Systems and methods for background signal reduction in biosensors

Abstract

A method of operating an analyte device, the method comprising: receiving an analyte signal measured from an analyte sensor device having a sensor tail; generating adjusted analyte data based on the analyte signal, generating the adjusted analyte data including reducing a background signal in the analyte signal according to an offset signal; calculating an analyte value based on the adjusted analyte data; and displaying the analyte value on a display device.

Description

[0001] Citations of relevant applications

[0002] This application claims priority and benefit to U.S. Provisional Patent Application No. 63 / 050,532, filed July 10, 2020, with the United States Patent and Trademark Office, the entire contents of which are incorporated herein by reference. Technical Field

[0003] Embodiments of this disclosure relate to systems and methods for reducing background signals in biosensors (such as analyte sensors). Background Technology

[0004] Electrochemical biosensors offer low-cost, rapid assessment tools that can be used to meet patients' needs for managing their medical conditions outside of hospital and clinical settings. Some examples of such electrochemical biosensors include implantable analyte sensors, which can be used to monitor the levels of various analytes in a patient's body, such as monitoring glucose levels in diabetic patients. Information about the levels of these analytes allows for the management and control of the patient's condition, such as alerting diabetic patients when glucose levels are high, low, or trending higher or lower.

[0005] Current analysis provides a class of detection schemes for electrochemical biosensors, in which an electrical signal (e.g., current) generated under a controlled voltage or potential reflects the concentration of the analyte in solution. The measured electrical signal includes a background signal, which may include noise and interference from various sources, such as other substances reacting with the sensor besides the early sensor attenuation (ESA) and late sensor attenuation (LSA) effects frequently observed in similar electrochemical biosensors. Summary of the Invention

[0006] Embodiments of this disclosure relate to systems and methods for reducing one or more background signals in an analyte signal measured by a biosensor.

[0007] According to one embodiment of the present disclosure, a method of operating an analyte apparatus includes: receiving an analyte signal measured from an analyte sensor apparatus having a sensor tail; generating adjusted analyte data based on the transmitted analyte signal, wherein transmitting the adjusted analyte data includes reducing a background signal in the analyte signal according to an offset signal; calculating an analyte value based on the adjusted analyte data; and displaying the analyte value on a display device.

[0008] The method may also include: displaying trend indicators; displaying analyte levels; generating alerts; or controlling drug delivery devices.

[0009] Reducing background signal may include: subtracting the offset from the analyte signal to generate an offset correction signal; calculating multiple sensitivities from the offset correction signal, each sensitivity corresponding to a reference point among multiple analyte reference points; calculating the median of the sensitivities within a time window; calibrating the adjusted analyte data to the offset correction signal based on the median of the sensitivities; and pairing the adjusted analyte data with the reference points.

[0010] The offset can be calculated from the global time-varying background offset based on the time elapsed since the activation of the self-analyte sensor device, thereby calculating the offset correction signal.

[0011] This offset can be a time-invariant offset.

[0012] The analyte sensor device may include: a first working electrode at the tail of the sensor, the first working electrode having a first sensitivity; and a second working electrode at the tail of the sensor, the second working electrode having a second sensitivity lower than the first sensitivity.

[0013] The first working electrode may have a first active region on which a first number of catalysts are disposed, and the second working electrode may have a second active region on which a second number of catalysts are disposed, the surface area of ​​the second active region being smaller than the surface area of ​​the first active region.

[0014] Reducing the background signal may include: detecting an analyte signal from a first working electrode; detecting another analyte signal from a second working electrode; calculating the difference between the analyte signal and the other analyte signal; and calculating adjusted analyte data based on the difference between the analyte signal and the other analyte signal.

[0015] The method may also include calculating individual background shifts based on analyte signals, additional analyte signals, and the difference between analyte signals and additional analyte signals.

[0016] The second working electrode can be configured to measure the individual background current and to calculate the offset signal based on the individual background current.

[0017] The method may further include applying temperature correction to the analyte signal based on the temperature from a temperature sensor in the analyte sensor device.

[0018] The sensor tail can extend from the body of the analyte sensor device, and the analyte sensor device may include: a first working electrode on the sensor tail having a first sensing layer at a first position along the sensor tail; and a second working electrode on the sensor tail having a second sensing layer at a second position along the sensor tail adjacent to the first position.

[0019] The method may further include detecting a system fault of the analyte sensor device by the following steps: detecting an analyte signal from a first working electrode; detecting another analyte signal from a second working electrode; calculating one or more consistency measures between the analyte signal and the other analyte signal; comparing the one or more consistency measures with a threshold; and detecting a system fault of the analyte sensor device when the one or more consistency measures exceed the threshold.

[0020] System failures can be caused by late sensor attenuation (LSA).

[0021] The method may also include correcting system faults by: calculating an orthogonal fit between the analyte signal and another analyte signal; calculating a fixed offset based on the orthogonal fit; and correcting the analyte signal or another analyte signal based on the fixed offset.

[0022] The method may also include correcting system faults by: calculating an orthogonal fit between the analyte signal and another analyte signal; calculating a time-varying shift based on the orthogonal fit; and correcting the analyte signal or another analyte signal based on the time-varying shift.

[0023] According to one embodiment of the present disclosure, the analyzer device includes: a plurality of communication circuits; and a plurality of processing circuits having a memory storing instructions that, when executed by the processing circuits, cause the processing circuits to: receive an analyte signal measured from an analyte sensor device having a sensor tail, the analyte signal being received via the communication circuits; generate adjusted analyte data based on the analyte signal, the analyte signal including instructions to cause the processing circuits to reduce a background signal in the analyte signal according to an offset signal; calculate an analyte value based on the adjusted analyte data; and display the analyte value on a display device.

[0024] The memory can further store instructions that, when executed by the processing circuitry, cause the processing circuitry to: display trend indicators; display analyte levels; generate alarms; or control the drug delivery device.

[0025] Instructions for reducing background signal may include instructions that, when executed by the processing circuitry, cause the processing circuitry to perform the following operations: subtract an offset from the analyte signal to generate an offset correction signal; calculate multiple sensitivities from the offset correction signal, each sensitivity corresponding to a reference point among multiple analyte reference points; calculate the median of the sensitivities within a time window; calibrate the adjusted analyte data to the offset correction signal based on the median of the sensitivities; and pair the adjusted analyte data with the reference points.

[0026] The offset can be calculated from the global time-varying background offset based on the time elapsed since the activation of the self-analyte sensor device, thereby calculating the offset correction signal.

[0027] This offset can be a time-invariant offset.

[0028] The analyte sensor device may include: a first working electrode at the tail of the sensor, the first working electrode having a first sensitivity; and a second working electrode at the tail of the sensor, the second working electrode having a second sensitivity lower than the first sensitivity.

[0029] The first working electrode may have a first active region on which a first number of catalysts are disposed, and the second working electrode may have a second active region on which a second number of catalysts are disposed, the surface area of ​​the second active region being smaller than the surface area of ​​the first active region.

[0030] Instructions for reducing background signals may include instructions that, when executed by the processing circuitry, cause the processing circuitry to perform the following operations: detect an analyte signal from a first working electrode; detect an additional analyte signal from a second working electrode; calculate the difference between the analyte signal and the additional analyte signal; and calculate adjusted analyte data based on the difference between the analyte signal and the additional analyte signal.

[0031] Instructions for reducing background signals may include instructions that, when executed by the processing circuitry, cause the processing circuitry to calculate individual background offsets based on the analyte signal, other analyte signals, and the difference between the analyte signal and other analyte signals.

[0032] The second working electrode can be configured to measure the individual background current and to calculate the offset signal based on the individual background current.

[0033] The memory may further store instructions that, when executed by the processing circuitry, cause the processing circuitry to apply temperature correction to the analyte signal based on the temperature from the temperature sensor of the analyte sensor device.

[0034] The sensor tail can extend from the body of the analyte sensor device, and the analyte sensor device may include: a first working electrode on the sensor tail having a first sensing layer at a first position along the sensor tail; and a second working electrode on the sensor tail having a second sensing layer at a second position along the sensor tail adjacent to the first position.

[0035] The memory may further store instructions that, when executed by the processing circuitry, cause the processing circuitry to detect a system fault in the analyte sensor device by: detecting an analyte signal from a first working electrode; detecting an additional analyte signal from a second working electrode; calculating one or more consistency measures between the analyte signal and the additional analyte signal; comparing one or more consistency measures with a threshold; and detecting a system fault in the analyte sensor device when one or more consistency measures exceed the threshold.

[0036] System failures can be caused by late sensor attenuation (LSA).

[0037] The memory may further store instructions that, when executed by the processing circuitry, cause the processing circuitry to correct system faults by: calculating an orthogonal fit between the analyte signal and another analyte signal; calculating a fixed offset based on the orthogonal fit; and correcting the analyte signal or another analyte signal based on the fixed offset.

[0038] The memory may further store instructions that, when executed by the processing circuitry, cause the processing circuitry to correct system faults by: calculating an orthogonal fit between the analyte signal and another analyte signal; calculating a time-varying offset based on the orthogonal fit; and correcting the analyte signal or another analyte signal based on the time-varying offset.

[0039] According to one embodiment of the present disclosure, the analyte sensor device includes: a sensor tail, the sensor tail including: a first working electrode on the sensor tail having a first sensitivity; and a second working electrode on the sensor tail having a second sensitivity lower than the first sensitivity.

[0040] The first working electrode may have a first active region on which a first number of catalysts are disposed, and the second working electrode may have a second active region on which a second number of catalysts are disposed, the surface area of ​​the second active region being smaller than the surface area of ​​the first active region.

[0041] The analyte sensor device may also include a processor and a memory, the memory storing instructions that, when executed by the processor, cause the processor to: measure the analyte signal based on the first working electrode; and reduce the background signal in the analyte signal according to an offset signal.

[0042] The memory may also store instructions that, when executed by the processor, cause the processor to reduce the background signal by: subtracting the offset from the analyte signal to generate an offset correction signal; calculating multiple sensitivities from the offset correction signal, each sensitivity corresponding to a reference point among multiple analyte reference points; calculating the median of the sensitivities within a time window; calibrating the adjusted analyte data to the offset correction signal based on the median of the sensitivities; and pairing the adjusted analyte data with the reference points.

