CA2349561A1 - System and method for predicting human cognitive performance using data from an actigraph - Google Patents

System and method for predicting human cognitive performance using data from an actigraph Download PDF

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Publication number
CA2349561A1
CA2349561A1 CA002349561A CA2349561A CA2349561A1 CA 2349561 A1 CA2349561 A1 CA 2349561A1 CA 002349561 A CA002349561 A CA 002349561A CA 2349561 A CA2349561 A CA 2349561A CA 2349561 A1 CA2349561 A1 CA 2349561A1
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Prior art keywords
curve
function
data
sleep
time
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Granted
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CA002349561A
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French (fr)
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CA2349561C (en
Inventor
Thomas J. Balkin
Gregory L. Belenky
Stanley W. Hall
Gary H. Kamimori
Daniel P. Redmond
Helen C. Sing
Maria L. Thomas
David R. Thorne
Nancy Jo Wesensten
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Walter Reed Army Institute of Research
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Individual
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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A61B5/162—Testing reaction times
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/70—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A61B5/18—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state for vehicle drivers or machine operators

Abstract

A system and a method for providing a determination of predicted cognitive performance of an individual based the time of day and on factors including sleep history based on activity data form an actigraph. The system and metho d provide a numerical representation of the predicted cognitive performance. Both may be used to optimize the work schedule of the actigraph wearer to maximize the cognitive capacity during working hours.

Claims (53)

