HK1129290B - Temperature-adjusted analyte determination for biosensor systems - Google Patents

Description

Temperature regulated analyte determination for biosensor systems

Background

Biosensor systems typically provide analysis for one or more analytes in a biological fluid. Such analysis typically includes quantitative determination of analytes in biological fluids. This analysis is used to diagnose and treat physiological abnormalities. For example, for diabetics who frequently check blood glucose levels to regulate diet and/or medication, it is important to determine the glucose level in the blood. For others, monitoring of uric acid, lactate, cholesterol, bilirubin, and the like may be important.

Biosensor systems may be implemented using desktop, portable, and other measurement devices. The portable device may be hand-held and typically includes a measurement device and a sensor strip. Typically, a biological fluid sample is introduced into a sensor strip disposed in a measurement device for analysis. Biosensor systems may be designed to analyze one or more analytes, and may use different amounts of biological fluids. Some biosensor systems can analyze one drop of Whole Blood (WB), for example, 1-15 microliters (μ L) in volume.

Biosensor systems typically measure an output signal to determine the analyte concentration in a biological fluid sample. The output signal is generated by an oxidation/reduction reaction or a redox reaction of the analyte. An enzyme or similar substance may be added to the sample to enhance the redox reaction. The output signal may be an electrical signal, light, or light converted to an electrical signal. The biosensor system may use an optical sensor system or an electrochemical sensor system to generate the output signal.

In an optical system, the analyte concentration can be determined by measuring the light that has interacted with a light-distinguishable substance, such as an analyte or a reactant or a product formed by the reaction of a chemical indicator with an analyte redox reactant. An incident excitation beam from a light source is directed to the sample. The optically distinguishable substance absorbs or shifts a portion of the wavelength of the incident light beam, thereby changing the wavelength of the incident light beam or reducing the intensity of the incident light beam. The detector collects and measures the attenuated or wavelength-altered incident light beam (i.e., the output signal). In other optical systems, the chemical indicator fluoresces or emits light in response to an analyte redox reaction when it is illuminated by an excitation beam. The detector collects and measures this light (i.e., the output signal).

In electrochemical systems, analyte concentration is determined by measuring an electrical signal, such as current or potential. Typically, the analyte undergoes a redox reaction when an excitation signal is applied to the sample. The excitation signal is typically an electrical signal such as a current or potential. The redox reaction generates an output signal in response to the excitation signal. The output signal is typically an electrical signal, such as a current or potential, which can be measured and correlated to the analyte concentration.

In electrochemical systems, the measuring device typically has electrical contacts that are connected to electrical conductors in the sensor strip. The electrical connectors are connected to electrodes extending into the biological fluid sample through the conductors. The measurement device applies an excitation signal to an electrical conductor through an electrical junction, which delivers the excitation signal to the sample through the electrode. In response to the excitation signal, a redox reaction of the analyte generates an output signal. The measurement device determines an analyte concentration in response to the output signal. Toilet bowlExamples of portable measuring devices include: ascensia Breeze available from Bayer CorporationAnd EliteA measuring instrument; precision available from Abbott, Park, IllinoisA biosensor; accucheck available from Roche of Indianapolis, IndianaA biosensor; and OneTouch Ultra available from Lifescan, Milpitas, CaliforniaA biosensor. Examples of bench-top measuring devices include: BAS 100B Analyzer available from BAS instruments, West Lafayette, Indiana; CH Instruments electrochemical workbench available from CH Instruments of Austin, Texas; cypress electrochemical workbench available from Cypress Systems of Lawrence, Kansas; and EG available from Princeton research Instruments of Princeton, N.J.&G electrochemical instrument.

The sensor strip may include a reagent that reacts with an analyte in the biological fluid sample. These reagents include an ionizing agent for promoting redox of the analyte, as well as any mediator or other substance that facilitates electron transfer between the analyte and the conductor. The ionizing agent may be an analyte-specific enzyme such as glucose oxidase or glucose dehydrogenase to catalyze the oxidation of glucose in the WB sample. These reagents may include a binder that binds the enzyme to the mediator. In the optical system, these reagents include a chemical indicator and another enzyme or similar substance to enhance the reaction of the chemical indicator with the analyte or redox reaction product of the analyte.

Most biosensor systems use correlation equations or calibration equations to determine the analyte concentration in the biological fluid sample. The correlation equation represents the relationship between the output signal and the analyte concentration. From each correlation equation, the analyte concentration for a particular output signal can be calculated. The correlation equation depends on the sample temperature. The output signal for a particular analyte concentration may vary due to the effects of temperature on the analyte redox reaction, enzyme kinetics, diffusion, and the like. In order to calculate the analyte concentration from the output signal at a particular sample temperature, a correlation equation is required for each possible sample temperature.

To reduce the number of correlation equations used in sample analysis, many biosensor systems attempt to use one or more correlation equations to provide an analyte concentration at a particular reference temperature. The analyte concentration at the sample temperature is typically compensated by the difference between the sample temperature and the reference temperature to provide the analyte concentration at the reference temperature.

Some biosensor systems perform temperature compensation by varying the output signal prior to calculating the analyte concentration using a correlation equation. The output signal is typically multiplied by a temperature correction coefficient or the like. The temperature corrected output signal is used to determine the analyte concentration. Biosensor systems using temperature corrected output signals are described in U.S. patent nos. 4,750,496 and 6,576,117.

Other biosensor systems are temperature compensated by varying the analyte concentration calculated from the correlation equation. The analyte concentration calculated from the correlation equation is typically subjected to a temperature correction procedure to provide a temperature corrected analyte concentration. Biosensor systems using temperature-corrected analyte concentrations are described in U.S. patent nos. 5,366,609, 5,508,171, and 6,391,645.

There are also biosensor systems that are temperature compensated by varying the output signal prior to calculating the analyte concentration using the correlation equation and/or by varying the analyte concentration calculated by the correlation equation. Biosensor systems that use temperature-corrected output signals and/or temperature-corrected analyte concentrations are described in U.S. Pat. Nos. 4,431,004 and 5,395,504.

Although these temperature compensation methods trade off various advantages and disadvantages, they are not ideal enough. These methods do not fully combine the effects of different sample temperatures on the analyte redox reaction, the kinetics and diffusion of the enzyme and mediator. These methods do not adequately address the effects of different analyte concentrations on enzyme kinetics and diffusion at different sample temperatures. These methods also do not adequately address the effects of different analyte concentrations on redox reactions at different sample temperatures. In addition, changes in the output signal and/or the calculated analyte concentration may introduce or amplify errors associated with determining the analyte concentration from the output signal.

Accordingly, there is a continuing need for improved biosensor systems, particularly those that provide improved accuracy and precision of analyte concentrations at a reference temperature. The systems, devices, and methods of the present invention overcome at least one of the disadvantages associated with conventional biosensor systems.

Disclosure of Invention

The present invention provides a biosensor system that determines the concentration of an analyte in a biological fluid sample from an output signal generated by an analyte redox reaction. The biosensor system adjusts the correlation between the analyte concentration and the output signal at a reference temperature to determine the analyte concentration from the output signal at other temperatures. The biosensor system uses the temperature-adjusted correlation to determine an analyte concentration from an output signal at a sample temperature.

