Compensation system and method for thermistor sensing in analyte biosensor

Abstract

To provide a procedure that addresses a risk of inaccurate glucose results a non-equilibrated meter relying solely on a thermistor-based temperature measurement causes, to provide a system that compares an estimation temperature with the measurement temperature to provide information on whether the meter is properly equilibrated, to provide a system that determines analyte concentration using the estimation temperature from a temperature estimation algorithm even if non-equilibration is detected, and to provide a system that compares the estimation temperature with the measurement temperature to provide information on whether a test sensor is damaged.SOLUTION: An analyte concentration sensor system includes: a bio-sensor interface to be connected to a test sensor including a body fluid sample; a thermistor-based temperature sensor; and a controller. The controller is configured to: generate and read a signal via the bio-sensor interface; determine both a measurement ambient temperature and an estimation ambient temperature; compare these temperatures; and select any of them based on a difference to enhance measurement accuracy.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] (Related Applications) This application claims priority to U.S. Provisional Patent Application No. 62 / 850,841, filed May 21, 2019, which is incorporated by reference in its entirety.

[0002] The present invention relates generally to biosensors for analyte concentration (e.g., blood glucose levels), and more particularly to a system for detecting failure of a test sensor in providing a temperature value from either an estimated or measured temperature in the process of determining an analyte concentration. [Background technology]

[0003] The quantitative determination of analytes in body fluids is of great importance for the diagnosis and maintenance of certain physiological conditions. For example, persons with diabetes (PWD) may experience a high level of glutamate in their body fluids. The course values ​​are checked frequently. The results of such tests can be used to prescribe glucose intake at meals and / or determine whether insulin or other medications are required. PWDs typically use a measurement device (e.g., a blood glucose meter) that calculates the glucose concentration in a fluid sample from the PWD. The fluid sample is then collected on a test sensor that is received by the measurement device. Failure to take corrective action can have serious medical consequences for the patient.

[0004] One method for monitoring blood glucose levels in PWDs is the use of portable test devices. Because these devices are portable, users can conveniently measure their blood glucose levels anywhere. One type of device analyzes a blood sample using an electrochemical test sensor. The user obtains a blood sample using a lancet and deposits it into a reservoir within the test sensor. The electrochemical test sensor typically contains electrodes that, when paired with a meter, electrically measure the blood sample's response, thereby determining the analyte concentration. Therefore, users must carry a dedicated meter device to determine the analyte value of the blood sample.

[0005] Typically, a meter applies an input signal (e.g., a gated amperometric signal) to the electrodes of the test sensor. Conventional test sensors and meters typically use glucose concentration estimation algorithms that determine a correlation between measured current outputs from a blood sample and predetermined analyte concentration values ​​that correlate with these outputs. These predetermined values ​​are determined by a lab instrument, such as a YSI lab instrument.

[0006] The chemical reactions employed in the test sensor of any amperometric blood glucose monitoring (BGM) system are affected by temperature. Therefore, the measured temperature value is an important input to the glucose estimation algorithm of such systems. In known systems, temperature is measured using a thermistor-based temperature sensor. The thermistor for the temperature sensor is typically located within the meter. Due to the meter's thermal mass, the thermistor cannot immediately respond to changes in ambient temperature, which can distort the temperature measurement. When a BGM meter is moved from one environment to another, the meter requires a certain amount of time to equilibrate to the new environment, during which time the thermistor value will not accurately reflect the actual temperature. In the complex glucose estimation algorithm employed in gated amperometric meters, temperature is included in many terms of various compensation equations. Therefore, an inaccurate thermistor-based temperature value can lead to erroneous results.

[0007] Therefore, the temperature estimate from the thermistor may not be accurate unless the meter has been equilibrated to its environment. There is a risk that the algorithm will use an incorrect temperature value due to a thermistor error, which could result in inaccurate glucose readings. One way to address the unbalanced environment is to use an estimated temperature based on other parameters not derived from the thermistor. However, using this estimated temperature poses another risk: a damaged sensor could provide an incorrect temperature estimate. Therefore, a large discrepancy between the estimated temperature and the thermistor temperature could indicate a damaged sensor in addition to the meter not being balanced. If the sensor is damaged, the correct response is to report an error code. However, if the damaged sensor is not detected, the meter will attempt to calculate glucose using the temperature reading from the damaged sensor, which could result in inaccurate glucose readings. Summary of the Invention [Problem to be solved by the invention]

[0008] Therefore, there is a need for a procedure to address the risk that unbalanced meters that rely solely on thermistor-based temperature measurements will provide inaccurate glucose results. Furthermore, there is a need for a system that compares estimated and measured temperatures to provide information regarding whether the meter is properly balanced. Furthermore, there is a need for a system that can determine analyte concentration using estimated temperatures from a temperature estimation algorithm even when unbalance is detected. Furthermore, there is a need for a system that compares estimated and measured temperatures to provide information regarding whether the test sensor is damaged. [Means for solving the problem]