[0043] The offset can be calculated from the global time-varying background offset based on the time elapsed since the activation of the self-analyte sensor device, thereby calculating the offset correction signal.

[0044] This offset can be a time-invariant offset.

[0045] The first working electrode may have a first active region on which a first number of catalysts are disposed, and the second working electrode may have a second active region on which a second number of catalysts are disposed, the surface area of ​​the second active region being smaller than the surface area of ​​the first active region, and the instructions for reducing the background signal may include instructions that, when executed by the processor, cause the processor to perform the following operations: detect an analyte signal from the first working electrode; detect another analyte signal from the second working electrode; calculate the difference between the analyte signal and the other analyte signal; and calculate adjusted analyte data based on the difference between the analyte signal and the other analyte signal.

[0046] The memory may further store instructions that, when executed by the processor, enable the processor to calculate the individual background offset based on the analyte signal, other analyte signals, and the difference between the analyte signals and other analyte signals.

[0047] The memory may further store instructions that, when executed by the processor, enable the processor to calculate the individual background offset based on the analyte signal, other analyte signals, and the difference between the analyte signals and other analyte signals.

[0048] The analyte sensor device may also include a processor and a memory, the memory storing instructions that, when executed by the processor, cause the processor to: apply temperature correction to the analyte signal based on the temperature from the temperature sensor of the analyte sensor device. Attached Figure Description

[0049] The accompanying drawings, together with the specification, illustrate exemplary embodiments of the present disclosure and, together with the specification, serve to explain the principles of the present disclosure.

[0050] Figure 1 This is a diagram illustrating an in vivo analyte monitoring system that can be used with embodiments of the present disclosure.

[0051] Figure 2This is a block diagram of an analyzer readout device that can be used with embodiments of the present disclosure.

[0052] Figure 3 This is a block diagram of an analyte sensor device that can be used with embodiments of this disclosure.

[0053] Figure 4 This is a system flowchart illustrating an analyte sensor device communicating with an analyte readout device according to some embodiments of the present disclosure.

[0054] Figure 5 This is a graph depicting the impact of late-stage sensor attenuation (LSA) on the analyte sensor over a 14-day period.

[0055] Figure 6 It is a graph describing the measured raw current passing through the analyte sensor and the individual background sensor.

[0056] Figure 7 The results of several sensor studies performed using computer simulation models (e.g., mathematical simulations) are described to examine the impact of various factors on low-end accuracy measures.

[0057] Figure 8 It is a graph describing the output of several different background sensors measured from several different subjects.

[0058] Figure 9A and Figure 9B These are graphs describing sensor traces before and after subtracting the global background current, according to some embodiments of this disclosure.

[0059] Figure 10A and Figure 10B It is a graph describing the analyte concentration measurement calculated from the analyte reference value measured at the corresponding time based on interstitial fluid sensor data.

[0060] Figure 11 This is a flowchart of a method for reducing background current according to one embodiment of the present disclosure.

[0061] Figure 12 This is a schematic diagram of a multichannel analyte sensor according to one embodiment of the present disclosure.

[0062] Figure 13A and Figure 13B Each of the embodiments according to this disclosure is shown. Figure 12 3D and cross-sectional views of the multichannel analyte sensor.

[0063] Figure 13C A cross-sectional view of a multichannel analyte sensor according to one embodiment of the present disclosure is shown.

[0064] Figure 14 This is a schematic diagram of the sensing layer of the working electrode according to one embodiment of the present disclosure.

[0065] Figure 15A and Figure 15B The graphs show the in vitro calibration data of dual glucose sensors with different sensitivities, calibrated using analytes and interfering substances respectively.

[0066] Figure 16 This is a flowchart of a method for calculating and / or removing individual background offsets according to one embodiment of the present disclosure.

[0067] Figure 17 Measurements from two sensor data channels and the difference between the measurements from the two sensors are described over a 14-day wear period.

[0068] Figure 18 This is a flowchart of a method for detecting late sensor attenuation (LSA) according to one embodiment of the present disclosure. Detailed Implementation

[0069] In the following detailed description, certain exemplary embodiments of the invention are shown and described by way of illustration only. As those skilled in the art will recognize, the invention can be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein.

[0070] The publications discussed herein are provided only for the purpose of acknowledging their prior publication prior to the filing date of this application. Nothing herein should be construed as an admission that this disclosure is not entitled to precede those publications by virtue of existing disclosures. Furthermore, the publication dates provided may differ from the actual publication dates, which may require separate verification.

[0071] In general, embodiments of this disclosure are used with systems, apparatus, and methods for detecting at least one analyte (such as glucose) in bodily fluids, such as subcutaneously in interstitial fluid (“ISF”) or blood, in dermal fluid within the dermis, or otherwise. Therefore, many embodiments include in vivo analyte sensors that are structurally configured such that at least a portion of the sensor is located, or can be located, within the user’s body (e.g., a few millimeters below the surface of the skin) to obtain information about at least one analyte in the body. However, embodiments disclosed herein can be used with in vivo analyte monitoring systems that incorporate in vitro capabilities, as well as purely in vitro or ex vivo analyte monitoring systems (including those that are entirely non-invasive).

[0072] Furthermore, for each embodiment of the methods disclosed herein, systems and apparatuses capable of performing each of those embodiments are covered within the scope of this disclosure. For example, embodiments of analyte sensor devices are disclosed, and these devices may have one or more sensors capable of performing or facilitating the execution of any and all method operations, analyte monitoring circuitry (e.g., analog circuitry), non-volatile memory (e.g., for storing instructions), power supply, communication circuitry, transmitter, receiver, processing circuitry, and / or controller (e.g., for executing instructions). These analyte sensor device embodiments can be used and are capable of being used to implement those operations performed by the analyte sensor devices according to any and all methods herein.

[0073] Similarly, embodiments of analyte readout devices are disclosed herein, having one or more transmitters, receivers, non-transient memory (e.g., for storing instructions), power supplies, processing circuitry, and / or controllers (e.g., for executing instructions) capable of performing any and all method operations or facilitating the execution of any and all method operations. These embodiments of analyte readout devices can be used to implement those operations performed by readout devices according to any and all methods described herein.

[0074] Implementations of trusted computer systems are also disclosed. These trusted computer systems may include one or more processing circuits, controllers, transmitters, receivers, non-volatile memory, databases, servers, and / or networks, and may be discretely located or distributed across multiple geographical areas. These implementations of trusted computer systems can be used to implement those operations performed by the trusted computer systems according to any and all of the methods described herein.

[0075] Returning to the discussion of analyte sensor devices, current-analytical biosensors provide a class of analyte sensors that generate an electrical signal by applying a voltage (or potential) between electrodes to oxidize or reduce various analytes. Systems used to measure the output of an analyte sensor are typically configured such that the measured current (i) is linearly correlated with the analyte concentration (C) of one or more analytes of interest, and can be characterized as follows:

[0076] i = m * C + b

[0077] Here, m is the signal sensitivity driven by the execution of the biochemical reaction-based detection scheme. While the intercept b in the above linear equation can be an “artificial” result of forcing a linear regression to a nonlinear system, in practice, real background currents do exist and can significantly contribute to increasing the intercept value. Background currents are primarily due to the simultaneous electrochemical reactions of other non-targeted electroactive compounds in the testing environment (e.g., subcutaneous interstitial fluid). These non-targeted electroactive compounds are generally considered interfering and, for example, in the case of a glucose sensor, can include acetaminophen, ascorbic acid, bilirubin, cholesterol, creatinine, cysteine, dopamine, ephedrine, glutathione, ibuprofen, L-DOPA, methyldopa, salicylates, tetracycline, tolazoline, tolbutamide, triglycerides, and uric acid.

[0078] Furthermore, in a few cases of sensor wear, the output of the analyte sensor may exhibit effects known as early sensor attenuation (ESA) and late sensor attenuation (LSA). Early sensor attenuation and late sensor attenuation refer to the effect of the analyte signal attenuating, respectively, in the early or late portions of the sensor's lifespan. As an example, an analyte sensor may be designed for use over a two-week period, and therefore its lifespan may be two weeks; however, embodiments of this disclosure are not limited to this and can be applied to sensors with shorter or longer lifespans. Early sensor attenuation can occur due to various factors, such as a foreign body response from the user around the puncture site of the implanted analyte sensor. This foreign body response, which may ultimately lead to the formation of a foreign body capsule around the implanted analyte sensor, can suppress correct readings from the analyte sensor for a short period after implantation (typically within the first 24 hours of the sensor's lifespan, and more specifically within the first 1 to 12 hours). Late sensor attenuation can also occur due to various factors, including the adhesive that holds the analyte sensor to the user's skin failing and / or a foreign body response from the user, including the formation of the aforementioned foreign body capsule. Late sensor decay can occur later in the analyte sensor wear and may affect sensors designed for wear for more than 10 days. Both early and late sensor decay result in artificially low glucose readings. Therefore, users who rely on these readings may take incorrect actions to increase their glucose levels (e.g., based on actual blood sugar levels) when such actions are not actually needed.

[0079] Some embodiments of this disclosure relate to improvements in the computer-implemented capabilities of an analyte monitoring system regarding the accuracy of signals generated by an analyte sensor, the detection of suspected analyte sensor malfunctions, and / or the detection of reduced signal response of an analyte sensor. In some embodiments, for example, the analyte sensor device is worn on the body, wherein the analyte sensor device includes an in vivo analyte sensor. According to one aspect of the embodiments, analyte metrics based on analyte sensor data received from the analyte sensor can be periodically calculated and updated by processing circuitry of the analyte sensor device. Analyte metrics may include, for example, recent analyte level percentile metrics, variability metrics, central tendency metrics, variance from variability metrics and central tendency metrics to a predetermined hypoglycemic risk function, baseline analyte level metrics, and baseline hypoglycemic risk metrics. Based on the analyte metrics, the processing circuitry can detect a suspected reduction in the signal response of the analyte sensor. In other embodiments, an analyte readout device can receive real-time, near-real-time, or historical analyte sensor data transmitted from the analyte sensor device and subsequently determine a suspected reduction in the signal response of the analyte sensor.

