Patent Description:
The present invention relates generally to a biosensor for analyte concentration (e.g., blood glucose) and more specifically a system that detects test sensor malfunctions in providing a temperature value from either an estimate temperature or a measured temperature in the process of analyte concentration determination.

The quantitative determination of analytes in body fluids is of great importance in the diagnoses and maintenance of certain physiological conditions. For example, persons with diabetes (PWDs) frequently check the glucose level in their bodily fluids. The results of such tests can be used to regulate the glucose intake in their diets and/or to determine whether insulin or other medication needs to be administered. A PWD typically uses a measurement device (e.g., a blood glucose meter) that calculates the glucose concentration in a fluid sample from the PWD, where the fluid sample is collected on a test sensor that is received by the measurement device. The failure to take corrective action may have serious medical implications for that person.

One method of monitoring the blood glucose level of a PWD is with a portable testing device. The portable nature of these devices enables users to conveniently test their blood glucose levels at any location. One type of device utilizes an electrochemical test sensor to analyze the blood sample. A user employs a lancet to obtain a blood sample for application to a reservoir in the test sensor. The electrochemical test sensor typically includes electrodes that, when mated with the meter, electrically measures the reaction of the blood sample to determine an analyte concentration. A special meter device must therefore be carried by the user to determine the blood sample analysis.

Typically, a meter applies an input signal (e.g., a gated amperometry signal) to the electrodes of the test sensor. Traditional test sensors and meters typically use a glucose concentration estimation algorithm that determines the correlation between the measured current output from the blood sample and pre-determined analyte concentration values correlated with such outputs. These pre-determined values are determined by a laboratory instrument such as a YSI laboratory instrument.

The chemical reactions employed in the test sensors of any amperometric blood glucose monitoring (BGM) system are affected by temperature. A measured temperature value is therefore an important input into the glucose estimation algorithm of such systems. In known systems, temperature is measured by a thermistor based temperature sensors. The thermistor for the temperature sensor is typically located within the meter. Due to the thermal mass of the meter, thermistors cannot respond instantaneously to changes in the ambient temperature and thus distortions in temperature measurements can occur. When BGM meters are moved from one environment to another, a period of time is required for the meter to equilibrate to its new environment, and during this time the thermistor value will not accurately reflect the actual temperature. In the complex glucose estimation algorithms employed in gated amperometry meters, the temperature is included in many terms in the various compensation equations, and thus when the thermistor based temperature value is incorrect, erroneous results may occur.

Temperature estimates from thermistors are therefore subject to a risk that the meter has not equilibrated to its environment, resulting in erroneous temperature values being used by the algorithm. This creates a risk of inaccurate glucose readings. One solution for a non-equilibrated environment is to use an estimate temperature based on other parameters not derived from the thermistor. However, using the estimated temperature creates another risk from damaged sensors that may produce erroneous temperature estimates. Therefore, a large difference between the estimated temperature and the thermistor can indicate a damaged sensor in addition to a dis-equilibrated meter. In the case of a damaged sensor, the correct response is to report an error code. However, if the damaged sensor is not detected, the meter may attempt to calculate glucose using the temperature measurement from the damaged sensor, possibly resulting in inaccurate glucose readings.

Thus, there exists a need for a procedure to address the risk of inaccurate glucose results caused by a disequilibrated meter that relies solely on thermistor based temperature measurement. There is another need for a system that compares the estimated temperature to the measured temperature to provide information about whether the meter is properly equilibrated. There is another need for a system that allows use of an estimated temperature from a temperature estimation algorithm to determine analyte concentration even when disequilibration is detected. There is another need for a system that compares the estimated temperature to the measured temperature to provide information about whether the test sensor is damaged.

A biosensor with temperature compensation is known from <CIT>.

According to independent claim <NUM>, an analyte concentration sensor system for measuring an analyte of a fluid sample of a user is provided.

In another example, a method to determine suitability of a temperature measurement from a thermistor temperature sensor in an analyte meter, the analyte meter including a biosensor interface operable to be connected to a test sensor holding a fluid sample, and a controller, is set out in independent claim <NUM>.