[0009] According to one embodiment, an analyte concentration sensor system for measuring an analyte in a bodily fluid sample of a user is disclosed. The sensor system includes a biosensor interface operable to connect to a test sensor holding the bodily fluid sample. A thermistor-based temperature sensor is configured to measure temperature. A controller is coupled to the biosensor interface and the temperature sensor. The controller is operable to generate input signals to the biosensor interface and read output signals from the biosensor interface. The controller determines a measured temperature from the temperature sensor. The controller determines an estimated temperature by executing a temperature estimation algorithm. The controller determines a difference between the estimated temperature and the measured temperature. The controller selects one of the estimated temperature and the measured temperature based on the estimated temperature, the measured temperature, and the difference between the estimated temperature and the measured temperature. The controller provides the selected estimated temperature or the measured temperature as a temperature input to the analyte concentration determination algorithm.

[0010] Another example is a method for determining the suitability of a temperature measurement from a thermistor temperature sensor in an analyte meter. The analyte meter includes a biosensor interface operable to connect to a test sensor holding a bodily fluid sample, and a controller. An input signal to the interface is generated when the biosensor interface is connected to the test sensor with the bodily fluid sample. An output signal from the test sensor is determined. A measured temperature from the thermistor-based temperature sensor is determined. An estimated temperature from a temperature estimation algorithm is determined via the controller. A difference between the estimated temperature and the measured temperature is determined via the controller. One of the estimated temperature and 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 the measured temperature is provided as a temperature input to an analyte concentration determination algorithm.

[0011] Another example is an analyte concentration sensor system for measuring an analyte in a bodily fluid sample of a user. The sensor system includes a biosensor interface operable to connect to a test sensor holding the bodily fluid sample. The system includes a thermistor-based temperature sensor configured to measure temperature. The system includes a biosensor interface and The biosensor includes a controller coupled to the temperature sensor. The controller is operable to generate an input signal to the biosensor interface and to read an output signal from the biosensor interface. The controller is operable to determine a measured temperature from the temperature sensor and to determine an estimated temperature by executing a temperature estimation algorithm. The controller determines an absolute value of a difference between the estimated temperature and the measured temperature. The controller determines a failure of the test sensor based on the estimated temperature, the measured temperature, and the absolute value of the difference between the estimated temperature and the measured temperature.

[0012] Another example is a method for determining a fault in a test sensor connected to an analyte meter. The analyte meter includes a biosensor interface operable to connect to a test sensor holding a bodily fluid sample, and a controller. An input signal to the interface is generated when the interface is connected to the test sensor with the bodily fluid sample. An output signal from the test sensor is determined. A measured temperature from a thermistor-based temperature sensor is determined. An estimated temperature from a temperature estimation algorithm is determined via the controller. An absolute value of a difference between the estimated temperature and the measured temperature is determined. A fault in the test sensor is determined based on the estimated temperature, the measured temperature, and the absolute value of the difference between the estimated temperature and the measured temperature.

[0013] Further aspects of the present invention will become apparent to those skilled in the art upon reading the detailed description of the various embodiments set forth in conjunction with the drawings, which are briefly described below. [Brief explanation of the drawings]

[0014] [Figure 1]FIG. 1 is a block diagram illustrating an example of a biosensor system for determining an analyte concentration from a bodily fluid sample, according to one embodiment.

[0015] [Figure 2A] FIG. 2A is a flow diagram illustrating a routine executed to select a temperature value for use in an analyte concentration estimation algorithm executed by the biosensor system of FIG. 1, according to one embodiment. [Figure 2B] FIG. 2B is a flow diagram illustrating a routine executed to select a temperature value for use in an analyte concentration estimation algorithm executed by the biosensor system of FIG. 1, according to one embodiment.

[0016] [Figure 3] FIG. 3 is a state diagram illustrating the response of the routines of FIGS. 2A and 2B, showing the states that use measured temperatures, the states that use estimated temperatures, and the states that return error messages.

[0017] [Figure 4] 1 is a table showing parameters in an example of a temperature estimation algorithm.

[0018] [Figure 5A] 1 is a summary table showing the output of the temperature estimation algorithm compared to the temperature measured by the thermistor-based sensor.

[0019] [Figure 5B] 1 is a summary table showing the accuracy of the output of the analyte concentration estimation algorithm using the temperature measured by the thermistor-based sensor and the accuracy of the output of the temperature estimation algorithm when the study was performed with the meter in an equilibrated state.

[0020] [Figure 6] 1 is a graph illustrating an example of an input signal sequence for a temperature estimation algorithm.

[0021] [Figure 7A] 1 is a graph plotting the output error when an analyte concentration estimation algorithm is run using measured temperatures obtained from tests in which the meter was subjected to a wide range of equilibration conditions.

[0022] [Figure 7B] 10 is a graph plotting the output error when an analyte concentration estimation algorithm is run using estimated temperatures obtained from tests in which the meter was subjected to a wide range of equilibration conditions.

[0023] [Figure 8] 1 is a graph plotting the output error when the analyte concentration estimation algorithm is run using the final selected temperature (estimated or measured temperature) from tests in which the meter was subjected to a wide range of equilibration conditions.