[0080] Therefore, aspects of embodiments of this disclosure relate to systems and methods for increasing the accuracy of measurements by analyte sensors, including reduction of ESA (e.g., glucose metric for more closely tracking the measured blood glucose level) in the background signal and measurement signal, and detection of LSA. Thus, embodiments of this disclosure can improve the accuracy of analyte monitoring systems by reducing the background signal and by promptly notifying the user when a suspected analyte sensor malfunction is detected and / or when the analyte sensor should be replaced. Other features and advantages of the disclosed embodiments are further discussed below.

[0081] To provide additional background, examples of analyte monitoring systems that can implement embodiments of this disclosure will be described in more detail below. However, embodiments of this disclosure are not limited to the specific example systems described herein and can be implemented on a variety of different systems.

[0082] Exemplary Implementation of Analyte Monitoring System

[0083] Various types of analyte monitoring systems exist. For example, a “continuous analyte monitoring” system (or a “continuous glucose monitoring” system) is an in vivo system that can repeatedly or continuously transmit data from an analyte sensor device to an analyte readout device without, for example, automatically prompting according to a schedule, and can transmit information using wired connections (e.g., serial data connections, such as Universal Serial Bus or USB) or wireless connections (e.g., using wireless communication protocols such as Bluetooth or Bluetooth Low Energy, Wi-Fi, etc.). As another example, a “flash analyte monitoring” system (or a “flash glucose monitoring” system or a flash continuous glucose monitoring system or a “flash” system) is an in vivo system that can transmit data from an analyte sensor device in response to a scan or request for data from an analyte readout device, such as using near field communication (NFC), radio frequency identification (RFID), or Bluetooth protocols. In vivo analyte monitoring systems can also operate without the need for calibration using, for example, finger-prick (FS) calibration for blood glucose (BG) levels.

[0084] An in vivo monitoring system may include an analyte sensor that, when positioned in the body, comes into contact with the user's bodily fluids and senses the levels of one or more analytes contained therein. The bodily fluid may be, for example, interstitial fluid (ISF) in subcutaneous tissue. The analyte sensor may be part of an analyte sensor control unit located on the user's body and containing electronics and a power source that enable and control analyte sensing. The analyte sensor and the analyte sensor control unit together are referred to as an analyte sensor device. An analyte sensor device and variations thereof may also be referred to as a "sensor control unit," "analyte sensor control unit," "analyte sensor unit," "on-body electronics" device or unit, "on-body" device or unit, or "sensor data communication" device or unit, to name just a few. As used herein, these terms are not limited to devices having an analyte sensor and encompass devices having other types of sensors, whether biometric or non-biometric. The term "on body" (or "on-body") refers to any device that resides directly on or very close to the body, such as wearable devices (e.g., glasses, watches, wristbands or bracelets, necklaces or chokers).

[0085] The in vivo monitoring system may also include one or more analyte readout devices that receive sensed analyte data from the analyte sensor device. These analyte readout devices can process and / or display the sensed analyte data or sensor data to a user in any number of formats. To name just a few, these devices and variations thereof may be referred to as “handheld readout devices,” “readout devices” (or “readers”), “handheld electronic devices” (or “handheld”), “portable data processing” devices or units, “data receivers,” “receiver” devices or units (or “receivers”), “relay” devices or units, or “remote” devices or units. Other devices (such as personal computers) have also been used with or incorporated into in vivo and in vitro monitoring systems. For example, in some embodiments of this disclosure, a smartphone, tablet, or personal digital assistant can operate as an analyte readout device by using a software application (or application) installed on the device. Such devices may run operating systems, such as those developed by Google LLC. Or developed by Apple Inc. For convenience, the term "smartphone" will be used herein to refer to any personal electronic device of various personal electronic devices, including smartphones, personal digital assistants, tablets and similar devices.

[0086] An in vivo analyte monitoring system can be distinguished from an "ex vivo" system, which contacts a biological sample outside the body (or more precisely, "extracorporeal") and typically includes a metering device having a port for receiving an analyte test strip carrying the user's bodily fluids (e.g., blood from a finger prick), which can be analyzed to determine the user's analyte levels. The embodiments described herein can be used in conjunction with in vivo systems, in vitro systems, and combinations thereof.

[0087] The embodiments described herein can be used to monitor and / or process information about any number of one or more different analytes. Analytes that can be monitored include, but are not limited to, acetylcholine, amylase, bilirubin, cholesterol, human chorionic gonadotropin (hCG), glycated hemoglobin (HbA1c), creatine kinase (e.g., CK-MB), creatine, creatinine, DNA, fructosamine, glucose (e.g., blood glucose and / or interstitial glucose), glucose derivatives, glutamine, growth hormone, hormones, ketones, ketone bodies, lactate, peroxides, prostate-specific antigen, prothrombin, RNA, thyroid-stimulating hormone (TSH), and troponin. Drugs such as antibiotics (e.g., gentamicin, vancomycin, etc.), digoxin, theophylline, and warfarin can also be monitored. In embodiments monitoring more than one analyte, the analytes can be monitored at the same or different times.

[0088] Figure 1 This is a diagram illustrating an in vivo analyte monitoring system 100 that can be used with embodiments of the present disclosure. The in vivo analyte monitoring system includes an analyte sensor device 102 and one or more analyte readout devices 110, 120 that communicate with the analyte sensor device 102 via a local communication link or path 140, which may be wired or wireless and unidirectional or bidirectional. In embodiments where path 140 is wireless, near field communication (NFC) protocols, radio frequency identification (RFID) protocols, Bluetooth or Bluetooth Low Energy (BLE) protocols, Wi-Fi protocols, proprietary protocols, etc., including those communication protocols existing prior to the date of this application or variants thereof, may be used. Each of the analyte readout devices 110, 120 is also capable of wired, wireless, or combined communication with a computer system 170 (e.g., a local or remote computer system) via communication path (or link) 141, and wired, wireless, or combined communication with a network 190 (such as the Internet or the cloud) via communication path (or link) 142. Communication with network 190 may involve communication with trusted computer system 180 within network 190, or communication via communication link (or path) 143 through network 190 to computer system 170. Communication paths 141, 142, and 143 may be wireless, wired, or both, may be unidirectional or bidirectional, and may be part of a telecommunications network, such as a Wi-Fi network, local area network (LAN), wide area network (WAN), Internet, or other data network. In some cases, communication paths 141 and 142 may be the same path. All communication on paths 140, 141, and 142 may be encrypted, and the analyzer sensor device 102, one or more analyzer readout devices 110, 120, computer system 170, and trusted computer system 180 may each be configured to encrypt and decrypt those communications sent and received. Analyzer readout devices 110, 120 may synchronize with each other 115 or otherwise exchange data. In one example, the analyte reading device 110 may be a dedicated analyte reading device and may include a port 113 for testing strips through which analyte levels can be analyzed and analyte data can be obtained, while another analyte reading device 120 may be a cellular phone (e.g., a smartphone) or another device with an analyte reader software application installed and accessible thereon (whose primary purpose may differ from providing analyte reader capabilities).

[0089] Variations of devices 102 and 110 / 120, as well as other components of an in vivo analyte monitoring system suitable for use with the system, device, and method embodiments set forth herein, are described in U.S. Patent Application Publication No. 2011 / 0213225 ('225 Publication), and are incorporated herein by reference in their entirety for all purposes.

[0090] The analyte sensor device 102 may include a housing 103 that houses in vivo analyte monitoring circuitry and a power supply. In this embodiment, the in vivo analyte monitoring circuitry is electrically coupled to an analyte sensor 104 that extends through a patch 105 and protrudes away from the housing 103. The patch 105 includes an adhesive layer for attachment to the skin surface of a user's body. Other forms of body attachment to the body may be used in addition to or instead of adhesives.

[0091] The analyte sensor 104 is configured to be at least partially inserted into the user's body, where it can come into fluid contact with the user's bodily fluids (e.g., subcutaneous (subdermal) fluid, dermal fluid, or blood) and, together with in vivo analyte monitoring circuitry, is used to measure the user's analyte-related data. The analyte sensor 104 and any accompanying sensor control electronics can be applied to the body in any desired manner. For example, the insertion device can be used to position all or part of the analyte sensor 104 and bring it into contact with the user's bodily fluids using the outer surface of the user's skin. In doing so, the insertion device can also use a patch 105 to adhere the analyte sensor device 102 to the user's skin. In other embodiments, the insertion device can first position the analyte sensor 104, and then the accompanying sensor control electronics can subsequently be coupled to the analyte sensor 104 manually or by means of a mechanical means. Examples of insertion devices are described in U.S. Patent Application Publications Nos. 2008 / 0009692, 2011 / 0319729, 2015 / 0018639, 2015 / 0025345 and 2015 / 0173661, the entire contents of all of which are incorporated herein by reference and for all purposes.

[0092] After collecting raw data from the user's body, the analyte sensor device 102 can apply analog signal conditioning to the data and convert the data into conditioned raw data in digital form. In some embodiments, the analyte sensor device 102 can then algorithmically process the digital raw data into the form of a biometric (e.g., analyte level) and / or one or more analyte measures based thereon, representing a biometric measured by the user. For example, the analyte sensor device 102 may include processing circuitry that algorithmically performs any of the methods described herein to calculate an analyte measure used to detect a decrease in the signal response of the analyte sensor. The analyte sensor device 102 can then encode the calculated analyte measure, an indication of sensor malfunction, and / or the processed sensor data and wirelessly transmit it to the analyte readout device 110 / 120, which can then format or graphically process the received data for a digital display 124 for the user. In other embodiments, instead of wirelessly transmitting sensor data to another device (e.g., analyte readout device 110 / 120), or instead of wirelessly transmitting sensor data to another device (e.g., analyte readout device 110 / 120), the analyte sensor device 102 may graphically process the final form of the data to prepare it for display, and display the data on the display of the analyte sensor device 102. In some embodiments, the system uses the final form of biometric data (before graphical processing) (e.g., incorporated into a diabetes monitoring mechanism) and displays it to the user without further processing.

