US 8,620,419 B2Granted

Multi purpose criteria based adaptive training system

AssigneeLockheed Martin Corporation

InventorsEdward Rotenberg, Patrice D. Tremoulet, Randel A. Crowe, Ruthann Savage-King, Patrick Craven, Steven J. Tourville

Life of this patent

Estimating the term…

Abstract

A system and method include a computer implemented training framework that adapts its behavior to different types of training goals. The system utilizes a measured neuro-physiological state of a student to provide at least one of self regulation feedback and training environment feedback to optimize a learning experience for one or more different types of scenarios.

Claims17

Dependent claims

A sensor system comprising:

a sensor input to couple to an electroencephalograph sensor to detect a neuro-physiological state of a student;
a configurator input to receive information regarding training objective functions and to modify control algorithms and system parameters in accordance with a selected training objective function;
and
a controller coupled to the sensor input to implement the control algorithms and provide a communication if the student is outside a desired neuro-physiological state consistent with a desired learning zone and to provide a lesson intensity control signal as a function of the provided communication, sensed neuro-physiological state and selected training objective function;
a converter to convert the sensed neuro-physiological state of the student to cognitive parameters that are representative of cognitive workload, level of engagement, and alertness and wherein the lesson intensity is regulated using proportional integral control as a function of workload calculated from the sensed neuro-physiological state;
wherein the controller calculates the cognitive workload as a function of the amplitudes of the electroencephalograph signal at multiple electroencephalograph signal frequencies;
and
wherein the electroencephalograph signal frequencies include:
α corresponding to a range 8-12 Hz, β corresponding to a range of 12-30 Hz, γ corresponding to a range of 30-100 Hz, θ corresponding to a range of 4-7 Hz and δ corresponding to a range 0-4 Hz, and wherein the controller is configured to calculate workload, W(t), at time, t, according to the following formula:
W
⁡
(
t
-
n
)
=
k
1
⁢
α
⁡
(
t
-
n
)
+
k
2
⁢
β
⁡
(
t
-
n
)
+
k
3
⁢
γ
⁡
(
t
-
n
)
+
k
4
⁢
θ
⁡
(
t
-
n
)
+
k
4
⁢
δ
⁡
(
t
-
n
)
+
k
5
⁢
α
⁡
(
t
-
n
)
θ
⁡
(
t
-
n
)
+
k
6
⁢
γ
⁡
(
t
-
n
)
α
⁡
(
t
)
,
n
=
0
,
1
,
2
,
…
⁢
⁢
m
⁢
W
⁡
(
t
)
=
∑
i
=
0
m
⁢
r
i
⁢
W
⁡
(
t
-
i
)
where ki are conversion coefficients for different frequencies α(t), β(t), γ(t), θ(t), δ(t) and ri are coefficients.

139 more elements

A system comprising:

a sensor input to receive biosignals representative of a neuro-physiological state of a student;
a converter coupled to the sensor input to receive the biosignals and to convert the biosignals to learning zone digital values;
a training environment for the student responsive to lesson intensity values;
a configurator to receive input regarding training objective functions and to modify control algorithms in accordance with the training objective functions;
and
a controller coupled to the converter to receive the learning zone digital values and to provide a communication to the student if the learning zone digital values are indicative of the student being outside a desired neuro-physiological state consistent with the control algorithms and to modify the training environment as a function of the control algorithms and sensed neuro-physiological state;
a converter to convert the sensed neuro-physiological state of the student to cognitive parameters that are representative of cognitive workload, level of engagement, and alertness and wherein the lesson intensity is regulated using proportional integral control as a function of workload calculated from the sensed neuro-physiological state;
wherein the controller calculates the cognitive workload as a function of amplitudes of the electroencephalograph signal at multiple electroencephalograph signal frequencies;
and
wherein the electroencephalograph signal frequencies include:
α corresponding to a range 8-12 Hz, β corresponding to a range of 12-30 Hz, γ corresponding to a range of 30-100 Hz, θ corresponding to a range of 4-7 Hz and δ corresponding to a range 0-4 Hz, and wherein the controller is configured to calculate workload, W(t), at a time, t, according to the following formula:
W
⁡
(
t
-
n
)
=
k
1
⁢
α
⁡
(
t
-
n
)
+
k
2
⁢
β
⁡
(
t
-
n
)
+
k
3
⁢
γ
⁡
(
t
-
n
)
+
k
4
⁢
θ
⁡
(
t
-
n
)
+
k
4
⁢
δ
⁡
(
t
-
n
)
+
k
5
⁢
α
⁡
(
t
-
n
)
θ
⁡
(
t
-
n
)
+
k
6
⁢
γ
⁡
(
t
-
n
)
α
⁡
(
t
)
,
n
=
0
,
1
,
2
,
…
⁢
⁢
m
⁢
W
⁡
(
t
)
=
∑
i
=
0
m
⁢
r
i
⁢
W
⁡
(
t
-
i
)
where ki are conversion coefficients for different frequencies α(t), β(t), γ(t), θ(t), δ(t) and ri are coefficients.