[0024] [Figure 9] 1 is a summary table showing the accuracy of the analyte concentration estimation algorithm output when the meter is tested in three equilibration states (cold, hot, and equilibrated) and comparing results calculated at temperatures measured by a thermistor-based sensor, results calculated at temperatures estimated by an algorithm using signals from the test sensor, and results calculated at temperatures selected by logic based on the difference between the thermistor temperature and the estimated temperature. DETAILED DESCRIPTION OF THE INVENTION

[0025] While the present invention is susceptible to various modifications and variations, specific embodiments have been shown by way of example in the drawings. A detailed description of specific embodiments follows. However, it should be understood that the invention is not limited to the particular forms disclosed. Rather, the invention includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.

[0026] The present disclosure relates to an analyte concentration measurement system that estimates ambient temperature using a non-thermistor signal by employing temperature equilibration logic. The difference between the estimated temperature and the measured temperature from the thermistor is compared to a specified threshold to determine which of three actions to take: 1) calculate the analyte concentration normally using the thermistor signal, assuming the meter is equilibrated and the test sensor signal is valid; 2) calculate the analyte concentration using the estimated temperature, assuming the meter is not equilibrated to ambient conditions and using the estimated temperature would produce more accurate results; or 3) report an error, assuming the test sensor is degraded and the signal is invalid.

[0027] The logic governing the three possible actions is as follows: If there is good agreement between the estimated temperature and the thermistor-measured temperature, both results are considered accurate, and the thermistor-measured temperature is used to calculate the analyte concentration because it provides the most reliable value under normal circumstances. If there is a large discrepancy between the thermistor temperature and the estimated temperature, there are two possible causes: 1) the thermistor-measured temperature is inaccurate because the meter is not equilibrated to the ambient environment, or 2) the sensor signal used to make the calculation is inaccurate, resulting in an inaccurate estimated temperature, either because the sensor is damaged or the sample was disturbed during the test. The decision to issue a corrected result or return an error message is based on understanding the most likely relationship that exists between the thermistor-measured temperature and the estimated temperature in each of the two possible scenarios. Since most glucose concentration tests are performed at room temperature, if the thermistor-measured temperature is an extreme value and the estimated temperature is normal, the most likely cause is non-equilibration. In this case, the estimated temperature is used to calculate the analyte concentration. If the thermistor temperature reading is normal and the estimated temperature is extreme, the output signal waveform from the test sensor is likely abnormal and an error should be reported.

[0028] 1 is a schematic diagram of a biosensor system 100 for determining an analyte concentration in a biological fluid sample. The biosensor system 100 includes a measurement device 102 and a test sensor 104. The measurement device 102 and the test sensor 104 can be implemented in any analytical instrument, including benchtop, portable, or handheld devices. The measurement device 102 and test sensor 104 may be adapted to implement an electrochemical sensor system, an optical sensor system, a combination thereof, or the like. The biosensor system 100 determines the analyte concentration from the output signal using a glucose estimation algorithm that uses an input temperature to correct the temperature output. A temperature selection routine determines whether to use the temperature measured by the thermistor sensor, the estimated temperature, or return an error message. As described below, this routine improves the measurement performance of the biosensor system 100 when determining the analyte concentration of a sample by inputting a more accurate temperature into the analyte concentration estimation algorithm.

[0029] Biosensor system 100 may be used to determine analyte concentrations, including concentrations 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 contemplated that multiple analytes may also be determined. Analytes may be present in, for example, whole blood samples, serum samples, plasma samples, other bodily fluids such as urine, and non-bodily fluids. Thus, one example of an analyte concentration estimation algorithm is a glucose concentration estimation algorithm implemented by biosensor system 100. As used herein, the term "concentration" refers to analyte concentration, activity (e.g., enzymes and electrolytes), potency (e.g., antibodies), or any other measured concentration used to measure the desired analyte. While biosensor system 100 is shown as having a particular configuration, biosensor system 100 may have other configurations, including additional components.

[0030] The test sensor 104 has a base 106 that defines a reservoir 108 and a channel 110 with an opening 112. The reservoir 108 and channel 110 may be covered by a vented lid. The reservoir 108 defines a partially enclosed volume. The reservoir 108 may include a composition that aids in retaining a liquid sample, such as a water-swellable polymer or a porous polymer matrix. Reagents may be loaded into the reservoir 108 and / or channel 110. The reagents may include one or more enzymes, binders, mediators, and other species. The reagents may include chemical indicators for an optical system. The test sensor 104 may further include a sample interface 114 adjacent to the reservoir 108. The sample interface 114 may partially or completely surround the reservoir 108. The test sensor 104 may have other configurations.

[0031] In an optical system, the sample interface 114 has an optical portal or optical aperture for observing the sample. The optical portal may be covered with an essentially transparent material. The sample interface may have an optical portal on either side of the reservoir 108.