[0093] In some other embodiments, the raw digital data of the analyte may be encoded for transmission to another device, such as analyte readout device 110 / 120, which then algorithmically processes the raw digital data into a biometric form representing the user's measurement (e.g., a form easily adaptable for display to the user) and / or one or more analyte measures based thereon. Analyte readout device 110 / 120 may include processing circuitry for algorithmically performing any of the methods described herein to calculate an analyte measure used to detect a decrease in the signal response of an analyte sensor. The data processed by the algorithm may then be formatted or graphically processed for digital display to the user or for controlling other actions, such as controlling the operation of a drug delivery device (e.g., an insulin pump).

[0094] In other embodiments, the analyte sensor device 102 and the analyte readout device 110 / 120 transmit digital raw data to another computer system for algorithm processing and display.

[0095] The analyte readout device 110 / 120 may include a display 112 / 122 that outputs information to a user (e.g., to a user interface of a digital display 124) and / or receives input from a user, and one or more optional input components 111 / 121, such as buttons, actuators, touch-sensitive switches, capacitive switches, pressure-sensitive switches, scroll wheels, etc., for inputting data, commands, or otherwise controlling the operation of the analyte readout device 110 / 120. In some embodiments, the display 112 / 122 and the input components 111 / 121 may be integrated into a single component, such as a touchscreen user interface, that allows the display to detect the presence and location of a physical touch on the display. In some embodiments, the input components 111 / 121 of the analyte readout device 110 / 120 may include a microphone, and the analyte readout device 110 / 120 may include software configured to analyze audio input received from the microphone, thereby enabling the functionality and operation of the analyte readout device 110 / 120 to be controlled by voice commands. In some embodiments, the output components of the analyte readout devices 110 / 120 include a speaker for outputting information as an acoustic signal. Similar voice response components (such as speakers, microphones, and software routines) for generating, processing, and storing voice-driven signals may be included in the analyte sensor device 102.

[0096] The analyte readout device 120 may also include one or more data communication ports 123 for wired data communication with an external device such as the computer system 170 or the analyte sensor device 102. The analyte readout device 110 may also include one or more data communication ports for wired data communication with an external device, such as the computer system 170 or the analyte sensor device 102. Example data communication ports include a USB port, a mini-USB port, a USB Type-C port, a USB micro-A and / or micro-B port, an RS-232 port, an Ethernet port, a FireWire port, or other similar data communication ports configured to connect to a compatible data cable. As discussed above, the analyte readout device 110 may also include an integrated or attachable in vitro glucose analyzer including an in vitro test strip port 113 for receiving an in vitro glucose test strip for performing in vitro blood glucose measurements.

[0097] The analyte readout device 110 / 120 can display measured biometric data wirelessly received from the analyte sensor device 102, and can also be configured to output alarms, alert notifications, glucose values, etc., which can be visual, auditory, tactile, or any combination thereof. Further details and other illustrated embodiments can be found in U.S. Patent Application Publication No. 2011 / 0193704, which is incorporated herein by reference for all purposes. The terms “glucose value,” “glucose level,” and “glucose data” are used interchangeably herein, wherein these terms refer to the measured concentration of glucose (or “sugar”) in blood or interstitial fluid. The measured glucose concentration can be a raw signal measured by the analyte sensor device 102 using methods such as electroanalysis, coulometric analysis, voltammetry, colorimetry, optical techniques, etc., or a corresponding converted glucose concentration number or equivalent measurement in mg / dL or mmol / L.

[0098] The analyte readout device 110 / 120 can act as a data conduit to transmit measurement data and / or analyte measurements from the analyte sensor device 102 to the computer system 170 or the trusted computer system 180. In some embodiments, data received from the analyte sensor device 102 may be stored (permanently or temporarily) in one or more memories of the analyte readout device 110 / 120 before being uploaded to the computer system 170, the trusted computer system 180, or the network 190.

[0099] Computer system 170 may be a personal computer, server terminal, laptop computer, smartphone, tablet computer, or other suitable data processing device. Computer system 170 may include (or include) software for data management and analysis, and for communicating with components in analyte monitoring system 100. Computer system 170 may be used by a user or medical professional to display and / or analyze biometric data measured by analyte sensor device 102. In some embodiments, analyte sensor device 102 may transmit biometric data directly to computer system 170 without an intermediary such as analyte readout device 110 / 120, or indirectly using an Internet connection (again, as an option, without prior transmission to analyte readout device 110 / 120). The operation and use of computer system 170 are further described in the '225 disclosure incorporated herein by reference. Analyte monitoring system 100 may also be configured to operate in conjunction with a data processing module, as also described in the incorporated '225 disclosure.

[0100] The trusted computer system 180 may be physically or virtually under the control of the owner of the manufacturer or distributor of the analyte sensor device 102 via a secure connection, and may be used to perform authentication of the analyte sensor device 102, to securely store the user's biometric data, and / or as a server serving data analysis programs (e.g., accessible via a web browser) to perform analysis of the user's measurement data.

[0101] Example Implementation of the Analyte Readout Device

[0102] The analyte readout device 110 / 120 may be a mobile communication device, such as a dedicated readout device (configured to communicate with the analyte sensor device 102 and optionally with the computer system 170, but without mobile phone communication capabilities) or a mobile phone, including but not limited to Wi-Fi or internet-enabled smartphones, smartwatches, tablets, or personal digital assistants (PDAs). Examples of smartphones may include those based on… Operating system, Android TM operating system, operating system, WebOS TM , Operating system, or Mobile phones with operating systems that have data network connectivity for data communication via the Internet and / or LAN.

[0103] The analyte readout device 110 / 120 can also be configured as a mobile smart wearable electronic component, such as an optical component worn on or near the user's eyes (e.g., one or more smart glasses, such as Google Glass, which are mobile communication devices). This optical component may have a transparent display that shows the user information about the user's analyte level (as described herein) while allowing the user to view it with minimal obstruction to the user's overall vision. The optical component may be capable of wireless communication similar to that of a smartphone. Other examples of wearable electronic devices include devices worn around or near the user's wrist (e.g., a watch), neck (e.g., a necklace), head (e.g., a headband, a hat), chest, etc.

[0104] Figure 2This is a block diagram of analyte readout devices 110 / 120. Analyte readout devices 110 / 120 may include input components 111 / 121, displays 112 / 122, and processing circuitry 206. The processing circuitry may include one or more processors, microprocessors, controllers, and / or microcontrollers, each of which may be discrete chips or distributed across multiple different chips (and a portion of multiple different chips). Processing circuitry 206 may include a communication processor 202 with on-board memory 203 and an application processor 204 with on-board memory 205. Analyte readout devices 110 / 120 (and specifically, analyte readout device 110) may include a processor 213 for analyzing / processing in vitro blood glucose measurements from port 113. Analyte readout devices 110 / 120 also include radio frequency (RF) communication circuitry 208 coupled to RF antenna 209, memory 210, multifunction communication circuitry 212 with one or more associated antennas 214, power supply 216, power management circuitry 218, and clock 219. Figure 2 It is a simplified representation of typical hardware and functions residing in a smartphone, and those skilled in the art will readily recognize that other hardware and functions (e.g., codecs, drivers, glue logic) may also be included.

[0105] The communication processor 202 can interface with the RF communication circuitry 208 and perform analog-to-digital conversion, encoding and decoding, digital signal processing, and other functions that facilitate the conversion of voice, video, and data signals into formats suitable for delivery to the RF communication circuitry 208 (e.g., in-phase and quadrature), which can then wirelessly transmit the signals. The communication processor 202 can also interface with the RF communication circuitry 208 to perform the reverse functions necessary for receiving wireless transmissions and converting them into digital data, voice, and video. The RF communication circuitry 208 may include transmitters and receivers (e.g., integrated as a transceiver) and associated encoder logic.

[0106] Application processor 204 may be adapted to execute an operating system and any software applications residing on analyte readout device 110 / 120, process video and graphics, and perform other functions unrelated to the processing of communications transmitted and received via RF antenna 209. The operating system may operate in conjunction with multiple applications on analyte readout device 110 / 120 (e.g., specifically for analyte readout device 120). For analyte readout device 120, any number of applications (also referred to as “user interface applications”) may run on analyte readout device 120 at any given time, and may include one or more applications related to the diabetes monitoring mechanism, in addition to other commonly used applications unrelated to this mechanism (e.g., email, calendar, weather, sports information, games, etc.). For example, data received by the analyte readout device indicating sensed analyte levels and in vitro blood analyte measurements may be securely transmitted to a user interface application residing in memory 210 of analyte readout device 120. Such communication may be securely performed, for example, by using mobile application containerization, isolation, or packaging techniques.

[0107] Memory 210 may be shared by one or more of the various functional units present within the analyzer readout device 110 / 120, or may be distributed among two or more of them (e.g., as separate memories present in different chips). Memory 210 may also be a separate chip of its own. Memory 203, 205, and 210 are non-transient and may be volatile (e.g., RAM, etc.) and / or non-volatile memories (e.g., ROM, flash memory, F-RAM, etc.).

[0108] The multi-functional communication circuit 212 can be implemented as one or more chips and / or components (e.g., transmitters, receivers, transceivers, and / or other communication circuits) that perform other functions, such as local wireless communication, for example, communicating locally with the analyte sensor device 102 under appropriate protocols (e.g., Wi-Fi, Bluetooth, Bluetooth Low Energy, NFC, RFID, proprietary protocols, and others), and determining the geographic location of the analyte readout device 110 / 120 (e.g., Global Positioning System (GPS) hardware). One or more additional antennas 214 may be associated with the multi-functional communication circuit 212 as needed to operate with various protocols and circuits.

[0109] The power supply 216 may include one or more batteries, which may be rechargeable or disposable. The power management circuit 218 may regulate battery charging and power monitoring, power boost, and perform DC-DC voltage conversion, etc.