In a method for determining the concentration of an analyte in a sample of a biological fluid, the temperature of the sample is determined. The output signal is generated in response to a redox reaction of an analyte in the sample. Adjusting a reference temperature lower score in response to temperatureCorrelation between analyte concentration and output signal. Determining an analyte concentration from the temperature-adjusted correlation and the output signal at the sample temperature. Wherein the temperature-modulated correlation between analyte concentration and output signal is represented as follows:wherein A is_RFor analyte concentration at a reference temperature, OS_TIs the output signal at the temperature of the sample, Int_TFor the intercept adjusted by a normalized temperature function of the intercept, and S_TIs the slope adjusted by a normalized temperature function of the slope.

In a method for adjusting a correlation between an analyte concentration and an output signal at a reference temperature in response to a temperature, the correlation between the analyte concentration and the output signal is determined for the reference temperature and at least one other temperature. A normalized temperature function of a slope and an intercept of the correlation of the reference temperature is established. Adjusting the correlation of the reference temperature in response to a normalized temperature function of the slope and intercept.

A biosensor for determining the concentration of an analyte in a biological fluid includes a measurement device and a sensor strip. The measurement device has a processor connected to a sensor interface and a temperature sensor. The sensor strip has a sample interface located on a substrate. The sample interface is adjacent to a reservoir formed by the substrate. The processor adjusts a correlation between analyte concentration and output signal at a reference temperature in response to a sample temperature from the temperature sensor. The processor determines an analyte concentration from the temperature-adjusted correlation in response to an output signal from the sample interface.

Certain definitions are set forth below to provide a clearer and more consistent understanding of the specification and claims.

An "analyte" is defined as one or more substances present in a sample. The assay will determine the presence and/or concentration of the analyte present in the sample.

A "sample" is defined as a composition that may contain an unknown amount of analyte. Typically, the sample for electrochemical analysis is in liquid form, and preferably, the sample is an aqueous mixture. The sample may be a biological sample such as blood, urine or saliva. The sample may also be a derivative of a biological sample, such as an extract, a dilution, a filtrate or a reconstituted precipitate.

A "conductor" is defined as a conductive substance that remains stationary during an electrochemical analysis.

"accuracy" is defined as the closeness of the amount of analyte measured by the sensor system to the true amount of analyte in the sample. Accuracy can be expressed as a deviation of an analyte reading of the sensor system from a reference analyte reading. Larger deviation values reflect less accuracy.

"accuracy" is defined as the proximity of multiple analyte measurements to the same sample. Accuracy can be expressed as spread (spread) or variance between measurements.

A "redox reaction" is defined as a chemical reaction between two substances involving the transfer of at least one electron from a first substance to a second substance. Thus, redox reactions include oxidation and reduction. The oxidation half-cell reaction involves the loss of at least one electron from a first species, while the reduction half-cell reaction involves the addition of at least one electron from a second species. The ionic charge of the oxidized species increases by a value equal to the number of electrons lost. Also, the ionic charge reduction value of the reduced species is equal to the number of electrons obtained.

A "mediator" is defined as a substance that can be oxidized or reduced and that can transfer one or more electrons. Mediators are reagents in an electrochemical assay that are not target analytes, but rather provide indirect measurements of the analyte. In a simplified system, the mediator undergoes a redox reaction in response to oxidation or reduction of the analyte. The oxidized or reduced mediator then undergoes a relative reaction at the working electrode of the sensor strip, returning to its original oxidation number.

An "adhesive" is defined as a material that provides physical support to and holds an agent while being chemically compatible with the agent.

"steady state" is defined as the state when the signal is substantially constant (e.g., varies within 10% or 5%) with respect to changes in its independent input variables (time, etc.).

A "transient point" is defined as the value of the signal obtained as a function of time as an increasing diffusion rate transitions to a relatively constant diffusion rate. Before the transient point, the signal changes rapidly with time. Similarly, after the transient point, the rate of signal decay becomes relatively constant, reflecting a relatively constant rate of diffusion.

A "handheld device" is defined as a device that can be held in a human hand and is portable. An example of a handheld device is Ascensia available from Bayer HealthCare, LLC, Elkhart, INThe Elite blood glucose monitoring system is provided with a measuring device.

Drawings

The invention can be better understood with reference to the following drawings and description. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. Moreover, in the figures, corresponding parts are designated by the same reference numerals throughout the different views.

FIG. 1 shows a method for determining the concentration of an analyte in a biological fluid sample.

FIG. 2 illustrates a method for adjusting the correlation between analyte concentration and output signal at a reference temperature in response to sample temperature.

Fig. 3 is a graph illustrating the correlation between analyte concentration and output signal.

FIG. 4 is a graph illustrating the normalized slope of the correlation between glucose concentration in whole blood and current at 7 second detection time as a function of temperature.

FIG. 5 is a graph illustrating the normalized intercept of the correlation between glucose concentration in whole blood and current at 7 second detection time as a function of temperature.

FIG. 6 is a graph illustrating the normalized slope of the correlation between glucose concentration in whole blood and current for several test times as a function of temperature.

FIG. 7 is a graph illustrating the normalized intercept of the correlation between glucose concentration in whole blood and current for several test times as a function of temperature.

Fig. 8 is a graph illustrating the deviation of the calculated glucose concentration from the reference temperature without any temperature adjustment.

Fig. 9 is a graph illustrating the deviation of the calculated glucose concentration from the reference temperature with temperature adjustment.

FIG. 10 is a graph illustrating a temperature function of current from a glucose sensor with normalized slope and intercept.

Fig. 11 is a graph illustrating a temperature coefficient function of the normalized current of fig. 10 as a function of temperature.

FIG. 12 is a schematic diagram of a biosensor for determining the concentration of an analyte in a biological fluid sample.

Detailed Description

A biosensor system for determining an analyte in a biological fluid sample is described. The biosensor system determines the analyte concentration from the output signal generated by the oxidation/reduction or redox reaction of the analyte. The system adjusts a correlation equation for determining analyte concentration from output signals at one temperature, and thus determines analyte concentration from output signals at other temperatures (e.g., sample temperature). This correlation of temperature adjustment improves the accuracy and precision of the biosensor system in determining the analyte concentration of a sample. The biosensor system can determine the analyte concentration from the output signal at the sample temperature using a temperature-adjusted correlation equation for the reference temperature. The equation of correlation between analyte concentration and output signal can be represented graphically, mathematically, or a combination thereof. The correlation equation may be represented by a Program Number Assignment (PNA) table, another look-up table, etc. The biosensor system may be used to determine analyte concentrations such as glucose, uric acid, lactate, cholesterol, bilirubin, and the like.

FIG. 1 shows a method for determining the concentration of an analyte in a biological fluid sample. At 102, the sample temperature is measured. At 104, an output signal is generated in response to an oxidation/reduction reaction of the analyte in the sample. In 106, a correlation between the analyte concentration and the output signal at a reference temperature is adjusted in response to the temperature. At 108, the analyte concentration is determined from the correlation of the temperature adjustment and the output signal at the sample temperature. At 110, the analyte concentration is displayed and may be stored for future reference.

In 102 of FIG. 1, various techniques may be used to determine the sample temperature. The sample temperature may be measured using a thermistor, thermometer, or other temperature sensing device. The sample temperature may be calculated from the output signal of the electrochemical reaction in the sample. It may be assumed that the sample temperature is the same or similar to the ambient temperature or the temperature of the device implementing the biosensor system. Other techniques may be used to determine the sample temperature.

At 104 in fig. 1, an output signal is generated in response to an oxidation/reduction or redox reaction of an analyte in a sample. Optical sensor systems, electrochemical sensor systems, and the like may be used to generate the output signal.