[0032] In an electrochemical system, the sample interface 114 has a conductor connected to a working electrode and a conductor connected to a counter electrode. These electrodes may be in substantially the same plane or in different planes. The electrodes may be disposed on a surface of the base 106 that forms the reservoir 108. The electrodes may extend or protrude into the reservoir 108. A dielectric layer may partially cover the conductors and / or the electrodes. The sample interface 114 may have other electrodes or conductors.

[0033] Measurement device 102 includes electrical circuitry 116 coupled to a sensor interface 118 and a display 120. Electrical circuitry 116 includes a processor 122 coupled to a signal generator 124, a temperature sensor 126, and a storage medium 128. In this embodiment, temperature sensor 126 operates by providing an electrical signal to a thermistor and reading an output signal from the thermistor that is proportional to the ambient temperature.

[0034] The signal generator 124 provides an input electrical signal to the sensor interface 118 in response to the processor 122. In an optical system, the input electrical signal may be used to operate or control detectors and light sources within the sensor interface 118. In an electrochemical system, the input electrical signal may be transmitted by the sensor interface 118 to the sample interface 114 for application to the biological fluid sample. The input electrical signal may be a potential or current, and may be fixed, variable, or a combination thereof. A combination of fixed and variable may be the application of an AC signal with an offset DC signal. The input electrical signal may be applied as a single pulse, multiple pulses, in a sequence, or in a cycle, such as a gated amperometric signal. The signal generator 124 may also function as a generator and recorder, recording the output signal from the sensor interface.

[0035] The temperature sensor 126 determines the temperature of the sample in the reservoir of the test sensor 104 based on the output signal from the thermistor in the sensor 126. As described below, the temperature of the sample may be estimated by calculation from the output signal(s), time, and non-temperature signals, such as the ratio between the signals. The estimated temperature may be the same as or similar to a measurement of the ambient temperature or a measurement of the temperature of the device implementing the biosensor system. The temperature may be measured using a separate temperature-sensing device.

[0036] The storage medium 128 may be a magnetic memory, an optical memory, a semiconductor memory, or other storage medium, etc. The storage medium 128 may be a fixed memory device or a removable memory device such as a remotely accessed memory card.

[0037] The processor 122 performs analyte analysis and data processing using computer-readable software code and data stored in the storage medium 128. The processor 122 may initiate analyte analysis in response to, for example, the presence of the test sensor 104 in the sensor interface 118, the application of a sample to the test sensor 104, user input, etc. The processor 122 instructs the signal generator 124 to input an electrical signal to the sensor interface 118. The processor 122 receives an output signal from the temperature sensor 126 that is linked to the temperature of the sample. The processor 122 receives output signal(s) from the sensor interface 118. The output signal(s) is generated in response to a reaction of the analyte in the sample. The output signal(s) may be generated using an optical system, an electrochemical system, or the like. The processor 122 determines a compensated analyte concentration from the output signal using a glucose estimation algorithm, as described above. The analyte analysis result may be output to the display 120 and stored in the storage medium 128.

[0038] The correlation equation between the analyte concentration and the output signal may be represented graphically, mathematically, or by a combination thereof. The correlation equation may include one or more index functions. The correlation equation may be represented, for example, by a program number (PNA) table or another look-up table stored in the storage medium 128. Constants and weighting factors may also be stored in the storage medium 128. Instructions for performing the analyte analysis may be provided by computer-readable software code stored in the storage medium 128. The code may be object code or any other code that describes or controls the functions described herein. One or more data processing steps may be performed within the processor 122 on data obtained from the analyte analysis, including determining decay rates, K constants, ratios, functions, etc. In this example, the storage medium 128 stores an analyte concentration estimation algorithm 130 that determines the analyte concentration from inputs, such as signals from the sensor interface 118. The storage medium further stores a temperature selection routine 132 that determines the temperature values ​​to input into the analyte concentration estimation algorithm 130. The storage medium 128 further stores a temperature estimation algorithm 134 that determines an estimated temperature value for the temperature selection routine 132 .

[0039] In an electrochemical system, the sensor interface 118 has contacts that connect or electrically communicate with conductors in the sample interface 114 of the test sensor 104. The sensor interface 118 transmits input electrical signals from the signal generator 124 via the contacts to connectors in the sample interface 114. The sensor interface 118 also transmits output signals from the sample to the processor 122 and / or the signal generator 124 via the contacts.

[0040] In light absorption and light generation optical systems, the sensor interface 118 includes a detector that collects and measures light. The detector receives light from the liquid sample through an optical portal in the sample interface 114. In light absorption optical systems, the sensor interface 118 also includes a light source, such as a laser or light-emitting diode. The incident beam can have a wavelength selected to be absorbed by the reaction products. The sensor interface 118 directs the incident beam from the light source through the optical portal in the sample interface 114. The detector can be positioned at an angle, such as 45 degrees, relative to the optical portal to receive reflected light from the sample. The detector can be positioned adjacent to the optical portal on the opposite side of the sample from the light source to receive light transmitted through the sample. The detector can also be positioned in other locations to receive reflected and / or transmitted light.