[0110] The analyte readout device 110 / 120 may also include or be integrated with a drug delivery device (e.g., insulin, etc.), such that they share a common housing. Examples of such drug delivery devices or medication delivery devices may include a medication pump with a cannula that remains in the body to allow infusion over time periods of hours or days (e.g., a wearable pump for delivering basal insulin and insulin). When combined with a medication delivery device, the analyte readout device 110 / 120 may include a reservoir for storing the medication, a mechanical actuator, such as a solenoid or motor configured to control a device (such as a pump or syringe) that can be connected to a delivery tube, and an infusion cannula. The mechanical actuator may control the pump or syringe (or other medication delivery mechanism) to force the medication through the cannula inserted therein from the reservoir into the body of a person with diabetes. Other examples of drug delivery devices that can be included with (or integrated with) the analyte readout device 110 / 120 include portable injection devices (e.g., insulin pens) that only require skin puncture for each delivery and are subsequently removed. When combined with a portable injection device, the analyte readout device 110 / 120 may include an injection needle, a cartridge for carrying the drug, an interface for controlling the amount of drug to be delivered, and an actuator that causes an injection. The device can be reused until the drug is depleted, at which point the combined device can be discarded, or the cartridge can be replaced with a new cartridge, allowing for repeated reuse of the combined device. The needle can be replaced after each injection.

[0111] The combined device can be used as part of a closed-loop system (e.g., an artificial pancreas system that does not require user intervention to operate) or a semi-closed-loop system (e.g., an insulin circuit system that requires occasional user intervention to confirm dose changes). For example, the combined device can be implanted under the skin of a person (or patient) with diabetes and can be monitored in a repetitive, automated manner by an analyte sensor device 102. The analyte sensor device can then transmit the monitored analyte level to an analyte readout device 110 / 120, which automatically determines an appropriate drug dose to control the patient's analyte level and subsequently controls the drug delivery device to deliver the determined dose to the patient's body. Software instructions for controlling the amount of insulin delivered and pumped can be stored in the memory of the analyte readout device 110 / 120 and executed by the readout device's processing circuitry. These instructions also cause calculations of drug delivery volume and duration (e.g., large infusion and / or continuous background infusion dosing profiles) based on analyte level measurements obtained directly or indirectly from the analyte sensor device 102. In some embodiments, the analyte sensor device 102 can determine the drug dosage and transmit it to the analyte readout device 110 / 120.

[0112] Example implementation of sensor control device

[0113] Figure 3 This is a block diagram of the analyte sensor device 102. The analyte sensor device 102 includes an analyte sensor 104 and sensor electronics 250 (including analyte monitoring circuitry) that may have most of the processing capabilities for presenting final result data suitable for display to a user. Figure 3 In this embodiment, a single semiconductor chip 251 is described as potentially being a custom application-specific integrated circuit (ASIC). Within the ASIC 251 are several advanced functional units, including an analog front-end (AFE) 252, power management (or control) circuitry 254, a processor 256, and communication circuitry 258 (which may be implemented as a transmitter, receiver, transceiver, passive circuitry, or otherwise according to a communication protocol). In this embodiment, both the AFE 252 and the processor 256 serve as analyte monitoring circuitry; however, in other embodiments, either circuitry may perform analyte monitoring functions. The processor 256 may include one or more processors, microprocessors, controllers, and / or microcontrollers, each of which may be discrete chips or distributed across multiple different chips (and portions of multiple different chips). The ASIC 251 may also include a clock 255 (or timer) which may be used to measure the elapsed time from the activation of the analyte sensor device 102.

[0114] Memory 253 is also included within ASIC 251 and can be shared by various functional units present within ASIC 251, or distributed among two or more of them. Memory 253 can also be a separate chip. Memory 253 is non-transient and can be volatile and / or non-volatile memory. In this embodiment, ASIC 251 is coupled to power source 260, which can be a button cell battery, etc. Analog front end 252 interacts with in vivo analyte sensor 104, receives measurement data from the in vivo analyte sensor, and outputs the data in digital form to processor 256. In some embodiments, the processor can, in turn, process the digital data in any manner described elsewhere herein. The processed data can then be provided to communication circuitry 258 for transmission via antenna 261 to analyte readout devices 110 / 120, where, for example, further processing can be performed by a resident software application before the data is displayed, in some embodiments. Antenna 261 can be configured according to application requirements and communication protocols. Antenna 261 can be, for example, a printed circuit board (PCB) trace antenna, a ceramic antenna, or a discrete metal antenna. Antenna 261 can be configured as a monopole antenna, a dipole antenna, an F-type antenna, a loop antenna, or other types of antenna.

[0115] Information can be actively transferred from the analyte sensor device 102 to another device (e.g., the analyte readout device 110 / 120) at the initiative of the analyte sensor device 102 or the analyte readout device 110 / 120. For example, when analyte information is available, or according to a schedule (e.g., approximately every 1 minute, approximately every 5 minutes, approximately every 10 minutes, etc.), information can be automatically and / or repeatedly (e.g., continuously) transferred by the analyte sensor device 102. In this case, the information can be stored or recorded in the memory of the analyte sensor device 102 for later transfer. Information can be transferred from the analyte sensor device 102 in response to a request received by a second device. This request can be an automatic request, such as a request sent by the second device according to a schedule, or it can be a user-generated request (e.g., a self-organized or manual request). In some embodiments, a manual data request is referred to as a “scan” of the analyte sensor device 102 or an “on-demand” data transfer from the analyte sensor device 102. In some embodiments, the second device may send polling signals or data packets to the analyte sensor device 102, and the analyte sensor device 102 may treat each polling (or polling occurring at specific time intervals) as a request for data, and if data is available, may send such data to the second device. In many embodiments, communication between the analyte sensor device 102 and the second device is secure (e.g., encrypted and / or between authenticated devices), but in some embodiments, data may be transmitted from the analyte sensor device 102 in an insecure manner, for example, as a broadcast to all listening devices within range.

[0116] Different types and / or forms and / or amounts of information may be sent as part of each communication, including but not limited to: current sensor measurements (e.g., recently acquired analyte level information corresponding to the time of the start of reading), the rate of change of a metric measured over a predetermined time period, the rate of change of a metric (acceleration of the rate of change), or one or more of historical metric information corresponding to metric information acquired prior to a given reading and stored in the memory of the analyte sensor device 102.

[0117] Some or all of the real-time, historical, rate of change, and / or rate of change (e.g., acceleration or deceleration) information can be sent to the analyte readout device 110 / 120 in a given communication or transmission. In some embodiments, the type and / or form and / or quantity of information sent to the analyte readout device 110 / 120 may be pre-programmed and / or immutable (e.g., preset at manufacturing time), or may not be pre-programmed and / or not immutable, thereby allowing it to be selected and / or changed once or multiple times in the field (e.g., by activating a system switch, etc.). Therefore, in some embodiments, the analyte readout device 110 / 120 may output analyte values ​​derived from a current (real-time) sensor (e.g., in digital format), the current rate of analyte change (e.g., in the form of an analyte rate indicator, such as an arrow pointing in the direction indicating the current rate), and analyte trend history data based on analyte sensor readings (e.g., in the form of graphical traces) acquired and stored in the memory of the analyte sensor device 102. Additionally, skin temperature readings or measurements can be collected by an optional temperature sensor 257. These readings or measurements can be transmitted from the analyte sensor device 102 to another device (e.g., analyte readout device 110 / 120) (either individually or as measurements aggregated over time). However, instead of actually displaying the temperature measurement to the user, or in addition to displaying the temperature measurement to the user, the temperature readings or measurements can be used in conjunction with software programs executed by the analyte readout device 110 / 120 to correct or compensate for the analyte measurements output to the user.

[0118] Figure 4 This is a system flowchart 400 showing an analyte sensor device 402 (also called 102) communicating with an analyte readout device (also called an analyte display device) 404 (also called 110, 120). For example... Figure 4 As shown, at operation 406, the analyte sensor device 402 (e.g., analyte sensor device 102) measures analyte data (e.g., glucose level / value, peroxide level / value, ketone level / value, lactate level / value, etc.) for the user or patient. In some embodiments, at operation 410, the analyte sensor device 402 may perform one or more processing operations on the data (measurements) in the glucose data to generate processed data. These processing operations may include operations for reducing background signals present in the analyte data. At operation 412, the analyte sensor device 402 transmits the data (e.g., processed data in embodiments where some processing is performed by the analyte sensor device 402) to the analyte readout device 404 (e.g., analyte readout devices 110 / 120).

[0119] In embodiments where the analyte sensor device 402 performs operation 410, the analyte data transmitted at operation 412 may include raw analyte data (e.g., a digital version of the raw data read from the analyte sensor 104) and processed analyte data, or may include only processed analyte data. In embodiments where the analyte sensor device 402 does not perform the processing in operation 410, the raw analyte data transmitted at operation 412 includes substantially unmodified analyte data (e.g., raw analyte data).

[0120] Assuming unmodified data is transmitted at operation 412, in some embodiments of this disclosure, at operation 414, the analyte readout device 404 may perform additional processing on the raw analyte data received from the analyte sensor device 402. Furthermore, in some embodiments of this disclosure, at operation 414, the analyte readout device 404 may perform additional processing on the processed analyte data received from the analyte sensor device 402 and / or on the raw analyte data received from the analyte sensor device 402. Subsequently, at operation 418, the analyte readout device 404 may display corrected analyte data (modified by the analyte sensor device 402 and / or the analyte readout device 404). The processed analyte data displayed by the analyte readout device 404 at operation 418 is more likely to represent correct glucose data than any uncorrected analyte data.

[0121] Referring again to operations 410 and 414, analyte sensor device 402, analyte readout device 404, or both analyte sensor device 402 and analyte readout device 404 can process analyte data, and any or both of these processing operations may include operations for reducing background signal and / or detecting late sensor attenuation (LSA). Based on the reduction of background signal, analyte sensor device 402, analyte readout device 404, or both analyte sensor device 402 and analyte readout device 404 can improve the accuracy of the analyte value output and displayed by analyte readout device 404, and / or improve the accuracy of the analyte value used for controlling, for example, a drug delivery pump. Based on the detection of LSA by analyte sensor device 402 and / or analyte readout device 404, analyte sensor device 402, analyte readout device 404, or both analyte sensor device 402 and analyte readout device 404 can mitigate erroneous detection of low glucose during LSA. As discussed above, other combinations are possible because each of the analyte sensor device 402 and the analyte readout device 404 can perform one or more operations including background signal removal and LSA detection. The process for background signal removal and LSA detection according to some embodiments of this disclosure will be presented in more detail below.