Optical sensor systems typically measure the amount of light absorbed or produced by the reaction of a chemical indicator with an analyte redox reactant. Enzymes may be included in the chemical indicator to enhance reaction kinetics. The output signal or light of the optical system may be converted into an electrical signal such as a current or potential.

In light-absorbing optical systems, chemical indicators produce light-absorbing reaction products. Chemical indicators such as tetrazolium salts may be used in conjunction with enzymes such as diaphorase. Tetrazolium salts typically generate formazan (a chromogen) in response to the redox reaction of the analyte. An incident excitation beam from a light source is directed to the sample. The light source may be a laser, a light emitting diode, or the like. The incident light beam may have a wavelength selected to facilitate absorption by the reaction products. When an incident light beam passes through the sample, the reaction products absorb a portion of the incident light beam, thereby attenuating or reducing the intensity of the incident light beam. The incident beam may be reflected back from the sample to the detector or transmitted through the sample to the detector. The detector collects and measures the attenuated incident beam (output signal). The amount of light attenuated by the reaction product is indicative of the concentration of analyte in the sample.

In optical systems that generate light, the chemical indicator fluoresces or emits light in response to an analyte redox reaction. The detector collects and measures the light generated (output signal). The amount of light generated by the chemical indicator is indicative of the concentration of the analyte in the sample.

The electrochemical system applies an input signal to the biological fluid sample. The input signal may be a potential or a current and may be constant, varying, or a combination thereof, for example when an AC signal with a DC signal offset is applied. The input signal may be applied in the form of a single or multiple pulses, a sequence or a cycle. The analyte will undergo a redox reaction when an input signal is applied to the sample. Enzymes or the like may be used to enhance the redox reaction of the analyte. Mediators can be used to maintain the oxidation state of the enzyme. The redox reaction produces an output signal that can be measured continuously or periodically during transient output and/or steady state output. Various electrochemical methods can be used, such as amperometry, coulometry, voltammetry, and the like. Gated amperometry and gated voltammetry may also be used.

In amperometry, a potential or voltage is applied to the biological fluid sample. The redox reaction of the analyte generates an electrical current in response to the electrical potential. The current is measured over time to quantify the analyte in the sample. Amperometry typically measures the rate at which an analyte is oxidized or reduced to determine the concentration of the analyte in a sample. Biosensor systems using amperometry are described in U.S. patent nos. 5,620,579, 5,653,863, 6,153,069 and 6,413,411.

In coulometry, a potential is applied to a sample of biological fluid to thoroughly oxidize or reduce the analyte within the sample. The potential generates a current that is integrated over the oxidation/reduction time, thereby generating a charge that is representative of the analyte concentration. Coulometry typically yields the total amount of analyte within a sample. A biosensor system using coulometry for whole blood glucose measurement is described in U.S. patent No.6,120,676.

In voltammetry, a varying potential is applied to a biological fluid sample. The redox reaction of the analyte generates an electrical current in response to the applied potential. The current is measured over time to quantify the analyte in the sample. Voltammetry typically measures the rate at which an analyte is oxidized or reduced to determine the concentration of the analyte in a sample. "electrochemical methods" available in 1980 at a.j.bard and l.r.faulkner: additional information on voltammetry is found in fundametals and Applications.

In gated amperometry and gated voltammetry, pulsed excitation was used, as described in U.S. provisional patent application No.60/700,787, filed on 7/20/2005 and U.S. provisional patent application No.60/722,584, filed on 9/30/2005, respectively, which are incorporated herein by reference.

In 106 of fig. 1, the correlation between analyte concentration and output signal at a reference temperature is adjusted in response to temperature. The correlation may be expressed as a correlation equation or a calibration equation that calculates the analyte concentration from the output signal at the reference temperature. The correlation equation for the reference temperature is adjusted to calculate the analyte concentration in response to the output signal at other temperatures (e.g., the sample temperature). The correlation equation is for a reference temperature of 25 ℃. Other correlation equations at the reference temperature may be used.

A correlation equation may be implemented to manipulate the output signal for determining the analyte concentration. The correlation equation may also be implemented as a Program Number Assignment (PNA) table of slopes and intercepts of the correlation equation, another look-up table, etc., for comparison with the electrical output signal to determine the analyte concentration.

The effect of temperature on the correlation equation or the correction equation is responsive to the diffusion and enzymatic reaction behavior during the redox reaction. For example, temperature affects the oxidation and diffusion of glucose in a whole blood sample. In addition, temperature affects the diffusion of photoactive molecules.

The correlation equation may be linear or nearly linear and may be described as a second order polynomial. In general form, the correlation equation can be expressed as follows:

OS＝d_n*Aⁿ+d_n-1*A^n-1+K+d₂*A²+d₁*A+d₀ (1)。

where A is the analyte concentration, OS is the output signal, and the coefficient d_n、d_n-1、d₂、d₁And d₀A temperature dependent weighting factor for each term of the biosensor response is described.

The correlation equation can be described by an inverse expression in which the analyte concentration is expressed as a function of the output signal. This reduces the need to solve the nth order equation to obtain the analyte concentration. Thus, the correlation equation for analyte concentration can be expressed as follows:

A＝c_n*OSⁿ+c_n-1*OS^n-1+K+c₂*OS²+c₁*OS+c₀ (2)。

wherein c is_n、c_n-1、c₂、c₁And c₀Is a coefficient of a temperature-dependent weighting factor that describes each term of the biosensor response. The analyte concentration a may be glucose in a whole blood sample. The output signal may be the current or potential of the electrochemical system, the absorbance or transmission percentage of the optical system, etc.

The correlation equation can be expressed as a second order response between analyte concentration and output signal as follows:

A＝c₂*OS²+c₁*OS+c₀ (3)。

the correlation equation can be expressed as a linear response between analyte concentration and output signal as follows:

A_R＝c₁*OS_T+c₀＝OS_T/S_T+Int_T/S_T (4)。

wherein c is₁＝1/S_T，c₀＝Int_T/S_TAnd wherein A is_RFor analyte concentration at a reference temperature, OS_TTo output a signal, S_TThe product of the slope at the reference temperature and a normalized temperature function of the slope, and Int_TIs the product of the intercept at the reference temperature and a normalized temperature function of the intercept.

Equation (4) can be rewritten as follows to represent the output signal in response to the analyte concentration:

OS_T＝S_T*A_R+Int_T (5)。

wherein the OS_TIs the output signal at another temperature, e.g. the sample temperature, A_RIs the analyte concentration at the reference temperature, S_TCan be expressed as a standard of constant and slopeProduct of change temperature function, and Int_TCan be expressed as the product of a constant and a normalized temperature function of the intercept.

According to the analyte concentration A_RLower temperature vs. slope S_TAnd intercept Int_TEquation (5) indicates the output signal OS_TAs a function of temperature. Slope S_TAnd intercept Int_TThe slope and intercept of the correlation equation at the reference temperature are adjusted using a normalized temperature function of the slope and intercept. The slope and intercept of the temperature adjustment for the correlation of the reference temperature can be used with the output signal at another temperature (e.g., the sample temperature) to calculate the analyte concentration.

Thus, the correlation equation (5) can be rewritten as follows to calculate the analyte concentration using the slope and intercept of the temperature adjustment of the correlation of the reference temperature and the output signal at another temperature:

wherein A is_RFor analyte concentration at a reference temperature, OS_TIs an output signal at another temperature, Int_TAn intercept of a dependence of a reference temperature adjusted by a normalized temperature function of the intercept in response to another temperature, and S_TIs the slope of the dependence of the reference temperature adjusted by a normalized temperature function of the slope in response to another temperature.