An input signal is generated to the interface when connected to the test sensor with the fluid sample. An output signal is determined from the test sensor. A measured temperature is determined from a thermistor based temperature sensor. An estimated temperature is determined from a temperature estimation algorithm via the controller. The difference between the estimated temperature and the measured temperature is determined via the controller. One of the estimated temperature or the measured temperature is selected via the controller based on the estimated temperature, the measured temperature, and the difference between the estimated temperature and the measured temperature. The selected estimated temperature or measured temperature is provided as a temperature input to an analyte concentration determination algorithm.

Another example is an analyte concentration sensor system for measuring an analyte of a fluid sample of a user. The sensor system includes a biosensor interface operable to be connected to a test sensor holding the fluid sample. The system includes a thermistor based temperature sensor configured to measure temperature. The system includes a controller coupled to the biosensor interface and the temperature sensor. The controller is operable to generate an input signal to the biosensor interface and read an output signal from the biosensor interface. The controller is operable to determine a measured temperature from the temperature sensor and execute a temperature estimation algorithm to determine an estimated temperature. The controller determines an absolute difference between the estimated temperature and the measured temperature. The controller determines a malfunction of the test sensor based on the estimated temperature, the measured temperature, and the absolute difference between the estimated temperature and the measured temperature.

Another example is a method to determine failure of a test sensor connected to an analyte meter. The analyte meter includes a biosensor interface operable to be connected to the test sensor holding a fluid sample, and a controller. An input signal is generated to the interface when connected to the test sensor with the fluid sample. An output signal is determined from the test sensor. A measured temperature is determined from a thermistor based temperature sensor. An estimated temperature is determined from a temperature estimation algorithm via the controller. An absolute difference between the estimated temperature and the measured temperature is determined via the controller. A malfunction of the test sensor is determined based on the estimated temperature, the measured temperature, and the absolute difference between the estimated temperature and the measured temperature.

Additional aspects of the invention will be apparent to those of ordinary skill in the art in view of the detailed description of various embodiments, which is made with reference to the drawings, a brief description of which is provided below.

While the invention is susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and will be described in detail herein. It should be understood, however, that the invention is not intended to be limited to the particular forms disclosed. Rather, the invention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.

The present disclosure is directed toward an analyte concentration measurement system that employs temperature equilibration logic to estimate ambient temperature using non-thermistor signals. The differential between the estimated temperature and the temperature measured from the thermistor is compared to defined thresholds to determine one of three actions to perform. The three actions include: <NUM>) calculating the analyte concentration normally using the thermistor signal under the assumption that the meter is equilibrated and the test sensor signals are valid; <NUM>) calculating the analyte concentration using an estimated temperature under the assumption that the meter is not equilibrated to the ambient conditions and the estimated temperature will produce a more accurate result; or <NUM>) reporting an error under the assumption that the test sensor is compromised and the signals are not valid.

The logic that governs the three possible actions is as follows. When the estimated temperature and the thermistor measured temperature are in good agreement, both results are assumed to be accurate, and the thermistor measured temperature is used to calculate the analyte concentration because it produces the most reliable value under normal circumstances. When a large discrepancy is observed between the thermistor and the estimated temperature, there are two possible explanations: <NUM>) the thermistor measured temperature is inaccurate because the meter is not equilibrated to the ambient environment; or <NUM>) the estimated temperature is inaccurate because the sensor signals used to calculate the sensor were incorrect, either due to a damaged sensor or to perturbation of the sample during the test. The determination of whether to report a corrected result or an error message is based on an understanding of the most likely relationship between the thermistor measured temperature and the estimated temperature in each of the two possible scenarios described above. Since most glucose concentration testing occurs at room temperature, when the thermistor measured temperature is at an extreme value but the estimated temperature is normal, disequilibration is the most likely explanation, and the estimated temperature is used to calculate the analyte concentration. When the temperature reading from the thermistor is normal but the estimated temperature is extreme, it is more likely that the signal output waveform from the test sensor is anomalous and that an error should be reported.

