating the effectiveness of a person to perform a task based on previous or predicted sleep pattern comprising the steps of:

modeling circadian oscillators for the person;

calculating the amount of effective sleep in a sleep reservoir for the person based on the person'"'"'s sleep and activity pattern; and

calculating an effectiveness of the person to perform said task based on said oscillators and said sleep reservoir.

5. A method as recited in claim 4, comprising the further step of calculating a sleep debt.

6. A method as recited in claim 5, further comprising the step of calculating sleep intensity based on said sleep debt.

7. A method as recited in claim 6, wherein said step of modeling circadian oscillators further comprises determining sleep propensity and performance rhythm.

8. A method as recited in claim 7, wherein said step of modeling circadian oscillators is done according to the equation:

m(t)=F+(A₁*cos(2Π

(t−

V₁)/P₁)+A₂*cos(2Π

(t−

V₂)/P₂))

where F is an offset, t is the time of day, P₁ and P₂ are periods of two sinusoids, V₁ and V₂ are the peak times of day in time units or epochs past midnight, and A₁ and A₂ are amplitudes of their respective cosine curves.

9. A method as recited in claim 5, wherein said step of determining the person'"'"'s sleep debt is based on said amount of effective sleep in the sleep reservoir.

10. A method as recited in claim 4, comprising the further step of determining if the person'"'"'s sleep experienced any fragmentation.

11. A method as recited in claim 10, wherein said step of determining if the person'"'"'s sleep experienced any fragmentation is based on frequency of awakenings from sleep.

12. A method as recited in claim 4, comprising the further step of determining sleep inertia for the person.

13. A method as recited in claim 12, wherein said effectiveness of the person to perform said task is calculated based upon said circadian oscillators, said amount of effective sleep in said sleep reservoir, and said sleep inertia.

14. A method of evaluating the effectiveness of a person to perform a task based on sleep patterns comprising the steps of:

modeling circadian oscillators for the person;

calculating the amount of effective sleep in a sleep reservoir for the person;

determining if the person'"'"'s sleep experienced any fragmentation; and

calculating the effectiveness of the person to perform said task.

15. A method as recited in claim 14, comprising the further step of calculating a sleep intensity to determine a rate of sleep accumulation.

16. A method as recited in claim 14, comprising the further step of determining sleep inertia for the person, and

wherein said effectiveness of the person to perform said task is calculated based upon said circadian oscillators, said amount of effective sleep in said sleep reservoir, and said sleep inertia.

17. A system of evaluating the effectiveness of a person to perform a task based on sleep pattern comprising:

at least one input device for entering sleep/wake data;

a microprocessor that models circadian oscillators, calculates an amount of effective sleep in a sleep reservoir based on a sleep and activity pattern, and calculates an effectiveness to perform a task based on said oscillators and said sleep reservoir, based on said sleep/wake data; and

a display to show said effectiveness results.

18. A system as recited in claim 17, wherein said at least one input device provides data for an individual person.

19. A computer readable medium having computer-executable instructions for evaluating the effectiveness of a person to perform a task based on sleep pattern comprising the steps of:

modeling circadian oscillators for a person;

calculating the amount of effective sleep in a sleep reservoir for the person based on their sleep and activity pattern; and

calculating an effectiveness of the person to perform said task based on said oscillators and said sleep reservoir.

20. A computer readable medium having computer-executable instructions for evaluating the effectiveness of a person to perform a task based on sleep pattern, as recited in claim 19, comprising the further step of determining if the person'"'"'s sleep experienced any fragmentation.

21. A computer-readable medium having computer-executable instructions for evaluating the effectiveness of a person to perform a task based on sleep pattern comprising the steps of:

modeling circadian oscillators for the person;

calculating the amount of effective sleep in a sleep reservoir for the person;

determining if the person'"'"'s sleep experienced any fragmentation; and

calculating the effectiveness of the person to perform said task.

22. A computer-readable medium having computer-executable instructions for evaluating the effectiveness of a person to perform a task based on sleep pattern, as recited in claim 21, comprising the further step of determining sleep inertia for the person.

23. In a computer system having an interface including a display and a user interface selection device, a method of evaluating the effectiveness of a person to perform a task based on a sleep pattern using the interface, comprising the steps of:

(i) receiving sleep pattern data for an individual;

(ii) displaying a schedule based on the sleep schedule data; and

(iii) calculating and displaying a measure of task performance, wherein the measure is based at least in part on the received sleep pattern data.

24. The method of claim 23, further comprising steps of:

(iv) entering a parameter affecting the displayed schedule; and

(v) displaying a second schedule for the individual, wherein the second schedule includes a recalculated measure of task performance responsive to the entered parameter.

25. The method of claim 24, wherein step (iv) comprises modifying an existing parameter.

26. The method of claim 24, wherein step (iv) comprises editing a sleep and work interval.

27. The method of claim 23, wherein step (iii) comprises the steps of:

(a) modeling circadian oscillators for the individual;

(b) calculating the amount of effective sleep in a sleep reservoir for the individual based on the individual'"'"'s sleep and activity pattern; and

(c) calculating the measure of task performance based on the oscillators and the sleep reservoir.

28. The method of claim 23, further comprising the step of storing the measure of task performance to a file.

29. The method of claim 23, wherein step (i) comprises receiving sleep pattern data as input from a user of the computer system.

30. A computer readable medium storing computer readable instructions that, when executed by a computer system, perform a method of evaluating the effectiveness of a person to perform a task based on a sleep pattern using the interface, comprising the steps of:

(i) receiving sleep pattern data for an individual;

(ii) displaying a schedule based on the sleep schedule data; and

(iii) calculating and displaying a measure of task performance, wherein the measure is based at least in part on the received sleep pattern data.

31. The computer readable medium of claim 30, wherein the computer readable instructions further cause a computer system to perform method steps comprising:

(iv) entering a parameter affecting the displayed schedule; and

(v) displaying a second schedule for the individual, wherein the second schedule includes a recalculated measure of task performance responsive to the entered parameter.

32. The computer readable medium of claim 30, wherein step (iv) comprises modifying an existing parameter.

33. The computer readable medium of claim 30, wherein step (iv) comprises editing a sleep and work interval.

34. The computer readable medium of claim 30, wherein step (iii) comprises:

(a) modeling circadian oscillators for the individual;

(b) calculating the amount of effective sleep in a sleep reservoir for the individual based on the individual'"'"'s sleep and activity pattern; and

(c) calculating the measure of task performance based on the oscillators and the sleep reservoir.

35. A method for providing a cognitive performance level comprising:

receiving a data series representing at least one wake state and at least one sleep state,

selecting a function based on the data series,

determining a cognitive performance capacity using the selected function,

modulating the cognitive performance capacity with a time of day value, and

providing the modulated value.

36. The method according to claim 35, wherein the selecting the function based on the data series includes selecting the function from a group consisting of a wake function, a sleep function, and a sleep inertia function,

the wake function is expressed as follows

w(t)=C_t−

1−

k_w

where k_w is a positive function,

the sleep function is expressed as follows

s(t)=C<sub>t−

1</sub>+(100−

C<sub>t−

1</sub>)/k_s

where k_s is a time constant, and

the sleep inertia function is expressed as follows

i(t)=C_SW*[0.75+0.025(t−

t_LS)−

(0.025(t−

t_LS))²]

where t_LS is time when the last sleep state occurred and C_SW is the cognitive level at the last sleep state.