Adjusting the slope of the dependence of the reference temperature in response to the sample temperature as follows:

S_T＝S_R*f(T) (7)。

wherein S_RIs the slope of the dependence of the reference temperature and f (t) is a temperature function that adjusts the slope of the sample temperature.

The temperature function of slope f (t) adjusts the slope of the correlation of the reference temperature to the slope of the correlation of another temperature. The slope of the temperature adjustment can be used to calculate an analyte concentration or a glucose concentration using the output signal or current generated at the other temperature. To establish the temperature function f (t) of the slope, the slopes of the correlations of the other temperatures are normalized to the slope of the correlation of the reference temperature. The normalized slope of the correlation for a particular temperature is a unitless coefficient that adjusts the slope of the correlation for a reference temperature to the slope of the correlation for that particular temperature. The normalized slope of the reference temperature correlation is substantially one, indicating little or no adjustment to the slope of the reference temperature correlation. The normalized slope is analyzed graphically and/or mathematically, using, for example, regression analysis, to establish a temperature function f (T) of slope. Other normalization methods may be used to establish the temperature function.

The temperature function of slope f (t) may be a second order polynomial as follows:

f(T)＝a₂T²+a₁T+a₀ (8)。

wherein T is the sample temperature, and a₂、a₁And a₀Are coefficients of a regression analysis representing normalized slopes. Although expressed as a polynomial, the temperature function of slope f (t) may be expressed as a constant, exponential function, trigonometric function, other function, combinations thereof, or the like.

Adjusting the intercept of the correlation of the reference temperature in response to the sample temperature as follows:

Int_T＝Int_R*g(T) (9)。

wherein Int_RIntercept which is the dependence of the reference temperature and g (T) is a temperature function which adjusts the intercept of the sample temperature.

The temperature function of the intercept g (t) adjusts the intercept of the correlation of the reference temperature to the intercept of the correlation of another temperature. The temperature-adjusted intercept can be used to calculate an analyte concentration or a glucose concentration using the output signal or current generated at the other temperature. To establish the temperature function g (t) of the intercept, the intercept of the correlation of the different temperatures is normalized to the intercept of the correlation of the reference temperature. The normalized intercept of the correlation for a particular temperature is a unitless coefficient that adjusts the intercept of the correlation for the reference temperature to the intercept of the correlation for that particular temperature. The normalized intercept of the correlation of the reference temperature is substantially one, indicating little or no adjustment to the intercept of the correlation of the reference temperature. The normalized intercept is analyzed graphically and/or mathematically, using a regression analysis, for example, to establish a temperature function g (t) of the intercept. Other normalization methods may be used to establish the temperature function.

The temperature function of intercept, g (t), may be a second order polynomial as follows:

g(T)＝b₂T²+b₁T+b₀ (10)。

wherein T is the sample temperature, and b₂、b₁And b₀Are coefficients of a regression analysis representing normalized intercept. Although expressed as a polynomial, the temperature function of intercept, g (t), may be expressed as a constant, exponential function, trigonometric function, other function, combinations thereof, or the like.

In 108 of fig. 1, the analyte concentration of the sample is determined from the temperature-adjusted correlation equation (6) and the output signal at the sample temperature. The temperature functions f (T) and g (T) of slope and intercept are calculated using equations (8) and (10), respectively. The slope and intercept S of the correlation of the reference temperature adjusted in response to the sample temperature are calculated using equations (7) and (9), respectively_TAnd Int_T。

At 110 in FIG. 1, the analyte concentration calculated using the temperature adjusted correlation equation (6) and the output signal at the sample temperature can be displayed or stored for future reference.

The effect of changes in slope and intercept on analyte concentration in relation to changes in temperature can be analyzed. The temperature coefficient defines the change of a parameter related to the temperature change. For parameters such as analyte concentration, slope and intercept, the temperature coefficient may be defined as follows:

wherein alpha is_A、α_SAnd alpha_IntTemperature coefficients for analyte concentration, slope and intercept, respectively, a is analyte concentration, S is slope, Int is intercept, and T is temperature.

For a constant input signal, such as current, the relative change in analyte concentration a related to the change in slope S and intercept Int can be given using analyte calculation equation (6), as follows:

where OS is an output signal such as a current.

Substituting equations (16) and (17) into equation (15) gives the following relationship for the relative change in analyte concentration, such as glucose:

substituting and transforming the temperature coefficients of equations (11), (12) and (13) into equation (19) provides the following relationships:

equation (21) indicates that the effect of the temperature coefficient of the slope is equivalent to the analyte concentration, but opposite in magnitude. However, the effect of the temperature coefficient of intercept is small in magnitude, depending on the slope, intercept and measured analyte concentration.

For analytes such as glucose in whole blood, the change in intercept temperature coefficient has less effect on the glucose temperature coefficient at higher glucose concentrations. If the intercept-to-slope ratio Int/S is 50 and the glucose concentration is 150mg/dL, only one-third of the intercept temperature coefficient has an effect on the glucose temperature coefficient (the effect of temperature on the temperature coefficient of glucose concentration includes only one-third of the effect of temperature on the intercept temperature coefficient). At lower glucose concentrations, the effect of the intercept temperature coefficient on the glucose temperature coefficient is more pronounced. If the intercept-to-slope ratio Int/S is 50 and the glucose concentration is 50mg/dL, then all of the intercept temperature coefficients have an effect on the glucose temperature coefficient (the effect of temperature on the temperature coefficient of glucose concentration includes all of the effect of temperature on the intercept temperature coefficient). A smaller Int/S ratio will reduce the effect of the intercept temperature coefficient on the glucose temperature coefficient.

FIG. 2 illustrates a method for adjusting the correlation of analyte concentration to output signal at a reference temperature in response to temperature. In 202, a correlation between the analyte concentration and the output signal is determined for a reference temperature and at least one other temperature. At 204, a normalized temperature function of the slope and intercept of the correlation of the reference temperature is established. At 206, the correlation of the reference temperature is adjusted in response to the normalized temperature function of slope and intercept. This method may be used with the method described in fig. 1, similar methods, or other methods.

In 202 of fig. 2, a correlation between an analyte concentration and an output signal is determined for a reference temperature and at least one other temperature. As previously described, the output signal may be generated by an electrochemical reaction of an analyte in the sample. For each temperature, an output signal is experimentally generated from the electrochemical reaction at different analyte concentrations. The results of the experiment were analyzed to establish a correlation between analyte concentration and output signal at each temperature.

Fig. 3 is a graph illustrating the correlation between analyte concentration and output signal. In this figure, each output signal is a current generated by an electrochemical reaction (e.g., gated amperometry). The analyte concentration is the glucose concentration in whole blood. The correlation between the current and the glucose concentration is illustrated for a reference temperature of 25 ℃ and two other temperatures (10 ℃ and 40 ℃). While the correlation at 25 ℃ is selected as the correlation at the reference temperature, the correlation at other temperatures (including a temperature not shown) may be selected as the correlation at the reference temperature. Although the figures are directed to particular features such as number of correlations, output signal, analyte concentration, temperature, etc., the figures are not intended to limit scope, application, or implementation, etc.

Each of the illustrated correlations is linear and can be represented by a correlation equation having the general form:

where G is the glucose concentration, I is the current, Int is the intercept of the correlation line with the y-axis, and S is the slope of the correlation line. While the correlation between glucose concentration and current is shown as a linear relationship, other correlations may have other relationships such as polynomial relationships, exponential relationships, trigonometric relationships, combinations thereof, and the like.