<FIG> depicts a schematic representation of a biosensor system <NUM> that determines an analyte concentration in a sample of a biological fluid. Biosensor system <NUM> includes a measurement device <NUM> and a test sensor <NUM>, which may be implemented in any analytical instrument, including a bench-top device, a portable or hand-held device, or the like. The measurement device <NUM> and the test sensor <NUM> may be adapted to implement an electrochemical sensor system, an optical sensor system, a combination thereof, or the like. The biosensor system <NUM> determines analyte concentrations from output signals with a glucose estimation algorithm that uses a temperature input to correct its output for temperature. A temperature selection routine determines whether to use temperature measured from a thermistor sensor, an estimated temperature or return an error message. As will be explained, the routine improves the measurement performance of the biosensor system <NUM> in determining the analyte concentration of the sample by providing a more accurate temperature input into the analyte concentration estimation algorithm.

The biosensor system <NUM> may be utilized to determine analyte concentrations, including those of glucose, lipid profiles (e.g., cholesterol, triglycerides, LDL and HDL), microalbumin, hemoglobin A1C, fructose, lactate, or bilirubin. It is contemplated that other analyte concentrations may also be determined. It is also contemplated that more than one analyte may be determined. The analytes may be in, for example, a whole blood sample, a blood serum sample, a blood plasma sample, other body fluids like urine, and non-body fluids. Thus, one example of the analyte concentration estimation algorithm is a glucose concentration estimation algorithm executed by the biosensor system <NUM>. As used within this application, the term "concentration" refers to an analyte concentration, activity (e.g., enzymes and electrolytes), titers (e.g., antibodies), or any other measure concentration used to measure the desired analyte. While a particular configuration is shown, the biosensor system <NUM> may have other configurations, including those with additional components.

The test sensor <NUM> has a base <NUM> that forms a reservoir <NUM> and a channel <NUM> with an opening <NUM>. The reservoir <NUM> and the channel <NUM> may be covered by a lid with a vent. The reservoir <NUM> defines a partially-enclosed volume. The reservoir <NUM> may contain a composition that assists in retaining a liquid sample such as water-swellable polymers or porous polymer matrices. Reagents may be deposited in the reservoir <NUM> and/or the channel <NUM>. The reagents may include one or more enzymes, binders, mediators, and like species. The reagents may include a chemical indicator for an optical system. The test sensor <NUM> also may have a sample interface <NUM> disposed adjacent to the reservoir <NUM>. The sample interface <NUM> may partially or completely surround the reservoir <NUM>. The test sensor <NUM> may have other configurations.

In an optical sensor system, the sample interface <NUM> has an optical portal or aperture for viewing the sample. The optical portal may be covered by an essentially transparent material. The sample interface may have optical portals on opposite sides of the reservoir <NUM>.

In an electrochemical system, the sample interface <NUM> has conductors connected to a working electrode and a counter electrode. The electrodes may be substantially in the same plane or in different planes. The electrodes may be disposed on a surface of the base <NUM> that forms the reservoir <NUM>. The electrodes may extend or project into the reservoir <NUM>. A dielectric layer may partially cover the conductors and/or the electrodes. The sample interface <NUM> may have other electrodes and conductors.

The measurement device <NUM> includes electrical circuitry <NUM> connected to a sensor interface <NUM> and a display <NUM>. The electrical circuitry <NUM> includes a processor <NUM> connected to a signal generator <NUM>, a temperature sensor <NUM>, and a storage medium <NUM>. In this example, the temperature sensor <NUM> operates by providing an electrical signal to a thermistor and reading an output signal from the thermistor that is proportional to the ambient temperature.

The signal generator <NUM> provides an electrical input signal to the sensor interface <NUM> in response to the processor <NUM>. In optical systems, the electrical input signal may be used to operate or control the detector and light source in the sensor interface <NUM>. In electrochemical systems, the electrical input signal may be transmitted by the sensor interface <NUM> to the sample interface <NUM> to apply the electrical input signal to the sample of the biological fluid. The electrical input signal may be a potential or current and may be constant, variable, or a combination thereof, such as when an AC signal is applied with a DC signal offset. The electrical input signal may be applied as a single pulse or in multiple pulses, sequences, or cycles, such as a gated ampometric signal. The signal generator <NUM> also may record an output signal from the sensor interface as a generator-recorder.