[0122] Factors affecting the accuracy of analyte sensors

[0123] The accuracy of analyte sensors is affected by a variety of factors. As discussed in more detail below, aspects of embodiments of this disclosure particularly relate to improving the accuracy of analyte sensors by detecting late sensor attenuation (LSA) and reducing background signal.

[0124] Although minor, errors caused by late sensor attenuation (LSA) can affect low-end accuracy metrics. Furthermore, the presence of background current can also impact low-end accuracy. Some glucose sensor systems employ a combination of factory calibration and algorithms to detect, correct, and adjust the output mapping to minimize the impact of LSA and background current on accuracy. More direct methods of measuring LSA and background current can improve the effectiveness of mitigation, thereby further enhancing sensor accuracy.

[0125] Figure 5 This is a graph depicting the impact of late-stage sensor attenuation (LSA) on the analyte sensor over a 14-day period. As mentioned above, for a 14-day analyte sensor wear cycle (or the period during which a patient wears the sensor), a small number of analyte sensors were observed to experience generally continuous and stable degradation in the latter part of the cycle. Figure 5 An example is shown where the top graph illustrates a line indicating glucose levels measured by an implanted analyte sensor over a 14-day period, along with blood glucose (BG) measurements obtained at the corresponding times (shown as dots) (for reference). Figure 5 In the example shown, the sensor glucose readings begin to decrease after 7 days, but remain consistent with the reference BG reading. This is evident in the smoothed error graph comparing the sensor glucose readings to the BG readings, where the error remains approximately zero from 7 days up to about 11 days. However, in this sensor, later in the wear cycle, around day 12, the error begins to trend downwards (the error magnitude increases), indicating that the sensor glucose readings are starting to underreport compared to the BG readings. Therefore, this LSA may cause inaccurate readings by delaying the detection of high glucose levels or by indicating low blood sugar levels when glucose levels are within an acceptable range.

[0126] Background current is another source of error. As discussed above, systems used to measure the output of analyte sensors are typically configured such that the measured current (i) is linearly correlated with the analyte concentration (C) of one or more analytes of interest, and can be characterized as follows:

[0127] i = m * C + b

[0128] Here, m is the signal sensitivity driven by the execution of a detection scheme based on the biochemical reaction used to detect one or more analytes of interest. The background current, or background offset b, varies significantly over time and can also be considered a noise parameter. Therefore, the presence of the background offset b can reduce the signal-to-noise ratio (SNR) of the detection system, especially when the analyte of interest (or target analyte) has a relatively low signal compared to the background offset b (e.g., where the desired signal m*C is on the same order of magnitude as the background offset b).

[0129] Background shift b is partly caused by in vivo interfering substances, which are endogenous or exogenous compounds that are readily oxidized (or reduced) at voltages at or below the sensor's control voltage (which may correspond to the oxidation or reduction potential of the target analyte, and may exceed the oxidation or reduction potential of the interfering substance). A common mitigation strategy is to reduce the control voltage to minimize the interfering oxidation signal. However, as the control voltage decreases, the detection scheme for the biochemical reaction will generate at a significantly slower rate or even stop, thus setting a lower limit for the control voltage. Another mitigation strategy is to use a selectively permeable membrane to prevent interfering compounds from reaching and reacting at the electrode surface. However, adding an additional membrane to the sensor fabrication typically increases the complexity of the manufacturing process. Furthermore, selectively permeable membranes often only block a few common compounds and may not provide perfect selectivity to allow only the analyte of interest to pass through the membrane. Therefore, while these mitigation strategies reduce background shift b, applying further mitigation strategies can further improve the accuracy of the resulting signal.

[0130] Some embodiments of this disclosure involve reducing the background current (or background offset b) by calculating an offset signal and subtracting the offset signal from the measurement data, thereby mitigating the effects of background noise and improving the signal-to-noise ratio of the measurement. Some embodiments of this disclosure involve performing the subtraction or reduction of the background current during signal processing (e.g., when processing data via the analyte sensor device 402 and / or the analyte readout device 404) without requiring further modification of the analyte sensor device 402 with an additional membrane layer or alteration of the sensor's control voltage. As mentioned above, background reduction is particularly beneficial when measuring target analyte concentrations at the lower end of the operating range, which may have a relatively low signal-to-noise ratio without further processing. However, according to embodiments of this disclosure, analytes with higher concentrations (such as glucose) will also benefit from background reduction.

[0131] As an example, Figure 6 It is a graph depicting the measured raw current passing through the analyte sensor and the individual background sensor. For example... Figure 6As shown, the current detected by the background sensor is similar in magnitude to the current detected by the analyte sensor (e.g., the analyte signal and the background signal are approximately the same order of magnitude), and therefore a significant component of the output of the analyte sensor is the background signal corresponding to the output of the background sensor.

[0132] Other factors that can affect the performance of analyte sensors (such as glucose sensors) include: system malfunctions (such as LSA), time lag between analyte levels in blood and interstitial fluid (ISF), sensor calibration bias, and sensor calibration slope. Figure 7 Results from several sensor studies performed using computer simulation models (e.g., mathematical simulations) are described to examine the effects of various factors on low-end accuracy measures (e.g., accuracy at the low end of the concentration range, where the signal-to-noise ratio can be minimal), where 100% represents all data points falling within the threshold consistency range with a reference value, and 0% represents no data points falling within the threshold consistency range. In the baseline case, the computer simulation model for each study represents different degrees of these factors. Case 1 simulates the removal of the effects of system failures (e.g., LSA). Case 2 simulates the removal of system failures and the removal of the time lag between blood analyte levels and interstitial fluid analyte levels. Cases 3 through 6 further build upon Case 2: Case 3 further simulates the removal of offset variations; Case 4 also simulates the removal of slope variations; Case 5 simulates the removal of mean offset; and Case 6 simulates the removal of mean slope error. Of these cases, Case 3 appears to provide the greatest improvement across all six different studies. Thus, the ability to detect background current would likely reduce offset variations.

[0133] Reduce global background current

[0134] Some aspects of embodiments of this disclosure relate to reducing global background current to improve sensor measurement accuracy. These embodiments of this disclosure can be applied to all electrochemical biosensor applications, regardless of the target analyte concentration range, although embodiments of this disclosure may provide more significant improvements at the lower end of the analyte concentration range (e.g., peroxides, ketones, glucose, lactate, etc.).

[0135] As mentioned above Figure 6 As described, the signal detected by the background sensor (e.g., current) is similar in magnitude to the current detected by the analyte sensor (e.g., the analyte signal and the background signal are approximately of the same order of magnitude), and therefore a significant component of the analyte sensor's output is the background signal corresponding to the background sensor's output. Therefore, removing or reducing the background signal from the output of the analyte sensor (e.g., peroxide sensor, glucose sensor, etc.) will improve the accuracy of the analyte sensor.

[0136] Overall, the background current level varies over time and is typically not flat throughout the analyte sensor's wear cycle. For example, in Figure 6 In the specific example shown, the background current level changes over time and decreases slowly in the early stages of wear (a phenomenon known as the "run-in" effect) before stabilizing at a fairly high offset value (approximately 200 pA).

[0137] Figure 8 It is a graph describing the outputs of several different background sensors measured from several different subjects. For example... Figure 8 As shown, the background current distribution across subjects / wearing devices is similar, but not identical. For example, all subjects exhibit an initial high current level of approximately 800 pA, which gradually decreases during the first 50 hours (approximately two days) of the wearing cycle and remains at a relatively stable level for the remainder of the wearing cycle. Therefore, some aspects of embodiments of this disclosure involve calculating global background correction across subjects. While embodiments of this disclosure are not limited thereto, for Figure 8 The specific data set shown, based on a combination of background signals measured from different subjects, defines the global time-varying subtraction model (or statistical model) as the background current (in pA), as follows:

[0138] C = 450 * exp(-0.065 * T) + 380

[0139] Where T is the time in hours from when the sensor is activated.

[0140] Figure 9A and Figure 9B These are graphs depicting the sensor traces before and after subtracting the global background current, according to some embodiments of this disclosure. More specifically, Figure 9A and Figure 9B Each subplot, from top to bottom, includes two graphs: one corresponding to the sensor current in picoamperes (pA) and the other to the molar concentration of the analyte based on sensor data in millimoles (mM). Figure 9A In this context, the sensor current corresponds to the original sensor current, and... Figure 9B In this diagram, the sensor current corresponds to the corrected sensor current after subtracting the global background current. A subplot showing the molar concentration of the analyte calculated based on interstitial fluid sensor data also uses triangles to depict reference analyte levels (e.g., calculated based on the analyzed blood sample).

[0141] like Figure 9A and Figure 9B As shown, compared to not removing background current (such as...) Figure 9A Compared to (as shown), such as Figure 9BAs shown, after removing the background current, the calculated molar concentration of the analyte tracks the analyte reference more closely (triangle). In other words, the calculated molar concentration is more closely related to... Figure 9A It is closer to the middle one. Figure 9B References, especially in the early stages of wearing (e.g., the first 100 hours of wearing).

[0142] Figure 10A and Figure 10B This is a graph depicting the analyte concentration measurement calculated from an analyte reference value measured at a corresponding time point, based on interstitial fluid (ISF) sensor data. Ideally, the analyte concentration measurement based on ISF data is identical to the reference data, therefore the slope of the graph is 1, and the y-intercept or bias is 0. For example... Figure 10A As shown, in Figure 9A In the specific case shown, before subtracting or removing the global background current, the slope of the line fitted to the data is 0.49, and the y-intercept is 0.29. Figure 10B It shows in Figure 9B In the specific case shown, after subtracting the global background current, the slope of the line fitted to the data is 0.99 and the y-intercept is 0.023, thus reducing the background offset b by an order of magnitude (from 0.29 to 0.023) and the signal sensitivity m approximately doubles (from 0.49 to 0.99).

[0143] Therefore, aspects of embodiments of this disclosure relate to improving the accuracy of analyte sensors by reducing background current (e.g., by subtracting global background current).

[0144] Figure 11 This is a flowchart of a method 1100 for reducing background current according to one embodiment of the present disclosure. In various embodiments of the present disclosure, Figure 11 The operations described herein can be distributed among various components of the analyte monitoring system 100. For example, some or all of the operations can be performed by the analyte sensor device 102 or 402, and some or all of the operations can be performed by the analyte readout device 110 / 120 or 404. In the following discussion, these will be collectively referred to as the analyte monitoring system 100.