[0041] The display 120 may be analog or digital. The display 120 may include an LCD, LED, OLED, vacuum phosphor display, or other display adapted to show readings numerically. Other displays may also be used. The display 120 is in electrical communication with the processor 122. The display 120 may be separate from the measurement device 102, such as when communicating wirelessly with the processor 122. Alternatively, the display 120 may be detached from the measurement device 102, such as when the measurement device 102 is in electrical communication with a remote computing device, drug dosage infusion pump, or the like.

[0042] In use, a liquid sample for analysis is transferred to reservoir 108 by introducing it into opening 112. The liquid sample flows through channel 110, filling reservoir 108 and expelling any air previously contained therein. The liquid sample chemically reacts with reagents deposited within channel 110 and / or reservoir 108.

[0043] The test sensor 104 is positioned adjacent to the measurement device 102. "Adjacent" includes a position where the sample interface 114 is in electrical and / or optical communication with the sensor interface 118. "Electrical communication" includes the transmission of input and / or output signals between contacts in the sensor interface 118 and conductors in the sample interface 114. "Optical communication" includes the transmission of light between an optical portal in the sample interface 114 and a detector in the sensor interface 118. "Optical communication" also includes the transmission of light between an optical portal in the sample interface 114 and a light source in the sensor interface 118.

[0044] Processor 122 receives the measured temperature from temperature sensor 126. Processor 122 directs signal generator 124 to input a signal to sensor interface 118. In an optical system, sensor interface 118 operates a detector and a light source in response to this input signal. In an electrochemical system, sensor interface 118 inputs this signal to the sample via sample interface 114. Processor 122 receives an output signal generated in response to the redox reaction of an analyte in the sample, as described above.

[0045] In this example, processor 122 determines the analyte concentration of the sample via analyte concentration estimation algorithm 130. One of the inputs to analyte concentration estimation algorithm 130 is temperature, which is used to correct for the effect of differences between temperatures on the sensor output signal.

[0046] In this embodiment, processor 122 is operable to execute a temperature selection routine 132 that selects a temperature for analyte concentration estimation algorithm 130. Processor 122 also executes temperature estimation algorithm 134. Temperature estimation algorithm 134 is capable of estimating the ambient temperature with sufficient accuracy that it can reliably detect non-equilibration and be used by analyte concentration estimation algorithm 130 to calculate an accurate result. Temperature selection routine 132 also includes logic to determine when a large difference between the estimated temperature and the temperature measured by the thermistor in temperature sensor 126 is caused by a damaged sensor rather than a non-equilibration. This allows an error code to be displayed on display 120 rather than displaying an inaccurate result that would result from running analyte concentration estimation algorithm 130 at a temperature output by a damaged temperature sensor. Alternatively, "error code" may refer to an error index number or an actual message displayed on display 120 and / or stored in memory.

[0047] 2A and 2B are flow diagrams illustrating the temperature selection routine 132 of FIG. 1. The temperature selection routine 132 determines the temperature value to input into the analyte concentration estimation algorithm 130 in the biosensor system 100 of this example. The routine 132 executes on a controller, such as the processor 122 of FIG. 1. While it is preferable to use the estimated temperature if the thermistor temperature shifts by more than 3° C., it is impossible to know with certainty when this situation actually occurs. The only information available to the temperature selection routine 132 is the difference between the thermistor temperature and the estimated temperature. Therefore, the temperature selection routine 132 of FIGS. 2A and 2B follows specific temperature compensation logic to determine whether to use the estimated temperature, the temperature from the thermistor, or return an error message.

[0048] Routine 132 first measures (200) all test signals, which includes applying input signals from signal generator 124 to electrodes in test sensor 104. Processor 122 reads output signals from biosensor interface 118. The test signal measurement step further includes processor 122 reading signals from temperature sensor 126 of FIG. 1 to determine a measured ambient temperature (T). Processor 122 estimates (202) the ambient temperature (T Est) based on the output signals read from biosensor interface 118 and other inputs required by temperature estimation algorithm 134. Processor 122 then determines (204) the absolute value of the difference between the estimated ambient temperature and the temperature measured by temperature sensor 126 (T Est Residual).

[0049] The processor 122 then determines (206) whether the absolute value of the difference between the estimated ambient temperature and the temperature measured by the temperature sensor 126 exceeds a maximum allowable temperature compensation value (MaxComp). If this difference exceeds the maximum allowable temperature compensation value, the processor 122 reports (208) an error code for the test sensor 104. In this example, the difference between the estimated temperature and the measured temperature from the sensor 126 is a maximum of 22°C, although other values, such as values ​​between 15°C and 25°C, may be used. Such a large difference indicates that the system 100 is unlikely to be in a true unbalanced state, and therefore it is safer to report an error code indicating that the test sensor 104 has failed.