The temperature sensor <NUM> determines the temperature of the sample in the reservoir of the test sensor <NUM> based on the output signal of a thermistor in the sensor <NUM>. As will be explained below, the temperature of the sample may be estimated by calculation from non-temperature signals, such as the output signal or signals, time, ratio between signals, and the like. The estimated temperature is assumed to be the same or similar to a measurement of the ambient temperature or the temperature of a device implementing the biosensor system. The temperature may be measured using another temperature sensing device.

The storage medium <NUM> may be a magnetic, optical, or semiconductor memory, another storage device, or the like. The storage medium <NUM> may be a fixed memory device, a removable memory device, such as a memory card, remotely accessed, or the like.

The processor <NUM> implements the analyte analysis and data treatment using computer readable software code and data stored in the storage medium <NUM>. The processor <NUM> may start the analyte analysis in response to the presence of the test sensor <NUM> at the sensor interface <NUM>, the application of a sample to the test sensor <NUM>, in response to user input, or the like. The processor <NUM> directs the signal generator <NUM> to provide the electrical input signal or signals to the sensor interface <NUM>. The processor <NUM> receives an output signal associated with the sample temperature from the temperature sensor <NUM>. The processor <NUM> receives the output signal or signals from the sensor interface <NUM>. The output signal is generated in response to the reaction of the analyte in the sample. The output signal may be generated using an optical system, an electrochemical system, or the like. The processor <NUM> determines compensated analyte concentrations from output signals using a glucose estimation algorithm as previously discussed. The results of the analyte analysis may be output to the display <NUM> and may be stored in the storage medium <NUM>.

The correlation equations between analyte concentrations and output signals may be represented graphically, mathematically, a combination thereof, or the like. A correlation equation may include one or more index functions. Correlation equations may be represented by a program number (PNA) table, another look-up table, or the like that is stored in the storage medium <NUM>. Constants and weighing coefficients also may be stored in the storage medium <NUM>. Instructions regarding implementation of the analyte analysis may be provided by the computer readable software code stored in the storage medium <NUM>. The code may be object code or any other code describing or controlling the functionality described herein. The data from the analyte analysis may be subjected to one or more data treatments, including the determination of decay rates, K constants, ratios, functions, and the like in the processor <NUM>. In this example, the storage medium <NUM> stores an analyte concentration estimation algorithm <NUM> that determines the analyte concentration from inputs such as the signals from the sensor interface <NUM>. The storage medium also stores a temperature selection routine <NUM> that determines a temperature value to input to the analyte concentration estimation algorithm <NUM>. The storage medium <NUM> also stores a temperature estimation algorithm <NUM> for determining an estimated temperature value for the temperature selection routine <NUM>.

In electrochemical systems, the sensor interface <NUM> has contacts that connect or electrically communicate with the conductors in the sample interface <NUM> of the test sensor <NUM>. The sensor interface <NUM> transmits the electrical input signal from the signal generator <NUM> through the contacts to the connectors in the sample interface <NUM>. The sensor interface <NUM> also transmits the output signal from the sample through the contacts to the processor <NUM> and/or signal generator <NUM>.

In light-absorption and light-generated optical systems, the sensor interface <NUM> includes a detector that collects and measures light. The detector receives light from the liquid sensor through the optical portal in the sample interface <NUM>. In a light-absorption optical system, the sensor interface <NUM> also includes a light source such as a laser, a light emitting diode, or the like. The incident beam may have a wavelength selected for absorption by the reaction product. The sensor interface <NUM> directs an incident beam from the light source through the optical portal in the sample interface <NUM>. The detector may be positioned at an angle such as <NUM>° to the optical portal to receive the light reflected back from the sample. The detector may be positioned adjacent to an optical portal on the other side of the sample from the light source to receive light transmitted through the sample. The detector may be positioned in another location to receive reflected and/or transmitted light.

The display <NUM> may be analog or digital. The display <NUM> may include a LCD, a LED, an OLED, a vacuum fluorescent, or other display adapted to show a numerical reading. Other displays may be used. The display <NUM> electrically communicates with the processor <NUM>. The display <NUM> may be separate from the measurement device <NUM>, such as when in wireless communication with the processor <NUM>. Alternatively, the display <NUM> may be removed from the measurement device <NUM>, such as when the measurement device <NUM> electrically communicates with a remote computing device, medication dosing pump, and the like.