In 204 of fig. 2, a normalized temperature function of the slope and intercept of the correlation of the reference temperature is established. The temperature function adjusts the slope and intercept of the correlation for a reference temperature to the slope and intercept of the correlation for another temperature. The slope and intercept of the temperature adjustment can be used to calculate an analyte concentration or a glucose concentration using the output signal or current generated at the other temperature.

To establish the temperature function, the slope and intercept are normalized to the slope and intercept of the correlation of the reference temperature. The normalized slope of the correlation for a particular temperature is a unitless coefficient that adjusts the slope of the correlation for a reference temperature to the slope of the correlation for that particular temperature. The normalized intercept of the correlation for a particular temperature is a unitless coefficient that adjusts the intercept of the correlation for the reference temperature to the intercept of the correlation for that particular temperature. The normalized slope and normalized intercept of the reference temperature correlation are both substantially one, indicating little or no adjustment to the slope and intercept of the reference temperature correlation. Other normalization methods may be used.

The normalized slope of the correlation may be used to generate a temperature function f (t) of slope graphically and/or mathematically using regression analysis or the like. The temperature function of slope, f (t), from regression analysis may be a second order polynomial as follows:

f(T)＝a₂T²+a₁T+a₀ (23)。

wherein T is the sample temperature, and a₂、a₁And a₀Are coefficients of a regression analysis representing normalized slopes. Although expressed as a polynomial, regression analysis may express the temperature function of slope, f (t), as another function.

The normalized intercept of the correlation may be used to generate the temperature function g (t) of the intercept graphically and/or mathematically using regression analysis or the like. The temperature function of intercept g (t) from the regression analysis may be a second order polynomial as follows:

g(T)＝b₂T²+b₁T+b₀ (24)。

wherein T is the sample temperature, and b₂、b₁And b₀Are coefficients of a regression analysis representing normalized intercept. Although expressed as a polynomial, regression analysis may express the temperature function of intercept, g (t), as another function.

FIG. 3 illustrates the correlation between current and glucose at 10 deg.C, 25 deg.C and 40 deg.C using current i₄₀、i₂₅And i₁₀Calculate the same glucose concentration G₂₅Wherein the currents are generated by electrochemical reactions of analytes in the sample at the respective temperatures. The slope and intercept of the correlation can be normalized to the slope and intercept of the correlation at a reference temperature of 25 ℃. The normalized slope and intercept of the correlation can be used to generate a temperature function of slope f (t) and a temperature function of intercept g (t).

Fig. 4 and 5 are graphs illustrating normalized slope and intercept, respectively, of the correlation between glucose concentration in whole blood and current as a function of temperature. These correlations arise from electrochemical reactions using gated amperometry with a 7 second detection time. Normalized slopes and intercepts were derived from correlations at 10 ℃, 20 ℃, 25 ℃, 30 ℃ and 40 ℃. The normalized slope and intercept are normalized to the slope and intercept of the correlation at a reference temperature of 25 ℃. Although these figures are directed to particular features such as normalized slope, temperature, etc., these figures are not intended to limit scope, application, or implementation, etc.

In fig. 4, regression analysis of normalized slope yields a temperature function of slope, f (t), as follows:

f(T)＝-0.00005765*T²+0.01453*T+0.6703 (25)。

the temperature function f (t) of slope shown in equation (25) can be used to adjust the slope of the correlation for a reference temperature of 25 ℃ to the slope of the correlation for another temperature, such as the sample temperature. T is the further temperature. The slope of the temperature adjustment can be used to calculate the glucose concentration using the current generated at the other temperature. Other temperature functions of slope may be used.

In fig. 5, regression analysis of normalized intercept yields a temperature function g (t) of intercept as follows:

g(T)＝0.0001023*T²+0.01389*T+1.284 (26)。

the temperature function of the intercept, g (t), shown in equation (26) can be used to adjust the intercept of the correlation at a reference temperature of 25 ℃ to the intercept of the correlation at another temperature, such as the sample temperature. T is the further temperature. The temperature-adjusted intercept can be used to calculate the glucose concentration using the current produced at the other temperature. Other temperature functions of intercept may be used.

A separate slope and intercept temperature function may be used with a Program Number Allocation (PNA) table of slopes and intercepts for the correlation of reference temperatures. In addition, the normalized slope and intercept provide a range within which the intrinsic temperature properties of the biosensor system are independent of the magnitude of the output signal or current generated by the electrochemical reaction. The intrinsic temperature properties are generally dependent on the design and manufacture of the sensor strip. The biosensor system may change the temperature function and/or the correlation equation in response to the type of sensor strip and lot used. The temperature function and correlation equation can be changed by changing the PNA table when a different or new sensor strip is used.

Fig. 6 and 7 are graphs illustrating normalized slope and intercept, respectively, of the correlation between glucose concentration in whole blood and current as a function of temperature. These correlations arise from electrochemical reactions using gated amperometry with detection times of 5.5 seconds, 7 seconds, 8.5 seconds, 10 seconds, 11.5 seconds, 13 seconds, and 14.5 seconds. Normalized slopes and intercepts were derived from correlations at 10 ℃, 20 ℃, 25 ℃, 30 ℃ and 40 ℃. The normalized slope and intercept are normalized to the slope and intercept of the correlation at a reference temperature of 25 ℃. Although these figures are directed to particular features such as normalized slope, temperature, etc., these figures are not intended to limit scope, application, or implementation, etc.

Fig. 6 and 7 illustrate normalized slopes and intercepts of electrochemical reactions using gated amperometry at multiple detection times. In the determination of the temperature function of the normalized slope and intercept in an electrochemical method based on multiple pulses, a plurality of correction points are present in each pulse of the pulse sequence. By using the currents generated at different temperatures and different times of different pulses, the slopes and intercepts for different temperatures can be normalized to the slopes and intercepts at 25 ℃. These normalized slopes and intercepts may be represented graphically and/or mathematically as a function of temperature. The mathematical representation can be performed by regression analysis that produces a second order polynomial. In the multi-pulse method, there are many correction points within a time range such as 5.5 seconds to 7 seconds, 8.5 seconds, 10 seconds, and the like. Within this range, the inherent temperature properties of the biosensor will remain consistent if the reagent is sufficiently hydrated.

In fig. 6, the temperature functions of normalized slope substantially overlap each other except for a detection time of 5.5 seconds, which reflects the inherent consistency of the temperature sensitivity of the biosensor system. Furthermore, the temperature function of these normalized slopes is very symmetric with respect to a reference temperature of 25 ℃. The normalized slope at 10 ℃ is about 20% less than the normalized slope at 25 ℃. The normalized slope at 40 ℃ is about 20% greater than the normalized slope at 25 ℃.

In fig. 7, the temperature function of the normalized intercept is very similar for detection times between 5.5 seconds and 10 seconds. The longer the time, the greater the effect of temperature on the normalized intercept.

In 206 of fig. 2, the correlation of the reference temperature is adjusted in response to a normalized temperature function of slope and intercept. The correlation between analyte concentration and output signal at the reference temperature is as follows:

wherein G is_RIs the analyte concentration at the reference temperature, i_RFor the output signal at the reference temperature, Int_RIntercept as a dependence of reference temperature, and S_RIs the slope of the dependence of the reference temperature.

