US 10,896,739 B2Granted

Circadian phase estimation, modeling and control

AssigneeRensselaer Polytechnic Institute

InventorsJiaxiang Zhang, John T. Wen, Agung Julius

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Abstract

Method, system and computer program product are provided for estimating a circadian phase of a subject by: obtaining a sensed biological signal for the subject; and using, by one or more processors, adaptive frequency tracking to adaptively estimate the circadian phase of the subject from the sensed biological signal. Circadian phase estimation may be accelerated by providing a feedback loop for the adaptive frequency tracking, which utilizes, in part, a circadian phase model in automatically ascertaining a phase correction for the adaptive frequency tracking. The circadian phase estimation may be used in automatically constructing a light-based circadian rhythm model for the subject using a linear parameter-varying (LPV) formulation, and once constructed, the circadian rhythm model for the subject may be used to provide light-based circadian rhythm regulation.

Claims20

Dependent claims

A method comprising:

estimating a circadian phase of the subject using a circadian rhythm control system to facilitate regulating a subject's circadian rhythm, the estimating comprising:
obtaining a sensed biological signal for the subject;
using, by one or more processors, adaptive frequency tracking to adaptively estimate the circadian phase of the subject from the sensed biological signal;
and
the circadian rhythm control system initiating control of circadian light input to the subject based on the estimated circadian phase of the subject to regulate the subject's circadian rhythm,
wherein the adaptive frequency tracking utilizes an adaptive notch filter, and the measured biological signal obtained from the subject can be represented as a linear combination of N harmonics and a DC component:
n=d*+A1*sin(ω*t+ϕ1)+A2*sin(2ω*t+ϕ2)+ . . . +AN*sin(Nω*t+ϕN)
wherein internal variables of the adaptive frequency tracking converge to:
x
1
=
A
1
*
⁢
cos
⁡
(
ω
*
⁢
t
+
ϕ
1
)
2
⁢
⁢
ζ
x
2
=
A
1
*
⁢
ω
⁢
⁢
sin
⁡
(
ω
*
⁢
t
+
ϕ
1
)
2
⁢
⁢
ζ
x
3
=
-
A
2
*
⁢
cos
⁡
(
2
⁢
⁢
ω
*
⁢
t
+
ϕ
2
)
2
⁢
⁢
ζ
x
2
=
2
⁢
⁢
A
2
*
⁢
cos
⁡
(
2
⁢
⁢
ω
*
⁢
t
+
ϕ
2
)
2
⁢
⁢
ζ
⋮
x
2
⁢
N
-
1
=
-
A
N
*
⁢
cos
⁡
(
N
⁢
⁢
ω
*
⁢
t
+
ϕ
N
)
2
⁢
⁢
ζ
x
2
⁢
⁢
N
=
NA
N
*
⁢
ω
⁢
⁢
sin
⁡
(
N
⁢
⁢
ω
*
⁢
t
+
ϕ
N
)
2
⁢
⁢
ζ
d
=
d
*
,
ω
=
ω
*
and wherein the circadian phase of the subject comprises the phase of a fundamental harmonic defined as:
θ
=
tan
-
1
-
x
2
x
1
⁢
ω
where
n=input, i.e., the sensed biological signal;
θ=output, i.e., the circadian phase estimate;
x1, x2=state variables for the 1st order oscillator;
x3, x4=state variables for the 2nd order oscillator;
x2N−1, x2N=state variables for the Nth order oscillator;
d=estimated bias of the biological signal;
ω=estimated angular frequency of the circadian rhythm;
and
ζ=notch width of the filter.

200 more elements

A system comprising:

a circadian rhythm control system to facilitate regulating a subject's circadian rhythm, the circadian rhythm control system comprising one or more processors, which facilitate:
obtaining a sensed biological signal for the subject;
using, by the one or more processors, adaptive frequency tracking to adaptively estimate the circadian phase of the subject from the sensed biological signal;
and
the circadian rhythm control system initiating control of circadian light input to the subject based on the estimated circadian phase of the subject to regulate the subject's circadian rhythm,
wherein the adaptive frequency tracking utilizes an adaptive notch filter, and the measured biological signal obtained from the subject can be represented as a linear combination of N harmonics and a DC component:
n=d*+A1*sin(ω*t+ϕ1)+A2*sin(2ω*t+ϕ2)+ . . . +AN*sin(Nω*t+ϕN)
wherein internal variables of the adaptive frequency tracking converge to:
x
1
=
A
1
*
⁢
cos
⁡
(
ω
*
⁢
t
+
ϕ
1
)
2
⁢
⁢
ζ
x
2
=
A
1
*
⁢
ω
⁢
⁢
sin
⁡
(
ω
*
⁢
t
+
ϕ
1
)
2
⁢
⁢
ζ
x
3
=
-
A
2
*
⁢
cos
⁡
(
2
⁢
⁢
ω
*
⁢
t
+
ϕ
2
)
2
⁢
⁢
ζ
x
2
=
2
⁢
⁢
A
2
*
⁢
cos
⁡
(
2
⁢
⁢
ω
*
⁢
t
+
ϕ
2
)
2
⁢
⁢
ζ
⋮
x
2
⁢
N
-
1
=
-
A
N
*
⁢
cos
⁡
(
N
⁢
⁢
ω
*
⁢
t
+
ϕ
N
)
2
⁢
⁢
ζ
x
2
⁢
⁢
N
=
NA
N
*
⁢
ω
⁢
⁢
sin
⁡
(
N
⁢
⁢
ω
*
⁢
t
+
ϕ
N
)
2
⁢
⁢
ζ
d
=
d
*
,
ω
=
ω
*
and wherein the circadian phase of the subject comprises the phase of a fundamental harmonic defined as:
θ
=
tan
-
1
-
x
2
x
1
⁢
ω
where
n=input, i.e., the sensed biological signal;
θ=output, i.e., the circadian phase estimate;
x1, x2=state variables for the 1st order oscillator;
x3, x4=state variables for the 2nd order oscillator;
x2N-1, x2N=state variables for the Nth order oscillator;
d=estimated bias of the biological signal;
ω=estimated angular frequency of the circadian rhythm;
and
ζ=notch width of the filter.

