Method and system for predicting human cognitive performance

• US 7,766,827 B2
• Filed: 01/15/2004
• Issued: 08/03/2010
• Est. Priority Date: 10/30/1998
• Status: Active Grant

• Current Assignee: United States Army (U.S. Department Of Defense)
• Original Assignee: United States Of America As Represented By The Secretary Of The Army (Government of the United States of America)
• 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.
• Primary Examiner(s): Nasser; Robert L
• Application Number:
  US10/757,480
• Publication Number:
  US 20050033122A1
• Time in Patent Office: 2,392 Days
• Field of Search: None
• 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 performance 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 having a first sinusoidal curve with a 24 hour period and a second sinusoidal curve with a 12 hour period using a processor,

calculating a cognitive level of a person using a processor based on the person'"'"'s sleep/wake data received from an actigraph or a polysomnography system,

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

2. The method according to claim 1, wherein said sleep/wake data contains a series of epochs where each epoch is classified as sleep or wake.

3. A system comprising:

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

a microprocessor including

means for modeling a circadian rhythm,

means for determining a cognitive level of a person based on the person'"'"'s sleep/wake data at predetermined fixed intervals having an identical time period, wherein there are multiple intervals in each 24 hour period and

means for calculating a predicted cognitive performance in response to said determination of said cognitive level based on said circadian rhythm and said cognitive level, and

a display to show the predicted cognitive performance.

4. The system according to claim 3, wherein said input device is in communication with an actigraph.

5. The system according to claim 3, wherein said input device is in communication with a polysomnography system.

6. A computer program product stored on a computer readable medium for predicting a cognitive performance level of an individual, the computer program product comprising:

first program instructions to model a circadian rhythm,

second program instructions to determine a cognitive level of a person based on the person'"'"'s sleep/wake data that includes a series of epochs where each equal length epoch is classified as sleep or wake, and

third program Instructions to calculate a predicted cognitive performance for each epoch of data based on said circadian rhythm and said cognitive level.

7. The computer program product according to claim 6, wherein the circadian rhythm has a first sinusoidal curve with a 24 hour period and a second sinusoidal curve with a 12 hour period.

8. 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 an actigraph or a polysomnography system,

selecting a function based on the data series, wherein the function is selected from a group consisting of a wake function, a sleep function, and a sleep inertia function, where

the wake function is expressed as follows

w(t)=C<sub>t−

1</sub>−

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,

determining a cognitive performance capacity using the selected function using a processor,

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

providing the modulated value.

9. A system comprising:

at least one input device for receiving sleep/wake data, wherein said sleep/wake data contains a series of epochs where each equal length epoch is classified as sleep or wake,

a microprocessor including

means for modeling a circadian rhythm,

means for determining a cognitive level of a person based on the person'"'"'s sleep/wake data, and

means for calculating a predicted cognitive performance based on said circadian rhythm and said cognitive level, and

a display to show the predicted cognitive performance.

10. A system comprising:

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

a microprocessor including

means for modeling a circadian rhythm, wherein the circadian rhythm has a first sinusoidal curve with a 24 hour period and a second sinusoidal curve with a 12 hour period,

means for determining a cognitive level of a person based on the person'"'"'s sleep/wake data, and

means for calculating a predicted cognitive performance based on said circadian rhythm and said cognitive level, and

a display to show the predicted cognitive performance.

11. A system comprising:

at least one input device for receiving sleep/wake data, wherein the person'"'"'s sleep/wake data includes a series of epochs where each equal length epoch is classified as sleep or wake,

a microprocessor including

means for modeling a circadian rhythm,

means for determining a cognitive level of a person based on the person'"'"'s sleep/wake data, and

means for calculating a predicted cognitive performance based on said circadian rhythm and said cognitive level, said means for calculating the predicted cognitive performance performs the calculation for each epoch of data.

12. The system according to claim 11, further comprising a display to show the predicted cognitive performance.

13. A method comprising:

calculating a cognitive level of a person using a processor based on the person'"'"'s sleep/wake data received from an actigraph or a polysomnography system,

retrieving from memory a time of day value for a time of day that the calculated cognitive level is being calculated for, where the time of day value is from a data series of time of days values that together approximate a curve having a first curve component having a 24 hour period and a second curve component having a 12 hour period,

calculating a predicted cognitive performance using a processor based on said retrieved time of day value and said cognitive level, and

displaying said calculated predicted cognitive performance.