The correlation of the reference temperature represented by equation (27) may be adjusted in response to the sample temperature. Using the slope and intercept of the temperature adjustment for the correlation of the reference temperature and the output signal at the sample temperature, the analyte concentration at the reference temperature can be calculated as follows:

wherein G is_RIs the analyte concentration at the reference temperature, i_TIs the output signal at the temperature of the sample, Int_TIntercept of correlation of reference temperature adjusted in response to sample temperature, and S_TIs the slope of the dependence of the reference temperature adjusted for the sample temperature.

Slope S of a dependence on a reference temperature adjustable in response to a sample temperature_TThe following calculations were performed:

S_T＝S_R*f(T) (29)。

wherein S_RIs the slope of the dependence of the reference temperature and f (t) is a temperature function that adjusts the slope of the sample temperature.

Intercept Int of a correlation to a reference temperature that can be adjusted in response to a sample temperature_TThe following calculations were performed:

Int_T＝Int_R*g(T) (30)。

wherein Int_RIntercept which is the dependence of the reference temperature and g (T) is a temperature function which adjusts the intercept of the sample temperature.

S can be substituted by the equations (29) and (30)_TAnd Int_TThe correlation of the reference temperature adjusted in response to the sample temperature as shown in equation (28) is rewritten as follows:

wherein G is_RIs the analyte concentration at the reference temperature, i_TIs the output signal at the temperature of the sample, Int_RIntercept as a function of the dependence of the reference temperature, g (T) being a normalized temperature function of the intercept, S_RIs the slope of the dependence of the reference temperature, and f (t) is a normalized temperature function of the slope.

The correlation of the reference temperature adjusted in response to the sample temperature, as shown in equation (31), can be rewritten as follows for the examples shown in FIGS. 3-5:

wherein G is₂₅Is the analyte concentration at a reference temperature of 25 ℃, i_TIs the output signal at the temperature of the sample, Int₂₅Intercept of dependence of reference temperature of 25 ℃, S₂₅Is the slope of the dependence of the reference temperature at 25 ℃ and T is the sample temperature.

Fig. 8 and 9 are graphs illustrating deviation values of glucose from a reference temperature as a function of temperature. Fig. 8 is a graph illustrating the deviation of the calculated glucose concentration without any temperature adjustment. Fig. 9 is a graph illustrating the deviation of the calculated glucose concentration in the case where the temperature adjustment is performed as described above. These graphs illustrate the percent deviation from a reference temperature of 25 ℃ for plasma glucose concentrations in whole blood of 56.9mg/dL, 114.0mg/dL, and 432.9 mg/dL. The analysis was generated from an electrochemical reaction using gated amperometry at sample temperatures of 10 ℃, 20 ℃, 25 ℃, 30 ℃ and 7 second detection times at 40 ℃. Although these figures are directed to particular characteristics such as temperature, glucose concentration, etc., these figures are not intended to limit scope, application, or implementation, etc.

In FIGS. 8 and 9, the percent deviation values at 10 deg.C, 20 deg.C and 25 deg.C for the 56.9mg/dL glucose concentration showed little, if any, change after temperature adjustment, especially the percent deviation value at 10 deg.C. Fig. 8 shows that without temperature compensation, the glucose concentration from the correlation generally has a negative deviation at temperatures below the reference temperature of 25 ℃. Fig. 8 also shows that without temperature regulation, the glucose concentration from the correlation generally has a positive deviation at temperatures above the reference temperature of 25 ℃. FIG. 9 shows that the percent deviation values converge to a narrow range of about +/-5% when using temperature-adjusted correlations.

A temperature coefficient function of any particular parameter may be used to further illustrate the internal consistency of the temperature function used to adjust the correlation equation between analyte concentration and output signal. The temperature coefficient (intrinsic property) of the output signal OS may be defined as follows:

wherein alpha is_OSIs the temperature coefficient of the output signal, OS is the output signal, and T is the temperature.

Fig. 10 and 11 are graphs illustrating the effect of a temperature-adjusted correlation equation between analyte concentration and output signal on a temperature coefficient function. FIG. 10 illustrates a temperature function of current from a glucose sensor with normalized slope and intercept. Fig. 11 illustrates a temperature coefficient function of the normalized current of fig. 10 as a function of temperature. The normalized current and temperature coefficient (TempCo) is responsive to glucose concentrations of 50mg/dL, 100mg/dL, 200mg/dL, 400mg/dL, and 600 mg/dL. In fig. 10, the current at 25 ℃ should be equal to the glucose value according to equation (5) for normalized slope and intercept. Fig. 11 shows the temperature coefficient as a function of temperature, the lower the temperature, the higher the temperature coefficient. A temperature coefficient of about 1.85 to 0.75%/DEG C at a temperature of about 10 to 40 ℃. Furthermore, the temperature coefficient function is independent of glucose concentration. Although these figures are directed to particular characteristics such as temperature, glucose concentration, etc., these figures are not intended to limit scope, application, or implementation, etc.

Fig. 12 is a schematic diagram of a biosensor 1200 for determining an analyte concentration in a biological fluid sample. The biosensor 1200 includes a measurement device 1202 and a sensor strip 1204, which may be implemented as a desktop device, a portable or handheld device, or the like. The measurement device 1202 and the sensor strip 1204 may be adapted to implement an electrochemical sensor system, an optical sensor system, combinations thereof, or the like. Biosensor 1200 adjusts the correlation for determining analyte concentration from output signals at one temperature, and thus from output signals at other temperatures (e.g., the aforementioned sample temperature). This correlation of temperature adjustment improves the accuracy and precision of the biosensor 1200 in determining the analyte concentration of a sample. The biosensor 1200 may be used to determine analyte concentrations, including those of glucose, uric acid, lactate, cholesterol, bilirubin, and the like. Although a particular configuration of biosensor 1200 is shown, it may have other configurations, including configurations with other elements.

The sensor strip 1204 has a base 1206 that forms a reservoir 1208 and a channel 1210 with an opening 1212. The reservoir 1208 and the channel 1210 may be covered by a cap with a vent. The reservoir 1208 defines a partially enclosed volume (cap gap). Reservoir 1208 can contain a component that helps retain a liquid sample (e.g., a water-swellable polymer or porous polymer matrix). The reagent may be deposited in the reservoir 1208 and/or the channel 1210. The reagent may include one or more enzymes, binders, mediators, and the like. The reagent may comprise a chemical indicator for the optical system. The sensor strip 1204 may also have a sample interface 1214 disposed adjacent to the reservoir 1208. The sample interface 1214 may partially or completely surround the reservoir 1208. The sensor strip 1204 may have other configurations.

In an optical sensor system, the sample interface 1214 has a light inlet or aperture for viewing the sample. The light inlet may be covered with a substantially transparent material. On both sides of the reservoir 1208, the sample interface may have light inlets.

In an electrochemical system, the sample interface 1214 has conductors that connect to the working electrode and the counter electrode. The electrodes may lie substantially in the same plane. The electrodes may be spaced more than 200 μm or 250 μm apart and the spacing from the cover may be at least 100 μm. The electrodes may be disposed on a surface of the base 1206 forming the reservoir 1208. The electrodes may extend or be inserted into a cap gap formed by the reservoir 1208. The dielectric layer may partially cover the conductor and/or the electrode. The sample interface 1214 may have other electrodes and conductors.

The measurement device 1202 includes circuitry 1216 coupled to a sensor interface 1218 and a display 1220. Circuitry 1216 includes a processor 1222 coupled to a signal generator 1224, a temperature sensor 1226, and a storage medium 1228.