[0145] refer to Figure 11According to one embodiment of this disclosure, an analyte signal (e.g., measured by analyte sensor 104) is received from an analyte sensor. As mentioned above, the analyte can be, for example, a ketone, lactate, or glucose, but embodiments of this disclosure are not limited thereto. The analyte signal can be, for example, a digital signal processed by analog front-end 252. Furthermore, the analyte monitoring system 100 can perform temperature correction on the analyte signal, for example, adjusting or modifying the analyte signal to compensate for greater reactivity of the analyte with the electrode at higher temperatures (thus causing higher current and higher background current measurements at the same analyte concentration). Temperature correction can be performed based on the temperature measured at a time corresponding to the digital signal. The measured temperature can be collected by, for example, a temperature sensor 257 configured to measure the temperature at a local location of the analyte sensor 104, such as the skin surface temperature (TpSk) below the analyte sensor device 102 (e.g., at or near patch 105). In various embodiments of this disclosure, the measured temperature is averaged or smoothed over a time window. According to some embodiments of this disclosure, the temperature correction applied to both the background signal and the analyte signal is approximately 6.5% per degree Celsius.

[0146] In operation 1110, the analyte monitoring system 100 calculates an offset-corrected analyte signal by subtracting the offset from each analyte sensor (in the case of multiple analyte sensors and / or one or more background sensors). The offset can be based on, for example, a global time-varying background offset calculated based on a combination of sensor readings from different sensors and different users (as discussed above), such as C = 450 * exp(-0.065 * T) + 380; an individual background offset (e.g., a background offset calculated based on measurements specific to a particular patient monitored by the analyte monitoring system 100); or based on: a global non-time-varying offset; an individual non-time-varying offset; and / or a combination thereof, as will be discussed in more detail below.

[0147] In operation 1120, the analyte monitoring system 100 calculates the sensitivity at each analyte reference point from the calibrated analyte signal (e.g., m in the relationship between sensor analyte current and analyte concentration C, i = m * C + b) (where b is assumed to be zero in operation 1110 by subtracting the correction for the analyte signal from the background offset). The reference point may correspond to, for example, analyte concentrations measured using different techniques, such as measuring analyte levels in blood using finger puncture (FS).

[0148] In operation 1130, the analyte monitoring system 100 calculates the median of the sensitivity calculated in operation 1120 for each sensor within a time window (e.g., 72 hours to 168 hours) (which may be referred to herein as the median sensitivity for each sensor), and in operation 1140, the analyte monitoring system calculates analyte data based on the median sensitivity using the offset correction current i. The median sensitivity is a characterization of the in vivo sensitivity of the sensor over its entire sensor lifetime, wherein an in vivo sensitivity is calculated for each sensor. In some embodiments, the median sensitivity is calculated within a time window corresponding to the period during which the most stability is observed in sensors of the same type. After calculating the median sensitivity for each sensor, the in vivo median sensitivity is used to calculate analyte results for the entire sensor lifetime (e.g., 0 to 14 days, not just time windows such as 72 hours to 168 hours).

[0149] In some implementations, during operation 1150, the analyte monitoring system pairs the calculated analyte data with reference points, allowing for further downstream evaluation of system performance, such as sensor accuracy, precision, stability, and safety. Reference points correspond to blood analyte values ​​measured by an accurate system and are considered true values. These reference points are used to determine the sensitivity of each sensor by matching the calculated analyte data with reference data. By doing so, the calculated analyte data can be mapped to analyte values ​​without performing individual reference measurements. A system is considered more accurate when sensor results are closer to the reference data.

[0150] In addition to computing a global time-varying subtraction model, some aspects of embodiments of this disclosure involve computing additional or alternative background subtraction models. Some aspects of embodiments of this disclosure involve computing individual time-varying offsets for each specific patient (or subject) and / or for each specific wear of the device. Systems and methods for generating individual time-varying subtraction models are described in more detail below.

[0151] Additionally, some aspects of embodiments of this disclosure involve using a fixed offset (or a non-time-varying offset) instead of a time-varying offset. This embodiment may be more suitable for environments where the analyte monitoring system lacks the ability to perform time-varying calculations (e.g., due to the lack of a clock or timer), or where time-varying calculations may not be necessary (e.g., due to the availability of other correction factors, or due to differences in background signal and sensor batches between subjects, or the absence of differences).

[0152] In some embodiments of this disclosure, the offset is calculated based on a combination of global and individual offsets. For example, the offset used to correct the analyte signal in operation 1110 may be calculated based on a linear combination of global and individual offsets.

[0153] Both global and individual offsets (whether time-varying or non-time-varying) can be calculated based on historical data or based on sensor readings during wear (e.g., in real time).

[0154] For example, when calculating a global offset (time-varying or time-invariant) based on historical data, the global offset can be generated by combining background offsets from multiple different wears of different sensors worn by several different subjects (e.g., calculating an average, such as a mean). More specifically, when calculating a time-varying offset, the global offset at each time point is the average (e.g., a mean) of all background offsets from different wears. When calculating a time-invariant (or fixed) offset, the background offset of each individual can be averaged over the length of wear (e.g., across a 14-day wear cycle) (e.g., the mean or average of a low-pass filtered signal), and then the individual fixed background offsets from the individual can be averaged (e.g., a mean) to calculate the global background offset.

[0155] In some embodiments of this disclosure, different global offsets can be computed for different subject clusters, wherein subjects can be clustered based on the similarity of background offsets or based on the similarity of other physiological characteristics of patients or subjects. In some embodiments of this disclosure, unsupervised machine learning algorithms (such as K-means clustering) are used to perform clustering, where k is the number of clusters. In embodiments where multiple global offsets are defined for different patient clusters, a global offset suitable for a particular patient can be selected by identifying the cluster most similar to the patient (e.g., identifying which cluster the patient will be clustered into by the clustering algorithm) and applying the global offset associated with the identified most similar cluster.

[0156] Similarly, historical data from previous wear by an individual patient can be used to calculate the individual offset for a particular patient. In a manner similar to that described above for calculating the global average offset over multiple wears from multiple patients, some aspects of embodiments of this disclosure involve calculating the individual offset (fixed or time-varying) for a particular patient based on multiple background offsets measured over time from the same patient on several different wears. Therefore, embodiments of this disclosure allow for the customization of individual time-varying offsets to specific background offset characteristics of a patient.

[0157] When a patient first begins using the analyte monitoring system according to embodiments of this disclosure, there may be a lack of data for generating individual offsets based on previous wear. Therefore, as discussed above, a global offset can be initially applied, while individual offsets can be applied in later wears of the analyte sensor once sufficient individual historical background offset data has been collected. During intermediate periods, when some individual background offset data has been collected (but not enough information to develop a definitive individual model), a weighted combination of the global and individual offsets can be applied, as discussed above.

[0158] Measuring individual background offset

[0159] Some aspects of embodiments of this disclosure relate to systems and methods for measuring individual background shift. More specifically, some aspects of embodiments of this disclosure relate to analyte sensors or analyte sensor tails having multiple sensor channels.

[0160] Figure 12 This is a schematic diagram of a multichannel analyte sensor according to one embodiment of the present disclosure. Figure 13A and Figure 13B Each of the embodiments according to this disclosure is shown. Figure 12 3D and cross-sectional views of the multichannel analyte sensor.

[0161] Figure 12 An embodiment of an analyte sensor according to this disclosure is schematically illustrated. Sensor 1200 includes electrodes 1201, 1202, 1203, and 1204 on a base or external portion 1208 and an insertion tip or internal portion 1230. The sensor may be fully implanted in the user or may be configured such that only a portion 1230 is positioned within the user (internal) and another portion 1208 is positioned externally (externally) to the user or patient. For example, sensor 1200 may include an external portion 1208 positioned above the surface of skin 1210 and an internal portion 1230 (subcutaneous space 1220) positioned below the skin. In this embodiment, the base portion or external portion 1208 may include contacts (connected via trace 1240 to corresponding electrodes of the internal portion 1230) for connection to another device also external to the user, such as a transmitter unit. For example, in some embodiments, sensor 1200 corresponds to the analyte sensor 104 described above, and the other device external to the user corresponds to sensor electronics 250. Although Figure 4The embodiment shows four electrodes 1201, 1202, 1203 and 1204 arranged side by side on the same surface of the base 1208, but other configurations are conceivable, such as fewer or more electrodes, some or all electrodes on different surfaces of the base or existing on another base, some or all electrodes stacked together, electrodes of different materials and sizes, etc.

[0162] Figure 13A A perspective view of an embodiment of an electrochemical analyte sensor 1200 is shown. The electrochemical analyte sensor 1200 has a first portion 1208 (which may be characterized as a major portion in this embodiment) and a second portion (which may be characterized as a minor portion in this embodiment). The first portion 1208 is positioned above the surface of skin 1210. The second portion includes an insertion tip 1230 positioned below the skin (e.g., penetrating the skin and entering, for example, a subcutaneous space 1220), which contacts a user's biofluid (such as interstitial fluid). The insertion tip 1230 extends from the base 1208 of the electrochemical analyte sensor 1200. Contact portions 1248 of a first working electrode 1201, a second working electrode 1202, a counter electrode 1203, and a reference electrode 1204 are positioned on the portion of the sensor 1200 above the skin surface 1210. The subcutaneous portions 1243 of the first working electrode 1201, the second working electrode 1202, the counter electrode 1203, and the reference electrode 1204 are also shown in the second portion, particularly at the insertion tip 1230. A trace 1240 from the electrode at the tip to the contact point can be provided, such as... Figure 13A As shown. It should be understood that more or fewer electrodes can be provided on the sensor. For example, the sensor may include more than one working electrode, and / or the counter electrode and reference electrode may be a single counter electrode / reference electrode, etc.