In use, a liquid sample for analysis is transferred into the reservoir <NUM> by introducing the liquid to the opening <NUM>. The liquid sample flows through the channel <NUM>, filling the reservoir <NUM> while expelling the previously contained air. The liquid sample chemically reacts with the reagents deposited in the channel <NUM> and/or reservoir <NUM>.

The test sensor <NUM> is disposed adjacent to the measurement device <NUM>. Adjacent includes positions where the sample interface <NUM> is in electrical and/or optical communication with the sensor interface <NUM>. Electrical communication includes the transfer of input and/or output signals between contacts in the sensor interface <NUM> and conductors in the sample interface <NUM>. Optical communication includes the transfer of light between an optical portal in the sample interface <NUM> and a detector in the sensor interface <NUM>. Optical communication also includes the transfer of light between an optical portal in the sample interface <NUM> and a light source in the sensor interface <NUM>.

The processor <NUM> receives the measured temperature from the temperature sensor <NUM>. The processor <NUM> directs the signal generator <NUM> to provide an input signal to the sensor interface <NUM>. In an optical system, the sensor interface <NUM> operates the detector and light source in response to the input signal. In an electrochemical system, the sensor interface <NUM> provides the input signal to the sample through the sample interface <NUM>. The processor <NUM> receives the output signal generated in response to the redox reaction of the analyte in the sample as previously discussed.

The processor <NUM> determines the analyte concentration of the sample via the analyte concentration estimation algorithm <NUM> in this example. One of the inputs to the analyte concentration estimation algorithm <NUM> is temperature, which is used to correct for the effect of differences in temperature on the sensor output signals.

The processor <NUM> in this example is operable to execute the temperature selection routine <NUM> that selects the temperature for the analyte concentration estimation algorithm <NUM>. The processor <NUM> also executes the temperature estimation algorithm <NUM> that is capable of estimating the ambient temperature with sufficient accuracy that it can reliably detect disequilibration and be used by the analyte concentration estimation algorithm <NUM> to calculate an accurate result. The temperature selection routine <NUM> also includes logic to determine when a large discrepancy between the estimated temperature and the temperature measured by the thermistor of the temperature sensor <NUM> is caused by a damaged sensor rather than disequilibration, allowing an error code to be displayed on the display <NUM> rather than an incorrect result from executing the analyte concentration estimation algorithm <NUM> with the temperature output by a damaged temperature sensor. Alternatively, an error code can refer to an error index number or to an actual message displayed on the display <NUM> and/or recorded in memory.

<FIG> are a flow diagram showing the temperature selection routine <NUM> in <FIG> that determines the temperature value to input into the analyte concentration estimation algorithm <NUM> in the example biosensor system <NUM>. The routine <NUM> is executed on a controller such as the processor <NUM> in <FIG>. Although it is better to use the estimated temperature when the thermistor is shifted by more than <NUM>° C, it is impossible to know with certainty when this situation has actually occurred. The only information available to the temperature selection routine <NUM> is the difference between the thermistor and the estimated temperature. The temperature selection routine <NUM> in <FIG> therefore follows certain temperature compensation logic to determine whether to use the estimated temperature, the temperature from the thermistor, or return an error message.

The routine <NUM> first measures all the test signals (<NUM>). This includes applying an input signal from the signal generator <NUM> to the electrodes in the test sensor <NUM>. The processor <NUM> reads the output signal from the biosensor interface <NUM>. The test signal measurement step also includes the processor <NUM> reading a signal from the temperature sensor <NUM> in <FIG> and determining the measured ambient temperature (T). The processor <NUM> estimates the ambient temperature (T Est) based on the output signals read from the biosensor interface <NUM> and other inputs required by the temperature estimation algorithm <NUM> (<NUM>). The processor <NUM> then determines the absolute value of the difference between the estimated ambient temperature and the temperature measured by the temperature sensor <NUM> (T Est Residual) (<NUM>).