[0050] If this difference is less than the maximum allowable temperature compensation value, processor 122 determines (210) whether the measured temperature from temperature sensor 126 and the estimated temperature are both within the room temperature range. In this example, the room temperature range is between 17.5°C and 27.5°C (e.g., 22.5±5°C). However, other ranges of values ​​may be used. For example, the definition of the room temperature range may vary depending on the expected typical use environment. Thus, the high end of the room temperature range may be between 25°C and 30°C, and the low end may be between 13°C and 20°C. If the estimated and measured temperatures fall outside the room temperature range in opposite directions, the processor 122 reports (208) an error code for the test sensor 104.

[0051] If both the measured temperature and the estimated temperature are within the room temperature range, the processor 122 determines whether the measured temperature is within the room temperature range and whether the difference between the measured temperature and the estimated temperature is greater than the residual error limit threshold (212). If the measured temperature is within the room temperature range but the difference is greater than the residual error limit threshold, the processor 122 reports an error code for the test sensor 104 (208). In this example, the residual error limit threshold is 10°C, and an error code is reported because a difference of more than 10°C indicates that the test sensor is damaged. Depending on the system, the residual error limit threshold can range between 7°C and 15°C.

[0052] If the difference is less than the residual error limit threshold, processor 122 determines (214) whether both the measured temperature and the estimated temperature are greater than the maximum temperature in the room temperature range and whether the difference between the estimated temperature and the measured temperature is greater than the extreme residual error limit threshold. If these conditions are met, processor 122 reports (208) an error code for test sensor 104. In this example, the maximum temperature in the room temperature range is 27.5°C and the extreme residual error limit threshold is 12°C.

[0053] If these conditions are not met, processor 122 determines (216) whether both the measured temperature and the estimated temperature are below the minimum 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. In this example, the minimum temperature of the room temperature range is 17.5°C, and the extreme residual error limit threshold is 12°C for both steps 214 and 216. Depending on the system, the extreme residual error limit threshold may range between 7°C and 15°C for both steps 214 and 216. If these conditions are met, processor 122 reports (208) an error code for test sensor 104. In this example, the extreme residual error limit threshold is slightly wider than the residual error limit threshold because the estimated temperature may be slightly less reliable in extreme conditions. However, in some embodiments, the same value may be used for both thresholds.

[0054] If the above conditions are not met, processor 122 determines (218) whether a) the measured temperature is lower than the lowest temperature in the room temperature range and the estimated temperature is equal to or greater than the adjusted low temperature value, or b) the measured temperature is higher than the highest temperature in the room temperature range and the estimated temperature is equal to or less than the adjusted high temperature value. This step determines whether the estimated temperature is room temperature while the temperature measured by the thermistor has an extreme value. This combination is consistent with an unbalanced meter that has just been brought inside from a hot or cold environment. When a meter is unbalanced, less heat is transferred to or from the sensor, resulting in a higher expected temperature for a sensor tested with a high temperature meter and a lower expected temperature for a sensor tested with a low temperature meter. In this example, the adjusted high or low temperature value is 2.5°C higher or lower than the high and low temperatures in the room temperature range, respectively, so the adjusted low temperature value is 15°C and the adjusted high temperature value is 30°C. If the above conditions are not met, processor 122 uses 220 the temperature from temperature sensor 126 as the temperature input to analyte concentration estimation algorithm 130 .

[0055] If the conditions of step 218 are met, processor 122 compares 222 the absolute value of the difference between the measured temperature and the estimated temperature to a balancing threshold. In this example, the balancing threshold is 6° C. An exemplary balancing threshold of 6° C. is used to determine the accuracy of the temperature estimation algorithm and the risk of false positives. The equilibration threshold may be adjusted depending on the desired balance of risk between a negative result and a false positive result. The equilibration threshold may be between 3°C and 10°C. If the difference is greater than the equilibration threshold, processor 122 uses (224) the estimated temperature as the temperature input to analyte concentration estimation algorithm 130. If the absolute value of the difference is less than the equilibration threshold, processor 122 uses (222) the temperature from temperature sensor 126 as the temperature input to analyte concentration estimation algorithm 130.

[0056] 3 is a graph illustrating the correlation between estimated temperature and measured temperature from a temperature sensor and the resulting various logic states. A first region 300 illustrates a situation in which a measured temperature is used as the temperature input to the analyte concentration estimation algorithm 130. Two regions 310 and 312 illustrate a situation in which an estimated temperature is used as the temperature input to the analyte concentration estimation algorithm 130. Regions 310 and 312 are bounded by lines 302 and 304, which indicate the boundaries of the room temperature range. Regions 310 and 312 are further bounded by lines 314 and 316, which indicate the lower equilibration boundaries. Two additional regions 320 and 322 illustrate situations in which an error message is returned, indicating that the temperature sensor 126 is damaged.

[0057] In this example, temperature estimation is performed by a temperature estimation algorithm 134. The temperature estimation algorithm 134 is derived from a multiple regression analysis of input variables. Such an algorithm may be developed by performing multiple regression based on various parameters for a particular test sensor and other measurement signals. In this example, a multiple regression equation (standard deviation: 1.5°C) was developed that accurately estimates ambient temperature using the electrical signal generated by the test sensor during a glucose test.

