Method and device for monitoring an analyte concentration in the living body of a human or animal
View Patent ↗The present invention generally relates to a method and a device for monitoring an analyte concentration in the living body of a human or animal. In particular to a method and device for determining analyte values y(t n ) correlating with the concentration to be determined are determined for consecutive points in time t n . The analyte values y(t n ) is used to predict a prediction value for an analyte y(t n0 +Δt) over a prediction period Δt.
1. A method for continuous monitoring of an analyte concentration in the living body of a human or animal, the method comprising:
determining an analyte values y(t n ) correlating with the concentration of the analyte for consecutive points in time t n ;
calculating a prediction value y(t n0 +Δt) over a prediction period Δt based on the analyte value y(t n ) using the following equation:
y ( t n0 +Δt )= F ( t n0 , t n0−Δn , . . . , t (n0−(m−2)Δn) , t (n0−(m−1)Δn) ); and
generating a warning signal if the prediction value y(t n0 +Δt) deviates from a predetermined value by more than a threshold value,
wherein function F(t k , t k−Δn , t k−2Δn , . . . , t k−(m−2)Δn , t k−(m−1)Δn ) depends on the analyte values y(t k ), y(t k−Δn ), y(t k−2Δn ), . . . , y(t k−(m−2)Δn ), y(t k−(m−1)Δn ) and the function F is used to approximate the progression of the analyte values y(t n ) at time t n0 in vicinity U of an analyte value y(t n0 ) with a pre-determined accuracy σ, such that
σ
2
≥
∑
t
k
∈
U
[
y
(
t
k
)
-
F
(
t
k
-
Δ
t
,
t
k
-
Δ
n
-
Δ
t
,
t
k
-
2
Δ
n
-
Δ
t
,
…
t
(
k
-
(
m
-
2
)
Δ
n
)
-
Δ
t
,
t
(
k
-
(
m
-
1
)
Δ
n
)
-
Δ
t
)
]
2
whereby n 0 , m, and Δn are integers.
2. The method according to claim 1 , wherein the function F depends not only on analyte values y(t k ), y(t k−Δn ), y(t k−2Δn ), . . . , y(t k−(m−2)Δn ), y(t k−(m−1)Δn ), but in addition on their first time derivatives.
3. The method according to claim 1 , wherein the function F depends not only on analyte values y(t k ), y(t k−Δn ), y(t k−2Δn ), . . . , y(t k−(m−2)Δn ), y(t k−(m−1)Δn ), but in addition on their first and second time derivatives.
4. The method according to claim 1 , wherein the function F contains linear or square terms.
5. The method according to claim 1 , wherein the function F is a linear function.
6. The method according to claim 1 , wherein the function F can be represented by coefficients a 0 to a m as follows:
F
=
a
0
+
∑
j
=
1
m
y
(
t
(
k
-
(
m
-
j
)
Δ
n
)
)
a
j
.
7. The method according to claim 6 , wherein the coefficients, a 0 to a m , are determined by minimizing the sum
∑
t
k
∈
U
[
y
(
t
k
)
-
a
0
-
∑
i
=
1
m
y
(
t
(
k
-
(
m
-
i
)
Δ
n
)
-
Δ
t
)
a
i
]
.
8. The method according to claim 6 , wherein the coefficients, a 0 to a m , are determined by solving a system of linear equations which contains one equation each of the type
y
(
t
k
)
=
a
0
+
∑
j
=
1
m
y
(
t
(
k
-
(
m
-
j
)
Δ
n
)
-
Δ
t
)
a
j
for at least m+1 different analyte values y(t k ) from the vicinity U of the point in time t n0 .
9. The method according to claim 8 , wherein the system of equations contains more than m+1 equations and is solved numerically by approximation to determine the coefficients, a 0 to a m .
10. The method according to claim 1 , wherein the analyte values y(t n ) used to determine the function F are obtained by numerical processing, in particular by filtering, of measured values.
11. The method according to claim 1 , wherein the analyte values y(t n ) used to calculate the prediction value are determined from consecutive points in time t n which are separated by intervals of 30 seconds to 5 minutes, preferably by 1 to 3 minutes.
12. The method according to claim 1 , wherein the analyte values y(t n ) used to calculate the prediction value or one of the prediction values are determined for times t n which are separated by an interval corresponding to the prediction period Δt.
13. The method according to claim 1 , wherein the number of the coefficients, a 0 to a m , is 4 to 11, preferably 6 to 9.
14. The method according to claim 1 , wherein the function F is determined as a function of transformed coordinate values Ty(t k ), Ty(t k−Δn ), Ty(t k−2Δn ), . . . , Ty(t k−(m−2)Δn ), Ty(t k−(m−1)Δn ), which were determined by means of a transformation, preferably a linear transformation, from analyte values y(t k ), y(t k−Δn ), y(t k−2Δn ), . . . , y(t k−(m−2)Δn ), y(t k−(m−1)Δn ), whereby the transformation is selected such that at least one of the values Ty(t k ), Ty(t k−Δn ), Ty(t k−2Δn ), . . . , Ty(t k−(m−2)Δn ), Ty(t k−(m−1)Δn ) has a negligible influence on the function F at the predetermined accuracy σ.
15. A method for continuous monitoring of an analyte concentration in the living body of a human or animal, the method comprising:
determining an analyte values y(t n ) correlating with the concentration of the analyte for consecutive points in time t n ;
calculating a prediction value y(t n0 +Δt) over a prediction period Δt based on the analyte value y(t n ) using the following equation:
y ( t n0 +Δt )= F ( t n0 , t n0−Δn , . . . , t (n0−(m−2)Δn) , t (n0−(m−1)Δn) )
generating a warning signal if the prediction value y(t n0 +Δt) deviates from a predetermined value by more than a threshold value,
wherein function F(t k , t k−Δn , t k−2Δn , . . . t k−(m−2)Δn , t k−(m−1)Δn ) depends on the analyte values y(t k ), y(t k−Δn ), y(t k−2Δn ), . . . , y(t k−(m−2Δn ), y(t k−(m−1)Δn ); and
adapting the function F(t k , t k−Δn , t k−2Δn , . . . , t k−(m−2)Δn , t k−(m−1)Δn ) in a vicinity U of an analyte value y(t n0 +Δt) at a point in time t n =t n0 +Δt for a calculated prediction value y(t n0 +Δt), such that the adapted function F approximates the progression of analyte values y(t n ) in the vicinity U with a predetermined accuracy and an additional prediction value y(t n0 +2Δt) is calculated therefrom,
whereby n 0 , m, and Δn are integers.