The signal generator 1224, in response to the processor 1222, provides an electrical input signal to the sensor interface 1218. In an optical system, the electrical input signal may be used to operate or control the detector and light source in sensor interface 1218. In an electrochemical system, an electrical input signal may be transmitted by sensor interface 1218 to sample interface 1214, thereby applying the electrical input signal to the biological fluid sample. The electrical input signal may be a potential or a current and may be constant, varying, or a combination thereof, for example when an AC signal with a DC signal offset is applied. The electrical input signal may be applied in the form of a single or multiple pulses, sequences or periods. The signal generator 1224 may also record the output signal from the sensor interface as a generator-recorder.

The temperature sensor 1226 measures the temperature of the sample in the reservoir of the sensor strip 1204. The sample temperature may be measured, calculated from the output signal, or may be assumed to be the same or similar to the ambient temperature or the measurement of the temperature of the device in which the biosensor system is implemented. The temperature may be measured using a thermistor, thermometer, or other temperature sensing device. Other techniques may be used to determine the sample temperature.

The storage medium 1228 may be a magnetic, optical, or semiconductor memory, other computer-readable storage device, or the like. The storage medium 1228 may be a fixed storage device or a removable storage device such as a memory card.

The processor 1222 implements analyte analysis and data processing using computer readable software code and data stored in the storage medium 1228. The processor 1222 may initiate analyte analysis in response to the presence of the sensor strip 1204 at the sensor interface 1218, initiate application of a sample onto the sensor strip 1204 in response to user input, and so forth. The processor 1222 directs the signal generator 1224 to provide the electrical input signal to the sensor interface 1218. The processor 1222 receives the sample temperature from the temperature sensor 1226. The processor 1222 receives the output signals by the sensor interface 1218. An output signal is generated in response to a redox reaction of an analyte in the sample. Optical systems, electrochemical systems, etc. may be used to generate the output signal. Processor 1222 determines the analyte concentration from the output signal at the sample temperature using the aforementioned temperature-adjusted correlation equation for the reference temperature. The results of the analyte analysis are output to display 1220 and may be stored in storage medium 1228.

The equation of correlation between analyte concentration and output signal can be represented graphically, mathematically, or a combination thereof. The correlation equation may be represented by a Program Number Assignment (PNA) table, another look-up table, etc., stored in the storage medium 1228. Instructions for performing analyte analysis may be provided by computer-readable software code stored in storage medium 1228. The code may be object code or any other code that describes or controls the functions described herein. The data from the analyte analysis may be subjected to one or more data processing in processor 1222, including determination of decay rate, K-constant, slope, intercept and/or sample temperature.

In an electrochemical system, the sensor interface 1218 has contacts that connect to or are in electrical communication with conductors in the sample interface 1214 of the sensor strip 1204. The sensor interface 1218 transmits the electrical input signal from the signal generator 1224 to the connector in the sample interface 1214 via these contacts. The sensor interface 1218 also transmits output signals from the sample to the processor 1222 and/or the signal generator 1224 via the contacts.

In optical systems that absorb light and generate light, sensor interface 1218 includes a detector that collects and measures light. The detector receives light from the liquid sensor via a light inlet in the sample interface 1214. In optical systems that absorb light, sensor interface 1218 also includes a light source such as a laser, light emitting diode, or the like. The incident light beam may have a wavelength selected to facilitate absorption by the reaction products. Sensor interface 1218 directs an incident light beam from the light source via a light inlet in sample interface 1214. The detector may be positioned at an angle, such as 45 deg., to the light entrance to receive light reflected back from the sample. A detector may be disposed adjacent to the light inlet on the other side of the sample from the light source to receive light transmitted through the sample.

Display 1220 can be analog or digital. The display may be an LCD display adapted to display numerical readings.

In use, a liquid sample for analysis is transferred into the cap gap formed by reservoir 1208 by introducing liquid into opening 1212. The liquid sample flows into the reservoir 1208 via the channel 1210, filling the cap gap while venting the previously contained air. The liquid sample chemically reacts with reagents deposited in the channel 1210 and/or reservoir 1208.

The sensor strip 1204 is positioned adjacent to the measurement device 1202. The proximal locations include locations where the sample interface 1214 is in electrical and/or optical communication with the sensor interface 1218. Electrical communication includes the transfer of input and/or output signals between contacts in sensor interface 1218 and conductors in sample interface 1214. Optical communication includes the transfer of light between a light inlet in the sample interface 1214 and a detector in the sensor interface 1218. Optical communication also includes the transfer of light between a light inlet in the sample interface 1214 and a light source in the sensor interface 1218.

The processor 1222 receives the sample temperature from the temperature sensor 1226. Processor 1222 directs signal generator 1224 to provide an input signal to sensor interface 1218. In an optical system, sensor interface 1218 operates the detector and light source in response to the input signal. In an electrochemical system, the sensor interface 1218 provides the input signal to the sample through the sample interface 1214. Processor 1222 receives the aforementioned output signal generated in response to the redox reaction of the analyte in the sample.

Processor 1222 determines an analyte concentration of the sample. The measurement device adjusts the correlation between the analyte concentration and the output signal at the reference temperature in response to the sample temperature. Determining an analyte concentration from the temperature-adjusted correlation and the output signal at the sample temperature. At 110, the analyte concentration is displayed and may be stored for future reference.

Without intending to be limited in scope, application, or implementation, the foregoing methods and systems may be implemented using the following algorithms:

step 1: switching on the power supply of the meter

Step 2: performing biosensor self-tests

And step 3: performing standardization of biosensor electronics

And 4, step 4: measuring the temperature T

And 5: checking temperature range

If (T > T_Hi) If so, an error mode of "excessive temperature" is set "

If (T < T)_Low) Then, an error mode "temperature is too low" is set "

Step 6: applying an input signal to a sample

And 7: measuring the output signal i

And 8: looking up slope and intercept in Program Number Assignment (PNA) tables

Slope value of S ═ current

Int is the intercept of the current

And step 9: adjusting slope and intercept of temperature effects

S_T＝S*(a₂*T₁ ²+a₁*T₁+a₀)

Int_T＝Int*(b₂*T₁ ²+b₁*T₁+b₀)

Step 10: calculating the glucose concentration at 25 deg.C

Step 11: examination of extreme glucose content

If (G)₂₅＞G_max) If so, an error mode of "glucose is too high"

Step 12: display the results

A Program Number Assignment (PNA) table that may be used in the algorithm is given in table I below. The constants that can be used in the algorithm are given in table II below. Other PNA tables and/or constants may be used.