The processor <NUM> then determines whether the absolute value of the difference between the estimated ambient temperature and the temperature measured by the temperature sensor <NUM> exceeds the largest allowed temperature compensation value (MaxComp) (<NUM>). If the difference exceeds the largest allowed temperature compensation, the processor <NUM> reports an error code for the test sensor <NUM> (<NUM>). In this example, the largest variation between the estimated temperature and the temperature measured from the sensor <NUM> is <NUM>° C, but other values may be used such as between <NUM>° C to <NUM>° C. Such a large difference indicates that the system <NUM> is unlikely to be in true disequilibrium and thus it is safer to report an error code that the test sensor <NUM> is malfunctioning.

If the difference is under the largest allowed temperature compensation value, the processor <NUM> then determines whether the measured temperature from the temperature sensor <NUM> and the estimated temperature are both within a room temperature range (<NUM>). In this example, the room temperature range is between <NUM>° C and <NUM>° C (e.g., <NUM> ±<NUM>), but other range values may be used. For example, the room temperature range could be defined differently depending on the expected typical use environment. Thus the high temperature of the room temperature range may be between <NUM> and <NUM>° C and the low temperature may be between <NUM>° C and <NUM>° C. If both the estimated temperature and the measured temperature are outside of the room temperature range in opposite direction, the processor <NUM> then reports an error code for the test sensor <NUM> (<NUM>).

If the temperature and the estimated temperature are both within the room temperature range, the processor <NUM> determines whether the measured temperature is within the room temperature range and determines if the difference between the measured temperature and estimated temperature is greater than a residual error limit threshold value (<NUM>). If the measured temperature is within the room temperature range, but the difference is greater than the residual error limit threshold value, the processor <NUM> reports an error code for the test sensor <NUM> (<NUM>). In this example, the residual error limit threshold value is <NUM>° C, and differences above <NUM>° C are an indication of a damaged test sensor, so an error code is reported. Depending on the system, the range of the residual error limit threshold value may be between <NUM>° C and <NUM>° C.

If the difference is less than the residual error limit threshold value, the processor <NUM> determines whether both the temperature and the estimated temperature are greater than the highest temperature of the room temperature range, and whether the difference between the estimated temperature and the measured temperature are greater than an extreme residual error limit threshold value (<NUM>). If these conditions are met, the processor <NUM> reports an error code for the test sensor <NUM> (<NUM>). In this example, the highest temperature of the room temperature range is <NUM>° C and the extreme residual error limit threshold value is <NUM>° C.

If these conditions are not met, the processor <NUM> determines whether both the measured temperature and the estimated temperature are less than the lowest temperature of the room temperature range, and whether the difference between the measured temperature and the estimated temperature is greater than the extreme residual error limit threshold value (<NUM>). In this example, the lowest temperature of the room temperature range is <NUM>° C and the extreme residual error limit threshold value is <NUM>° C for both steps <NUM> and <NUM>. Depending on the system, the range of the extreme residual error limit threshold value may be between <NUM>° C and <NUM>° C for both steps <NUM> and <NUM>. If these conditions are met, the processor <NUM> reports an error code for the test sensor <NUM> (<NUM>). In this example, the extreme residual error limit threshold value is slightly wider than residual error limit threshold value since the estimated temperature may be slightly less reliable in extreme conditions. However, the same value may be used for both of these thresholds in some examples.

If the above conditions are not met, the processor <NUM> determines whether: a) the measured temperature is less than the lowest temperature of the temperature range and the estimated temperature is greater or equal to a low adjusted temperature value; or b) whether the measured temperature is greater than the highest temperature of the room temperature range and the estimated temperature is less than or equal to a high adjusted temperature value (<NUM>). This step determines whether the temperature measured by the thermistor is at an extreme value while the estimated temperature is at room temperature, a combination that is consistent with a disequilibrated meter recently brought inside from a hot or cold environment. When the meter is disequilibrated, a small amount of heat is transferred to or from the sensor, causing the expected temperature of a sensor tested in a hot meter to shift up and the expected temperature of a sensor tested in a cold meter to shift down. In this example, the high and low adjusted temperature values are <NUM>° C more than the high and low temperatures of the room temperature range, thus the low adjusted temperature value is <NUM>° C and the high adjusted temperature value is <NUM>° C. If these conditions are not met, the processor <NUM> uses the temperature from the temperature sensor <NUM> for the temperature input to the analyte concentration estimation algorithm <NUM> (<NUM>).

