Method and device for predicting physiological values
The invention relates generally to methods, systems, and devices for measuring the concentration of target analytes present in a biological system using a series of measurements obtained from a monitoring system and a Mixtures of Experts (MOE) algorithm. In one embodiment, the present invention describes a method for measuring blood glucose in a subject.
1. A method to measure an amount of concentration or analyte present in a biological system, comprising:
determining a calibration ratio (CalRatio) value, wherein
CalRatio
=
BG
cp
(
active
cp
+
offset
)
where BG cp is a blood glucose concentration at the calibration point, active cp is an active signal that corresponds to an electrochemical sensor signal at the calibration point, and offset is a value that takes into account a non-zero y-intercept value;
providing two or more ranges of CalRatio values;
identifying the range in which said determined CalRatio value falls;
employing an algorithm for prediction of further measurement values selected from one of a first algorithm and a second: algorithm, the first algorithm comprising:
BG=w 1 BG 1 +w 2 BG 2 +w 3 BG 3 |
where
BG 1 =p 1 (time)+ q 1 (active)+ r 1 (signal)+ s 1 (BG|cp)+ t 1
BG 2 =p 2 (time)+ q 2 (active)+ r 2 (signal)+ s 2 (BG|cp)+ t 2
BG 3 =p 3 (time)+ q 3 (active)+ r 3 (signal)+ s 3 (BG|cp)+ t 3
w
1
=
ⅇ
d
1
ⅇ
d
1
+
ⅇ
d
2
+
ⅇ
d
3
w
2
=
ⅇ
d
2
ⅇ
d
1
+
ⅇ
d
2
+
ⅇ
d
3
w
3
=
ⅇ
d
3
ⅇ
d
1
+
ⅇ
d
2
+
ⅇ
d
3
d 1 =τ 1 (time)+β 1 (active)+γ 1 (signal)+δ 1 (BG|cp)+∈ 1
d 2 =τ 2 (time)+β 2 (active)+γ 2 (signal)+δ 2 (BG|cp)+∈ 2
d 3 =τ 3 (time)+β 3 (active)+γ 3 (signal)+δ 3 (BG|cp)+∈ 3
in which BG i is the analyte predicted, BG/cp is the blood glucose value at a calibration point, time is the elapsed time, active is the active signal, signal being the calibrated signal, p i , q i , r i are coefficients, t i is a constant, e indicates an exponential function, d i is a parameter set usable to determine weightings w i , with τ i , β i , γ i , δ i , and ∈ i are constants, and the second equation comprising:
BG=w 1 BG 1 +w 2 BG 2 +w 3 BG 3
where
BG
1
=
p
1
(
time
c
)
+
q
1
(
active
)
+
r
1
(
signal
)
+
s
1
(
BG
❘
cp
)
+
t
1
BG
2
=
p
2
(
time
c
)
+
q
2
(
active
)
+
r
2
(
signal
)
+
s
2
(
BG
❘
cp
)
+
t
2
BG
3
=
p
3
(
time
c
)
+
q
3
(
active
)
+
r
3
(
signal
)
+
s
3
(
BG
❘
cp
)
+
t
3
w
1
=
ⅇ
d
1
ⅇ
d
1
+
ⅇ
d
2
+
ⅇ
d
3
w
2
=
ⅇ
d
2
ⅇ
d
1
+
ⅇ
d
2
+
ⅇ
d
3
w
3
=
ⅇ
d
3
ⅇ
d
1
+
ⅇ
d
2
+
ⅇ
d
3
d 1 =τ 1 (time c )+β 1 (active)+γ 1 (signal)+δ 1 (BG|cp)+∈ 1
d 2 =τ 2 (time c )+β 2 (active)+γ 2 (signal)+δ 2 (BG|cp)+∈ 2
d 3 =τ 3 (time c )+β 3 (active)+γ 3 (signal)+δ 3 (BG|cp)+∈ 3
in which BG i is the analyte predicted, time c is the elapsed time since calibration, active is the active signal, signal is the calibrated signal, BG/cp is the blood glucose value at a calibration point, p i , q i , r i are coefficients, t i is a constant, e indicates an exponential function, d i is a parameter set usable to determine weightings w i , with τ i , β i , γ i , δ i , and ∈ i are constants, wherein said algorithm is optimized for performance in the identified range; and
generating further measurement values indicative of amount or concentration of analyte present in the biological system, said generating comprising obtaining a raw signal specifically related to analyte amount or concentration in the biological system and using said algorithm to correlate the raw signal with a measurement value.