TABLE I

PNA#	Code table #	Slope 8.028 of column	PNA#	Code table #	Slope 8.498 of column	PNA#	Code table #	Slope of column 8.995	PNA#	Code table #	Slope 9.522 of column
														Intercept of a beam			Intercept of a beam			Intercept of a beam			Intercept of a beam
1	1	310.04	18	18	310.62	34	35	311.24	49	52	311.90
												2	2	330.11	19	19	331.87	35	36	333.73	50	53	335.71
3	3	350.18	20	20	353.11	36	37	356.22	51	54	359.51
												4	4	370.25	21	21	374.36	37	38	378.71	52	55	383.32
5	5	390.32	22	22	395.60	38	39	401.20	53	56	407.12
												6	6	410.39	23	23	416.85	39	40	423.69	54	57	430.92
7	7	430.46	24	24	438.09	40	41	446.17	55	58	454.73
												8	8	450.53	25	25	459.34	41	42	468.66	56	59	478.53
9	9	470.60	26	26	480.58	42	43	491.15	57	60	502.34
												10	10	490.67	27	27	501.83	43	44	513.64	58	61	526.14
11	11	510.74	28	28	523.07	44	45	536.13	59	62	549.95
												12	12	530.81	29	29	544.32	45	46	558.62	60	63	573.75
13	13	550.88	30	30	565.56	46	47	581.11	61	64	597.56
												14	14	570.95	31	31	586.81	47	48	603.59	62	65	621.36
15	15	591.02	32	32	608.05	48	49	626.08		66
												16	16	611.09	33	33	629.30		50			67
17	17	631.16		34			51			68

TABLE II

Constant number	Description of the invention	Numerical value	Unit of
				THI	Ineffective high temperature	50	℃
TLO	Ineffective low temperature	5	℃

a2	Coefficient of slope temperature function	-5.765e-5	--
				a1	Coefficient of slope temperature function	0.01453	--
a0	Coefficient of slope temperature function	0.6703	--
				b2	Coefficient of intercept temperature function	1.023	--
b1	Coefficient of intercept temperature function	-0.01389	--
				b0	Coefficient of intercept temperature function	1.284	--
Gmax	Maximum allowable glucose concentration	1500	mg/dL

While various embodiments of the invention have been described, it will be apparent to those of ordinary skill in the art that other embodiments and implementations are possible within the scope of the invention.

Claims (31)

1. A method for determining an analyte concentration in a biological fluid sample, comprising:

measuring the temperature of the sample;

generating an output signal in response to a redox reaction of an analyte in the sample;

adjusting a correlation between the analyte concentration and the output signal at a reference temperature in response to the temperature; and

determining an analyte concentration from the temperature-adjusted correlation and the output signal at the sample temperature;

wherein the temperature-modulated correlation between analyte concentration and output signal is represented as follows:

wherein A is_RFor analyte concentration at a reference temperature, OS_TIs the output signal at the temperature of the sample, Int_TFor the intercept adjusted by a normalized temperature function of the intercept, and S_TIs the slope adjusted by a normalized temperature function of the slope.

2. The method of claim 1, further comprising adjusting the correlation in response to a normalized temperature function of slope and a normalized temperature function of intercept.

3. The method of claim 1, wherein the normalized temperature function of slope comprises a regression analysis of normalized slope.

4. The method of claim 3, wherein the normalized temperature function of slope f (T) is represented as follows:

f(T)=a₂T²+a₁T+a₀

wherein T is the sample temperature, and a₂、a₁And a₀Are coefficients of a regression analysis representing normalized slopes.

5. The method of claim 1, wherein the normalized temperature function of the intercept comprises a regression analysis of normalized intercepts.

6. The method of claim 5, wherein the normalized temperature function of intercept g (T) is represented as follows:

g(T)=b₂T²+b₁T+b₀

wherein T is the sample temperature, and b₂、b₁And b₀Are coefficients of a regression analysis representing normalized intercept.

7. The method of claim 1, further comprising generating the output signal in response to an electrochemical process.

8. The method of claim 1, wherein the output signal comprises light.

9. The method of claim 1, wherein the output signal comprises an electrical signal.

10. The method of claim 1, further comprising generating the output signal in response to a pulsed input signal.

11. The method of claim 1, wherein the analyte comprises glucose and the biological fluid comprises whole blood.

12. A method for adjusting a correlation between an analyte concentration and an output signal at a reference temperature in response to a temperature, comprising:

determining a correlation between the analyte concentration and the output signal for a reference temperature and at least one other temperature;

establishing a normalized temperature function of the slope and intercept of the correlation of the reference temperature; and

adjusting the correlation of the reference temperature in response to a normalized temperature function of the slope and intercept.

13. The method of claim 12, wherein the normalized temperature function of slope comprises a regression analysis of normalized slope.

14. The method of claim 13, wherein the normalized temperature function of slope f (t) is represented as follows:

f(T)=a₂T²+a₁T+a₀

wherein T is the sample temperature, and a₂、a₁And a₀Are coefficients of a regression analysis representing normalized slopes.

15. The method of claim 12, wherein the normalized temperature function of the intercept comprises a regression analysis of normalized intercepts.

16. The method of claim 15, wherein the normalized temperature function of intercept g (t) is represented as follows:

g(T)=b₂T²+b₁T+b₀

wherein T is the sample temperature, and b₂、b₁And b₀Are coefficients of a regression analysis representing normalized intercept.

17. The method of claim 12, wherein the correlation between analyte concentration and output signal at a reference temperature is represented as follows:

wherein G is_RIs the analyte concentration at the reference temperature, i_RFor the output signal at the reference temperature, Int_RIntercept as a dependence of reference temperature, and S_RIs the slope of the dependence of the reference temperature.

18. The method of claim 12, wherein the dependence of the temperature adjustment of the reference temperature is expressed as follows:

wherein G is_RIs the analyte concentration at the reference temperature, i_TIs the output signal at the temperature of the sample, Int_RIntercept as a function of the dependence of the reference temperature, g (T) being a normalized temperature function of the intercept, S_RIs the slope of the dependence of the reference temperature, and f (t) is a normalized temperature function of the slope.

19. The method of claim 12, wherein the output signal comprises light.

20. The method of claim 12, wherein the output signal comprises an electrical signal.

21. The method of claim 12, further comprising generating the output signal in response to a pulsed input signal.

22. The method of claim 12, wherein the analyte comprises glucose and the biological fluid comprises whole blood.

23. A biosensor for determining an analyte concentration in a biological fluid, comprising:

a measurement device having a processor connected to a sensor interface and a temperature sensor;

a sensor strip having a sample interface located on a substrate, wherein the sample interface is adjacent to a reservoir formed by the substrate; and

wherein the processor adjusts a correlation between analyte concentration and output signal at a reference temperature in response to a sample temperature from the temperature sensor; and

wherein the processor determines an analyte concentration from the temperature-adjusted correlation in response to an output signal from the sample interface.

24. The biosensor of claim 23, where the processor adjusts the correlation in response to a normalized temperature function of slope and a normalized temperature function of intercept.

25. The biosensor of claim 23, wherein the correlation of the temperature adjustment of the reference temperature is represented as follows:

wherein G is_RIs the analyte concentration at the reference temperature, i_TIs the output signal at the temperature of the sample, Int_RIntercept as a function of the dependence of the reference temperature, g (T) being a normalized temperature function of the intercept, S_RIs the slope of the dependence of the reference temperature, and f (t) is a normalized temperature function of the slope.

26. The biosensor of claim 25, where the normalized temperature function of slope f (t) is represented as follows:

f(T)=a₂T²+a₁T+a₀

wherein T is the sample temperature, and a₂、a₁And a₀Are coefficients of a regression analysis representing normalized slopes.

27. The biosensor of claim 25, where the normalized temperature function of intercept g (t) is represented as follows:

g(T)=b₂T²+b₁T+b₀

wherein T is the sample temperature, and b₂、b₁And b₀Are coefficients of a regression analysis representing normalized intercept.

28. The biosensor of claim 23, where the output signal comprises light.

29. The biosensor of claim 23, where the output signal comprises an electrical signal.

30. The biosensor of claim 23, where the output signal is responsive to a pulsed input signal.

31. The biosensor of claim 23, where the analyte comprises glucose and the biological fluid comprises whole blood.