[0058] Using a set of training data from a large database of current distributions from properly balanced meters tested over a wide range of conditions, we developed an equation containing various terms based on the parameters shown in the table in Figure 4. The accuracy of the temperature estimation algorithm was evaluated using 38,367 readings from a laboratory study and 12,796 readings from successfully filled sensors tested with balanced meters in a medical clinical study. Summary statistics comparing the temperature measured by the temperature sensor with the output of the temperature estimation algorithm of this example are shown in the table in Figure 5A. Figure 5B is a table showing summary statistics of the percentage error of glucose results calculated with the thermistor and the estimated temperature using a balanced meter. While the temperature estimation algorithm is accurate, performance is slightly worse when using this estimate when the meter is balanced and the thermistor temperature is correct.

[0059] In this example, the equation for estimating temperature (in degrees Celsius) includes several terms and constants based on the parameters in Figure 4. The temperature estimate is calculated as the sum of these terms and constants. Signals are measured during six potential pulses at the main glucose working electrode (M pulses) and four potential pulses at the front "G" electrode (G pulses) in the strip test chamber. At the end of the test, a signal correlating with hematocrit (H pulse) is measured by applying one high potential signal pulse to the G electrode. Figure 6 illustrates this input potential signal sequence pattern. Figure 6 shows a series of six main pulses 610, 612, 614, 616, 618, and 620. Figure 6 also shows four pulses 630, 632, 634, and 636 at the front "G" electrode. Figure 6 further illustrates input signal 640 for measuring a signal correlating with hematocrit.

[0060] The current signal measured during one of the six M pulses is called MxArray(y), where x is the pulse number (1 to 6) and y is the measurement number within the pulse. The four G pulses are called in the same way (i.e., GxArray(y)). Four signals are measured during one H pulse (HArray(y)). The parameters are as shown in the table in Figure 4. Each term in the estimation formula is a coefficient and an index parameter constructed from one or more measured current values. It is the product of

[0061] Of course, other procedures may be used to estimate temperature, such as using artificial neural networks with appropriate machine learning algorithms. In this example, the temperature estimation algorithm 134 provides accurate results in studies representing a wide range of temperatures, glucose concentrations, and hematocrit contents.

[0062] These studies were performed with meters stored at low or high temperatures and then tested at room temperature (~22°C). For unbalanced meters, the calculated results using inaccurate thermistor values ​​were inaccurate, especially when the meter was colder than the test environment. However, the calculated results using estimated temperatures were accurate in all cases. Therefore, it is highly desirable to successfully identify when a meter is unbalanced and calculate glucose using the estimated temperature rather than the measured temperature. Figure 7A is a plot of the output error when the analyte concentration estimation algorithm is run using measured temperatures obtained by testing the meter over a wide range of equilibration conditions. Figure 7B is a plot of the output error when the analyte concentration estimation algorithm is run using estimated temperatures obtained by testing the meter over a wide range of equilibration conditions. Figure 8 is a plot of the output error when the analyte concentration estimation algorithm is run using the final selected temperature (estimated or measured) obtained by testing the meter over a wide range of equilibration conditions. In Figures 7A, 7B and 8, "*" indicates the output of the high temperature meter, "o" indicates the output of the balancing meter and "x" indicates the output of the low temperature meter.

[0063] Figures 7A and 7B show that when the meter is actually unbalanced, the estimated temperature calculated glucose results are much more accurate than the thermistor calculated glucose results. Figure 8 shows that when severe unbalance occurs, the algorithm logic works well to correctly switch to estimated temperature, thereby successfully preventing the grossly inaccurate results seen in Figure 7.

[0064] Applying the unbalancing logic significantly improves the performance of meters that have not yet been balanced after being brought in from a cold or hot environment, while maintaining the performance of balanced meters. Figure 9 is a table showing summary data from a study of balanced, cold, and hot meters in relation to the measured temperatures, the estimated temperatures obtained by the temperature estimation algorithm of the present embodiment, and the temperature selection routine 132 of Figures 2A and 2B.

[0065] As described above, in addition to unbalanced meters, the temperature selection routine 132 can determine damaged test sensors and therefore avoid using data from damaged test sensors for analyte concentration. Many studies have been conducted using damaged or disturbed test sensors. These damaged test sensors produce abnormal current signals that can affect the accuracy of temperature estimation. Therefore, the temperature selection routine 132 determines whether the discrepancy between the estimated temperature and the measured temperature is greater than a threshold value and whether the discrepancy is likely due to an error in the estimated temperature rather than the measured temperature, i.e., an error due to the test sensor. In this way, the discrepancy is used as an error detector for test sensor failure.

[0066] This logic significantly improves the performance of meters that are not actually balanced, while increasing the success rate of error detection if the test sensor is damaged and maintaining current performance if the test sensor is good.