If the conditions in step <NUM> are met, the processor <NUM> compares the absolute difference between the measured temperature and the estimated temperature with an equilibrium threshold value (<NUM>). In this example, the equilibrium threshold value is <NUM>° C. The example <NUM>° C threshold equilibrium value can be adjusted depending on the accuracy of the temperature estimation algorithm and the desired balance of risk between a false negative and a false positive result. The threshold equilibrium value may be between <NUM>° C and <NUM>° C. If the difference is greater than the equilibrium threshold value, the processor <NUM> uses the estimated temperature for the temperature input to the analyte concentration estimation algorithm <NUM> (<NUM>). If the absolute difference is less than the equilibrium threshold value, the processor <NUM> uses the temperature from the temperature sensor <NUM> for the temperature input to the analyte concentration estimation algorithm <NUM> (<NUM>).

<FIG> is a graph showing the correlation between the estimated temperature and the measured temperature from the temperature sensor and different logic states as a result. A first area <NUM> represents the situations where the measured temperature is used for the temperature input to the analyte concentration estimation algorithm <NUM>. Two areas <NUM> and <NUM> represent the situations where the estimated temperature is used for the temperature input to the analyte concentration estimation algorithm <NUM>. The areas <NUM> and <NUM> are bounded by lines <NUM> and <NUM> that represent the boundaries of the room temperature range. The areas <NUM> and <NUM> are further bounded by lines <NUM> and <NUM> that represent the lower bounds of the equilibrium boundary. Two additional areas <NUM> and <NUM> represent situations where an error message is returned to indicate the temperature sensor <NUM> has been damaged.

In this example, the estimation of the temperature is determined by the temperature estimation algorithm <NUM>. The temperature estimation algorithm <NUM> is derived from multiple regression analysis of input variables. Such an algorithm may be developed by performing the multiple regression based on different parameters for a specific test sensor as well as other measured signals. In this example, a multiple regression equation was developed that accurately estimates the ambient temperature using electrical signals generated from the test sensor during a glucose test (<NUM> standard deviation).

A set of training data taken from the large database of current profiles from properly equilibrated meters tested in a wide range of conditions was used to develop an equation with different terms from the parameters shown in the table in <FIG>. The accuracy of this temperature estimation algorithm was assessed with a set of <NUM>,<NUM> laboratory study readings and <NUM>,<NUM> internal clinical study readings obtained from normally filled sensors tested with equilibrated meters. Summary statistics of the comparison between the temperature measured by a temperature sensor and the output of the example temperature estimation algorithm are included in the table shown in <FIG> shows a table of summary statistics for the percent error of glucose results calculated with the thermistor and with the estimated temperature using equilibrated meters. Though the temperature estimation algorithm is accurate, using this estimate when the meter is equilibrated and the thermistor is correct would cause performance to become slightly worse.

In this example, the equation for estimating temperature (in °C) includes multiple terms based on the parameters in <FIG> and a constant. The temperature estimate is calculated as the sum of the terms and the constant. Signals are measured during six potential pulses at the main glucose working electrode (M pulses) and four potential pulses at a bare "G" electrode in the front of the strip test chamber (G pulses). At the end of the test, a single high potential pulse is applied to the G electrode to measure signals correlated with hematocrit (H pulse). This potential input signal sequence pattern is illustrated in <FIG> shows a series of six main pulses <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and <NUM>. <FIG> shows four pulses <NUM>, <NUM>, <NUM>, and <NUM> at the bare G electrode. <FIG> also shows an input signal <NUM> to measure signals correlated with the hematocrit.

Current signals measured during one of the six M pulses are designated as MxArray(y), where x is the pulse number (<NUM> - <NUM>) and y is the measurement number within the pulse. The same convention is used for the four G pulses (i.e., GxArray(y)). Four signals are measured during the single H pulse: HArray(y). The parameters are listed in the table shown in <FIG>. Each term in the estimation equation is the product of a coefficient and an index parameter constructed from one or more measured current values.