200 more elements

A computer program product for adaptively estimating circadian phase of a subject, the computer program product comprising:

a non-transitory computer-readable storage medium readable by one or more processors and storing instructions for execution by the one or more processors for performing a method comprising:
obtaining a sensed biological signal for the subject;
using adaptive frequency tracking to adaptively estimate the circadian phase of the subject from the sensed biological signal;
and
initiating control of circadian light input to the subject based on the estimated circadian phase of the subject to regulate the subject's circadian rhythm,
wherein the adaptive frequency tracking utilizes an adaptive notch filter, and the measured biological signal obtained from the subject can be represented as a linear combination of N harmonics and a DC component:
n=d*+A1*sin(ω*t+ϕ1)+A2*sin(2ω*t+ϕ2)+ . . . +AN*sin(Nω*t+ϕN)
wherein internal variables of the adaptive frequency tracking converge to:
x
1
=
A
1
*
⁢
cos
⁡
(
ω
*
⁢
t
+
ϕ
1
)
2
⁢
⁢
ζ
x
2
=
A
1
*
⁢
ω
⁢
⁢
sin
⁡
(
ω
*
⁢
t
+
ϕ
1
)
2
⁢
⁢
ζ
x
3
=
-
A
2
*
⁢
cos
⁡
(
2
⁢
⁢
ω
*
⁢
t
+
ϕ
2
)
2
⁢
⁢
ζ
x
2
=
2
⁢
⁢
A
2
*
⁢
cos
⁡
(
2
⁢
⁢
ω
*
⁢
t
+
ϕ
2
)
2
⁢
⁢
ζ
⋮
x
2
⁢
N
-
1
=
-
A
N
*
⁢
cos
⁡
(
N
⁢
⁢
ω
*
⁢
t
+
ϕ
N
)
2
⁢
⁢
ζ
x
2
⁢
⁢
N
=
NA
N
*
⁢
ω
⁢
⁢
sin
⁡
(
N
⁢
⁢
ω
*
⁢
t
+
ϕ
N
)
2
⁢
⁢
ζ
d
=
d
*
,
ω
=
ω
*
and wherein the circadian phase of the subject comprises the phase of a fundamental harmonic defined as:
θ
=
tan
-
1
-
x
2
x
1
⁢
ω
where
n=input, i.e., the sensed biological signal;
θ=output, i.e., the circadian phase estimate;
x1, x2=state variables for the 1st order oscillator;
x3, x4=state variables for the 2nd order oscillator;
x2N-1, x2N=state variables for the Nth order oscillator;
d=estimated bias of the biological signal;
ω=estimated angular frequency of the circadian rhythm;
and
ζ=notch width of the filter.

200 more elements

Dependencies are inferred from the claim text.

Facts

Application: 16/689,283Filed 20 Nov 2019 · continuation
Priority: 5 Jun 2012
Published: US 2020/0090781 A119 Mar 2020
Granted: 19 Jan 2021
Term ends: Not estimatedThe source records don’t support an estimate.

Classification13 codes

G16H 50/50
ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or…: for…
A61B 5/4857
Other medical applications: indicating the phase of biorhythm
A61N 5/0618
Apparatus adapted for a specific treatment: psychological treatment
G06N 7/02
Computing arrangements based on specific mathematical models: using fuzzy logic

Family

Application61/689,391Us provisional application · filed 5 Jun 2012
PCT/US2013/044007Parent of this continuation · filed 4 Jun 2013
US 2020/0090781 A1Pre-grant publication · published 19 Mar 2020
Application14/405,973Parent of this continuation
US 10,529,440 B2Parent of this continuation
US 2015/0186594 A1Published application
US 10,896,739 B2This patent

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