[0067] As used herein, the terms "component," "module," or "system" generally refer to computer-related entities, including hardware (e.g., circuits), The term "component" refers to a combination of hardware and software, software, or any entity related to an operating machine having one or more specific functions. For example, a "component" may be, but is not limited to, a process running on a processor (e.g., a digital signal processor), a processor, an object, an executable file, a thread of execution, a program, and / or a computer. By way of example, both an application running on a controller and the controller may be a component. One or more components may reside within a process and / or thread of execution, and components may be local to one computer and / or distributed among two or more computers. Furthermore, a "device" may be in the form of specially designed hardware, general-purpose hardware specialized by executing software that enables the hardware to have specific functions, software stored on a computer-readable medium, or a combination thereof.

[0068] While the present invention has been illustrated and described in one or more embodiments, equivalent variations and modifications are possible and will be apparent to those skilled in the art upon reading and understanding this specification and the accompanying drawings. Moreover, while a particular feature of the invention may be disclosed in only one of the embodiments, such feature may also be combined with one or more other features of other embodiments, if desired or advantageous for any particular application.

Claims

1. 1. An analyte concentration sensor system for measuring an analyte in a bodily fluid sample of a user, comprising: a biosensor interface operable to connect to a test sensor holding the bodily fluid sample; a thermistor-based temperature sensor configured to measure an ambient temperature; a controller coupled to the biosensor interface and the thermistor-based temperature sensor; The controller generating an input signal to the biosensor interface; reading an output signal from the biosensor interface; determining a measured ambient temperature from the thermistor-based temperature sensor; determining an estimated ambient temperature by executing a temperature estimation algorithm; determining an absolute value of the difference between the estimated ambient temperature and the measured ambient temperature; selecting either the estimated ambient temperature or the measured ambient temperature based on the estimated ambient temperature, the measured ambient temperature, and an absolute value of the difference between the estimated ambient temperature and the measured ambient temperature; 1. An analyte concentration sensor system operable to:

2. 1. A method for determining the adequacy of an ambient temperature measurement from a thermistor temperature sensor in an analyte meter, the analyte meter comprising a biosensor interface operable to connect to a test sensor holding a bodily fluid sample, and a controller, the method comprising: generating an input signal to the biosensor interface when the test sensor having the bodily fluid sample is connected; determining an output signal from the test sensor; determining a measured ambient temperature from a thermistor-based temperature sensor; determining an estimated ambient temperature from a temperature estimation algorithm via said controller; determining via the controller an absolute value of a difference between the estimated ambient temperature and the measured ambient temperature; and selecting, via the controller, either the estimated ambient temperature or the measured ambient temperature based on the estimated ambient temperature, the measured ambient temperature, and an absolute value of a difference between the estimated ambient temperature and the measured ambient temperature; A method comprising:

3. The method of claim 2 , wherein the analyte is glucose and the bodily fluid sample is blood.

4. The method of claim 2 , wherein the input signal is a gated current measurement pulse.

5. The method of claim 2 , wherein the temperature estimation algorithm includes input variables determined by multiple regression analysis.

6. The method of claim 2 , wherein the measured temperature is selected if the estimated temperature and the measured temperature are within a room temperature range.

7. 7. The method of claim 6, wherein the room temperature range includes an upper end of 25°C to 30°C and a lower end of 13°C to 20°C.

8. 3. The method of claim 2, wherein the estimated temperature is selected if the measured temperature is outside a room temperature range, the estimated temperature is less than an adjusted high temperature of the room temperature range and greater than an adjusted low temperature of the room temperature range, and an absolute value of the difference between the estimated temperature and the measured temperature exceeds an equilibrium threshold.

9. 9. The method of claim 8, wherein the room temperature range includes a high end of 25°C to 30°C and a low end of 13°C to 20°C, the adjusted high end is 27°C to 34°C, the adjusted low end is 11°C to 18°C, and the equilibrium threshold is 3°C to 10°C.

10. The method of claim 2 , further comprising reporting an error code for the test sensor if the absolute value of the difference between the estimated temperature and the measured temperature is greater than a maximum allowable temperature compensation value.

11. 3. The method of claim 2, further comprising reporting an error code for the test sensor if the measured temperature and the estimated temperature are outside a room temperature range in opposite directions.

12. 3. The method of claim 2, wherein an error code for the test sensor is reported if the measured temperature is within room temperature range and the absolute value of the difference between the estimated temperature and the measured temperature is greater than a residual error limit threshold.

13. 13. The method of claim 12, wherein an error code for the test sensor is reported if the measured temperature and the estimated temperature are greater than a maximum temperature in the room temperature range and the absolute value of the difference between the estimated temperature and the measured temperature is greater than an extreme residual error limit threshold.

14. 13. The method of claim 12, wherein an error code for the test sensor is reported if the measured temperature and the estimated temperature are lower than a minimum temperature of the room temperature range and the absolute value of the difference between the measured temperature and the estimated temperature is greater than an extreme residual error limit threshold.

15. providing the selected estimated temperature or the measured temperature as a temperature input to an analyte concentration determination algorithm; and determining the analyte concentration according to the analyte concentration determination algorithm; The method of claim 2 further comprising:

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