Of course other procedures to determine estimations of temperature may be used such as by artificial neural networks with appropriate machine learning algorithms. In this example, the temperature estimation algorithm <NUM> provides accurate results in studies representing a wide range of temperatures, glucose concentration, and hematocrit contents.

Three studies were conducted with meters stored at cold or warm temperatures and then tested at room temperature (~<NUM>). For the disequilibrated meters, results calculated with the incorrect thermistor values were inaccurate, particularly when the meter was colder than the test environment. Results calculated with the estimated temperature, however, were accurate in all cases. Successfully identifying when the meter is disequilibrated and then using the estimated temperature instead of the measured temperature to calculate glucose is therefore highly desirable. <FIG> is a graph of the plots of the error of the outputs of the analyte concentration estimation algorithm using measured temperatures from the tests conducted with meters in a wide range of equilibration states. <FIG> is a graph of the plots of the error of the outputs of the analyte concentration estimation algorithm using estimated temperatures from the tests conducted with meters in a wide range of equilibration states. 7C is a graph of the plots of the error of the outputs of the analyte concentration estimation algorithm using the final selected temperature (either estimated temperature or measured temperature) from the tests conducted with meters in a wide range of equilibration states. In <FIG> and <FIG>, the "*" symbol represents outputs from hot meters, the "o" symbol represents outputs from equilibrated meters, and the "x" symbols represents outputs from cold meters.

<FIG> show that when meters are actually disequilibrated, the glucose results calculated with the estimated temperature are much more accurate than glucose results calculated with the thermistor. <FIG> shows that the algorithm logic worked well and correctly switched to the estimated temperature when severe disequilibration occurred, preventing the severely inaccurate results seen in <FIG>.

Applying the disequilibration logic produces a dramatic improvement in performance for meters that have not been allowed to equilibrate after being brought from a cold or hot environment while maintaining performance with equilibrated meters. <FIG> shows a table of summary data from results of studies for equilibrated meters, cold meters and hot meters in relation to the measured temperature, the estimated temperature from the example estimated temperature algorithm, and the temperature selection routine <NUM> in <FIG>.

As explained above, in addition to disequilibrated meters, the temperature selection routine <NUM> can determine damaged test sensors and therefore avoid using data from a damaged test sensor for an analyte concentration. Many studies have been conducted with damaged or perturbed test sensors. Such damaged test sensors produce abnormal current signals, which can affect the accuracy of the temperature estimate. The temperature selection routine <NUM> therefore determines if a discrepancy between the estimated and measured temperature is greater than a threshold level and that it is likely due to error in the estimated temperature rather than the measured temperature, indicating an error from the test sensor. Thus, the discrepancy is used as an error detection tool for malfunctions of the test sensor.

This logic dramatically improves the performance of meters that are actually not equilibrated while also improving the error detection success rate when test sensor damage has occurred and maintaining current performance when the test sensor is normal.

Claim 1:
An analyte concentration sensor system (<NUM>) for measuring an analyte of a fluid sample of a user, the sensor system (<NUM>) comprising:
a biosensor interface (<NUM>) operable to be connected to a test sensor (<NUM>) holding the fluid sample;
a thermistor based temperature sensor (<NUM>) configured to measure ambient temperature;
a controller coupled to the biosensor interface (<NUM>) and the temperature sensor (<NUM>), the controller being configured to:
generate an input signal to the biosensor interface (<NUM>);
read an output signal from the biosensor interface (<NUM>);
determine a measured ambient temperature from the temperature sensor (<NUM>);
execute a temperature estimation algorithm to determine an estimated ambient temperature;
determine an absolute difference between the estimated ambient temperature and the measured ambient temperature;
select one of the estimated ambient temperature or the measured ambient temperature, the selection based on the estimated ambient temperature, the measured ambient temperature, and the absolute difference between the estimated ambient temperature and the measured ambient temperature when the absolute difference is less than a largest allowed temperature compensation value;
provide the selected estimated ambient temperature or measured ambient temperature as a temperature input to an analyte concentration determination algorithm;
determine an analyte concentration from executing the analyte concentration determination algorithm; and
report an error code for the test sensor (<NUM>) if the absolute value of the difference between the estimated ambient temperature and the measured ambient temperature is greater than the largest allowed temperature compensation value.