1. A method comprising:
collecting activity information of an individual with an actigraph, providing a data series representing wake states and sleep states of the individual based on an analysis of the activity information using a sleep scoring system, selecting a function based on the type of data in the data series, calculating a cognitive performance capacity based on the selected function, modulating the cognitive performance capacity with a time of day value, and outputting the modulated value as the cognitive performance level.
2. The method according to claim 1, further comprising:
storing the modulated values as coordinates representing time and amplitude, repeating the calculating, modulating and outputting steps of claim 1, plotting a curve from the stored modulated values, and outputting the curve representing cognitive performance level over a period of time.
3. The method according to claim 2, further comprising extrapolating from the curve a predictive curve based on anticipated wake states and anticipated sleep states.
4. The method according to claim 1, wherein said outputting step includes outputting the modulated value to a display.
5. The method according to claim 1, wherein said outputting step includes outputting the modulated value to a data file.
6. The method according to claim 1, wherein said outputting step includes outputting the modulated value to a printing device.
7. The method according to claim 1, further comprising formulating the time of day values to represent a curve having a period of 24 hours such that the curve includes a first sinusoidal curve having a 24-hour period and a second sinusoidal curve having a 12-hour period.
8. The method according to claim 1, wherein the time of day values represent a curve having a period of 24 hours such that the curve includes a first sinusoidal curve having a 24-hour period and a second sinusoidal curve having a 12-hour period.
9. The method according to claim 1, wherein the selecting step includes selecting from a group consisting of a wake function, a sleep function, a delay function, and a sleep inertia function.
10. The method according to claim 1, wherein the selecting step includes determining the present state for the data series as either the wake state or the sleep state, calculating a length of time in the present state, and selecting the function based on one of:
the length of time in the present state and the present state, and the length of time in a recent transition from wake to sleep or sleep to wake.
11. The method according to claim 10, wherein the selecting step includes selecting the function from a group consisting of a wake function, a sleep function, a delay function, and a sleep inertia function.
12. The method according to claim 1, wherein the calculating step calculates a ,cognitive performance level as a percentage value such that 100%
is a maximum cognitive performance capacity.
13. The method according to claim 1, wherein said method is performed in real-time.
14. A method comprising:
collecting activity information of an individual with an actigraph, providing a data series representing wake states and steep states of the individual based on an analysis of the activity information using a sleep scoring system, selecting a function based on the type of data in the data series, calculating a cognitive performance capacity based on the selected function, approximating a first curve of calculated cognitive performance capacities, storing the first curve, modulating the first curve with a second curve representing time of day rhythms, and outputting the modulated first curve.
15. The method according to claim 14, wherein said outputting step includes outputting a value of a point on the modulated first curve to a display.
16. The method according to claim 14, wherein said outputting step includes outputting a value of a point on the modulated first curve to a data file.
17. The method according to claim 14, wherein said outputting step includes outputting a value of a point on the modulated first curve to a printing device.
18. The method according to claim 14, further comprising extrapolating from the modulated first curve a predictive curve based on anticipated wake states and sleep states.
19. The method according to claim 14, further comprising formulating the second curve having a period of 24 hours such that the curve includes a first sinusoidal curve having a 24-hour period and a second sinusoidal curve having a 12-hour period.
20. The method according to claim 14, wherein the second curve having a period of 24 hours such that the curve includes a first sinusoidal curve having a 24-hour period and a second sinusoidal curve having a 12-hour period.
21. The method according to claim 14, wherein the selecting step includes selecting from a group consisting of a wake function, a sleep function, a delay function, and a sleep inertia function.
22. The method according to claim 14, wherein the selecting step includes:
determining the present state for the data series as either the wake state or the sleep state, calculating a length of time in the present state, and selecting the function based on one of the length of time in the present state and the present state, and the length of time in a recent transition from wake to sleep or sleep to wake.
23. The method according to claim 22, wherein the selecting step includes selecting the function from a group consisting of a wake function, a steep function, a delay function, and a sleep inertia function.
24. The method according to claim 14, wherein the calculating step includes calculating a cognitive performance level as a percentage value such that 100% is a maximum cognitive performance capacity.
25. The method according to claim 14, wherein said method operates in real-time.
26. A system comprising:
an actigraph, scoring means for providing a sleep score based on data collected by said actigraph, input means for receiving data from said scoring means, interpretation means for analyzing the received data and selecting a calculation function based on the composition of the received data, determination means for calculating a value using the calculation function, means for adding the value from said determination means to a curve including prior values, and modulating means for modulating the curve with a modulating curve to produce an output curve.
27. The system of claim 26, further comprising a display means for displaying the last value of the output curve.
28. The system of claim 26, wherein said interpretation means determines a time representing a length of time of a current state of the data.
29. The system of claim 26, wherein said interpretation means determines a time representing a transition from one state to another.
30. The system of claim 26, wherein the modulating curve represents variations over a 24-hour period.
31. The system of claim 26, wherein said modulating means matches the curve to the modulating curve based on time sequencing.
32. The system of claim 26, wherein said actigraph includes said scoring means, and communication means for communicating with said input means, said communication means connected to said scoring means; and said input means receiving data from said scoring means through said communication means.
33. The system of claim 26, wherein said determination means selects the function from a group consisting of a wake function, a sleep function, a delay function, and a sleep inertia function.
34. The system of claim 26, further comprising storage means for storing the output curve from said modulating means.
35. The system of claim 34, wherein said storage means stores the output curve as a series of data.
36. The system of claim 26, further comprising a housing, wherein said actigraph, scoring means, input means, interpretation means, determination means, adding means, and modulating means are located within said housing.
37. The system of claim 36, further comprising means for collecting data, and means for communicating either the value from said determination means or the output curve to said collecting means, said communicating means attached to said housing.
38. The system of claim 36, wherein said collecting means includes analysis means for analyzing data collected from multiple actigraphs.
39. The system of claim 26, wherein said adding means is memory.
40. A system comprising:
an actigraph, a scorer connected to said actigraph, an input connected to said scorer, a data analyzer connected to said input to select a calculation function responsive to data from said scorer, a calculator connected to said data analyzer to calculate a cognitive performance capacity using the calculation function, a first memory that stores modulation data, and a modulator connected to said first memory and said calculator to modulate the cognitive performance capacity with the modulation data to generate a predicted cognitive performance.
41. The apparatus of claim 40, further comprising a display connected to said modulator.
42. The apparatus of claim 40, further comprising an output connected to said modulator.
43. The apparatus of claim 40, further comprising a second memory connected to said modulator containing data.
44. The apparatus of claim 43, wherein said first memory and said second memory are integrally formed as one memory.
45. The apparatus of claim 43, wherein the modulation data represents time of day variations over a 24-hour period.
46. The system of claim 43, wherein said modulator matches the data in said second memory to the modulation data based on time sequencing.
47. The apparatus of claim 43, wherein said second memory is a first-in-first-out memory.
48. The apparatus of claim 40, wherein said input is a telemetric receiver.
49. The apparatus of claim 40, wherein said input is a keyboard.
50. The apparatus of claim 40, further comprising a first-in-first-out memory connected to said modulator that stores modulated data.
51. The system of claim 40, further comprising a housing, wherein said actigraph, scorer, said input, said data analyzer, said calculator, said first memory, and said modulator are within said housing.
52. The system of claim 51, further comprising a central data unit, and a transmitter connected with either said calculator or said modulator, said transmitter attached to said housing;
wherein said transmitter communicates with said central data unit.
53. The system of claim 52, wherein said central data unit stores and analyzes data collected from multiple actigraphs.
CA002349561A 1998-10-30 1999-09-03 System and method for predicting human cognitive performance using data from an actigraph Expired - Lifetime CA2349561C (en)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US10634498P 1998-10-30 1998-10-30
US12254199P 1999-03-02 1999-03-02
US60/106,344 1999-03-02
US60/122,541 1999-03-02
PCT/US1999/020104 WO2000026841A1 (en) 1998-10-30 1999-09-03 System and method for predicting human cognitive performance using data from an actigraph

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CA2349561A1 true CA2349561A1 (en) 2000-05-11
CA2349561C CA2349561C (en) 2009-11-10

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US (1) US6241686B1 (en)
EP (1) EP1125237B1 (en)
JP (1) JP4638041B2 (en)
AT (1) ATE302976T1 (en)
AU (1) AU758024B2 (en)
CA (1) CA2349561C (en)
DE (1) DE69926904T2 (en)
WO (1) WO2000026841A1 (en)

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DE69926904D1 (en) 2005-09-29
WO2000026841A1 (en) 2000-05-11
CA2349561C (en) 2009-11-10
EP1125237A1 (en) 2001-08-22
AU6134599A (en) 2000-05-22
US6241686B1 (en) 2001-06-05
EP1125237B1 (en) 2005-08-24
AU758024B2 (en) 2003-03-13
DE69926904T2 (en) 2006-06-22
JP2002529121A (en) 2002-09-10
JP4638041B2 (en) 2011-02-23
ATE302976T1 (en) 2005-09-15

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