141 more elements

Dependencies are inferred from the claim text.

Facts

Application: 12/558,164Filed 11 Sep 2009
Published: US 2011/0066005 A117 Mar 2011
Granted: 31 Dec 2013
Term ends: Not estimatedThe source records don’t support an estimate.

Classification8 codes

A61B 5/16
Measuring for diagnostic purposes ; Identification of persons: devices for psychotechnics ; Testing reaction times ; Devices for evaluating the…
A61B 5/02405
Measuring pulse rate or heart rate: determining heart rate variability
A61B 5/165
Devices for psychotechnics ; Testing reaction times ; Devices for evaluating the psychological state: evaluating the state of mind, e.g.…
A61B 5/4076
Detecting, measuring or recording for evaluating the nervous system: diagnosing or monitoring particular conditions of the nervous system

Family

US 2011/0066005 A1Pre-grant publication · published 17 Mar 2011
US 8,620,419 B2This patent

From the US filing history. Foreign family members aren’t listed.

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Abstract

A sensor system comprising:

a sensor input to couple to an electroencephalograph sensor to detect a neuro-physiological state of a student;
a configurator input to receive information regarding training objective functions and to modify control algorithms and system parameters in accordance with a selected training objective function;
and
a controller coupled to the sensor input to implement the control algorithms and provide a communication if the student is outside a desired neuro-physiological state consistent with a desired learning zone and to provide a lesson intensity control signal as a function of the provided communication, sensed neuro-physiological state and selected training objective function;
a converter to convert the sensed neuro-physiological state of the student to cognitive parameters that are representative of cognitive workload, level of engagement, and alertness and wherein the lesson intensity is regulated using proportional integral control as a function of workload calculated from the sensed neuro-physiological state;
wherein the controller calculates the cognitive workload as a function of the amplitudes of the electroencephalograph signal at multiple electroencephalograph signal frequencies;
and
wherein the electroencephalograph signal frequencies include:
α corresponding to a range 8-12 Hz, β corresponding to a range of 12-30 Hz, γ corresponding to a range of 30-100 Hz, θ corresponding to a range of 4-7 Hz and δ corresponding to a range 0-4 Hz, and wherein the controller is configured to calculate workload, W(t), at time, t, according to the following formula:
W
⁡
(
t
-
n
)
=
k
1
⁢
α
⁡
(
t
-
n
)
+
k
2
⁢
β
⁡
(
t
-
n
)
+
k
3
⁢
γ
⁡
(
t
-
n
)
+
k
4
⁢
θ
⁡
(
t
-
n
)
+
k
4
⁢
δ
⁡
(
t
-
n
)
+
k
5
⁢
α
⁡
(
t
-
n
)
θ
⁡
(
t
-
n
)
+
k
6
⁢
γ
⁡
(
t
-
n
)
α
⁡
(
t
)
,
n
=
0
,
1
,
2
,
…
⁢
⁢
m
⁢
W
⁡
(
t
)
=
∑
i
=
0
m
⁢
r
i
⁢
W
⁡
(
t
-
i
)
where ki are conversion coefficients for different frequencies α(t), β(t), γ(t), θ(t), δ(t) and ri are coefficients.

139 more elements

Facts

Application

12/558,164Filed 11 Sep 2009

Published

US 2011/0066005 A117 Mar 2011

Granted

31 Dec 2013

Term ends

Not estimatedThe source records don’t support an estimate.

Classification8 codes

A61B 5/16
Measuring for diagnostic purposes ; Identification of persons: devices for psychotechnics ; Testing reaction times ; Devices for evaluating the…
A61B 5/02405
Measuring pulse rate or heart rate: determining heart rate variability
A61B 5/165
Devices for psychotechnics ; Testing reaction times ; Devices for evaluating the psychological state: evaluating the state of mind, e.g.…
A61B 5/4076
Detecting, measuring or recording for evaluating the nervous system: diagnosing or monitoring particular conditions of the nervous system