[0163] Figure 13B It shows Figure 13A A cross-sectional view of a portion of the sensor 1200, particularly a cross-sectional view of a portion of the insertion tip 1230. Electrodes 1201, 1202, 1203, and 1204, as well as a substrate 1231 and a dielectric layer 1232, of the sensor 1200 are provided in a layered configuration or structure. For example, as... Figure 13B As shown, in one aspect, sensor 1200 (such as...) Figure 1 The analyte sensor 104 includes a substrate layer 1231 and a first conductive layer 1251 (containing, for example, carbon, gold, etc.) disposed on at least a portion of the substrate layer 1231, wherein the first conductive layer 1251 provides a portion of a first working electrode 1201. A first sensing layer 1261 disposed on at least a portion of the first conductive layer 1251 is also shown.

[0164] Still referencing Figure 13BA first insulating layer (such as a first dielectric layer 1232) is disposed or stacked on at least a portion of the first conductive layer 1251. Furthermore, a second conductive layer 1252 may be disposed or stacked on top of at least a portion of the first insulating layer (or dielectric layer) 1232. Similar to the first conductive layer 1251, the second conductive layer 1252 may also be made of carbon, gold, etc. Figure 13B As shown, the second conductive layer 1252 can provide a second working electrode 1202. A second sensing layer 1262 can be disposed on at least a portion of the second conductive layer 1252. In addition, a second insulating layer 1233 can be disposed on the second conductive layer 1252.

[0165] exist Figure 13B In the illustrated embodiment, a third conductive layer 1253 (including, for example, carbon, gold, etc.) is disposed on a portion of the substrate layer 1231 opposite to the first conductive layer 1251 (e.g., on the other side of the substrate layer 1231 along an axis perpendicular to or normal to the plane of the substrate layer 1231). The third conductive layer 1253 may provide a counter electrode 1203. A third insulating layer 1234 may be disposed on the third conductive layer 1253.

[0166] The fourth conductive layer 1254 can be disposed on the third conductive layer. For example... Figure 13B As shown, the fourth conductive layer 1254 can provide a reference electrode 1204, and in one aspect, it can include a layer 1264 of silver / silver chloride (Ag / AgCl), gold, etc., and a fourth insulating layer 1236 can be disposed on the fourth conductive layer 1254 to cover the layer 1264.

[0167] In this way, the sensor 1200 can be layered, such that at least a portion of each conductive layer is separated by a corresponding insulating layer (e.g., a dielectric layer).

[0168] Figure 13A and Figure 13B An embodiment in which the layers have different lengths is shown. However, the embodiments disclosed herein are not limited thereto. For example, in some embodiments, some or all of these layers may have the same or different lengths and / or widths.

[0169] In some embodiments, some or all of electrodes 1201, 1202, 1203, and 1204 may be disposed on different sides of substrate 1231 in a layered configuration as described above, or alternatively, may be disposed on the same side of substrate 1231 in an staggered depth arrangement and / or in a coplanar manner as shown, such that two or more electrodes may be positioned on the same plane on substrate 1231 (e.g., side-by-side (e.g., parallel) or at an angle relative to each other). For example, coplanar electrodes may include appropriate spacing between them and / or include dielectric or insulating material disposed between conductive layers / electrodes.

[0170] like Figure 13B As shown, in some embodiments, electrodes 1201, 1202, 1203, and 1204 are arranged on different sides of substrate 1231. In such embodiments, contact pads may be on the same or different sides of the substrate. For example, the electrodes may be on a first side, and their corresponding contacts may be on a second side; for example, traces connecting the electrodes and contacts may pass through the substrate (e.g., using vias or holes in substrate 1231).

[0171] Figure 13C A cross-sectional view of a multichannel analyte sensor according to one embodiment of the present disclosure is shown. Figure 13C The implementation methods shown are the same as Figure 13B The implementations shown are substantially similar, and similar reference numerals denote similar components, which will not be described again in this document. Figure 13C The embodiment shown also includes a third working electrode 1205, which includes a fifth conductive layer 1255 and may also include a third sensing layer 1265. A fifth insulating layer 1235 is disposed on the third conductive layer 1253, and the fifth conductive layer 1255 is disposed on the fifth insulating layer 1235. Figure 13C In the illustrated embodiment, the third insulating layer 1234, the fourth conductive layer 1254, layer 1264, and the fourth insulating layer 1236 are stacked on the fifth conductive layer 1255. As discussed in more detail below, according to some embodiments of this disclosure, the third working electrode 1205 can be used to measure individual background signals or background currents.

[0172] Figure 13B and Figure 13C Both descriptions depict a membrane 1207 surrounding the insertion tip 1230. According to some embodiments of this disclosure, the membrane 1207 acts as a mass transport limiting layer, such as an analyte flux regulating layer, which may be incorporated with the sensor to act as a diffusion-limiting barrier, thereby reducing the mass transport rate of an analyte (e.g., glucose or lactate) to the region surrounding the working electrode (e.g., the first working electrode 1201 and the second working electrode 1202). The mass transport limiting layer can be used to limit the flux of the analyte to the working electrode in the electrochemical sensor, making the sensor linearly responsive and easily calibrated over a wide range of analyte concentrations. The mass transport limiting layer may comprise a polymer and may be biocompatible. The mass transport limiting layer can perform multiple functions, such as providing the functions of a biocompatibility layer and / or an interference elimination layer.

[0173] In some embodiments, the mass transport confinement layer is a membrane composed of a cross-linked polymer containing heterocyclic nitrogen groups (such as a polymer of polyvinylpyridine and polyvinylimidazole). Electrochemical sensors equipped with such membranes exhibit considerable sensitivity and stability under various conditions, as well as a high signal-to-noise ratio.

[0174] According to some embodiments, the membrane is formed by in-situ crosslinking in an alcohol-buffered solution of a zwitterionic portion, a non-pyridine copolymer component, and optionally a hydrophilic or hydrophobic portion and / or another portion having other desired properties. The modified polymer may be made from a precursor polymer containing heterocyclic nitrogen groups. Optionally, hydrophilic or hydrophobic modifiers may be used to “fine-tune” the permeability of the resulting membrane to the analyte of interest. Optional hydrophilic modifiers (such as poly(ethylene glycol), hydroxyl, or polyhydroxyl modifiers) may be used to enhance the biocompatibility of the polymer or the resulting membrane.

[0175] Although Figure 12 , Figure 13A , Figure 13B and Figure 13C The foregoing discussion described an implementation comprising stacked, substantially flat layers; however, the embodiments disclosed herein are not limited thereto and can be implemented using other physical structures, such as a generally cylindrical layer configuration arranged around an axis (e.g., by dip coating).

[0176] Figure 14 This is a schematic diagram of the sensing layer of the working electrode according to one embodiment of the present disclosure. Specifically, Figure 14 The diagram illustrates a first sensing layer 1261 of a first working electrode 1201, a second sensing layer 1262 of a second working electrode 1202, and a third sensing layer 1265 of a third working electrode 1205, according to one embodiment of the present disclosure. Some sensing layers (such as the first sensing layer 1261 and the second sensing layer 1262) may include a catalyst capable of catalyzing a reaction of the analyte.

[0177] Some analytes (such as oxygen) can be directly electro-oxidized or electro-reduced on the sensor, and more specifically, directly electro-oxidized or electro-reduced on at least the working electrode of the sensor. For other analytes, such as glucose and lactate, the presence of at least one electron transfer agent and / or at least one catalyst can facilitate the electro-oxidation or electro-reduction of the analyte. Catalysts can also be used for those analytes (such as oxygen) that can be directly electro-oxidized or electro-reduced on the working electrode. For these analytes, each working electrode includes a sensing layer formed on a surface adjacent to the working electrode or on the surface of the working electrode (see, for example...). Figure 13B (Sensing layer 1261). In many embodiments, the sensing layer is formed near or on at least a small portion of the working electrode.

[0178] Various sensing layer configurations can be used. In some implementations, the sensing layer is deposited on the conductive material of the working electrode. The sensing layer may extend beyond the conductive material of the working electrode. In some cases, the sensing layer may also extend on other electrodes, for example, on a counter electrode and / or a reference electrode (or provide a counter / reference). The sensing layer may be integral with the material of the electrodes.

[0179] The sensing layer that is in direct contact with the working electrode may contain an electron transfer agent that directly or indirectly transfers electrons between the analyte and the working electrode, and / or a catalyst that promotes the reaction of the analyte.

[0180] The sensing layer, which is not in direct contact with the working electrode, may include a catalyst that facilitates the reaction of the analyte. However, such a sensing layer may not include an electron transfer agent that transfers electrons directly from the working electrode to the analyte, because the sensing layer is spaced apart from the working electrode. An example of this type of sensor is a glucose or lactate sensor, which includes an enzyme (e.g., glucose oxidase, glucose dehydrogenase, lactate oxidase, etc.) in the sensing layer. Glucose or lactate can react with a second compound in the presence of the enzyme. The second compound can then be electro-oxidized or electro-reduced at the electrode. Changes in the signal at the electrode indicate changes in the level of the second compound in the fluid and are proportional to changes in the glucose or lactate level, and therefore correlated with the analyte level.

[0181] In some embodiments that include more than one working electrode, one or more working electrodes do not have a corresponding sensing layer, or have a sensing layer that does not contain one or more components (e.g., electron transfer agents and / or catalysts) required for electrolytic analyte processing. Therefore, the signal at this working electrode corresponds to a background signal, which can be removed from the analyte signal obtained from one or more other working electrodes associated with the fully functional sensing layer, for example, by subtracting the signal.

[0182] In some embodiments, the sensing layer includes one or more electron transfer agents. The electron transfer agents that can be used are electroreducible and electrooxidizable ions or molecules with a redox potential several hundred millivolts higher or lower than the redox potential of a standard calomel electrode (SCE). The electron transfer agents can be organic, organometallic, or inorganic.

[0183] In some embodiments, the electron transfer agent has a structure or charge that prevents or substantially reduces diffusion loss of the electron transfer agent during the time the sample is analyzed. For example, electron transfer agents include, but are not limited to, redox substances bound to a polymer, which may in turn be disposed on or near a working electrode. The bond between the redox substance and the polymer can be covalent, coordinated, or ionic. Although any organic or organometallic redox substance can be bound to the polymer and used as an electron transfer agent, in some embodiments, the redox substance is a transition metal compound or complex, such as osmium, ruthenium, iron, and cobalt compounds or complexes. It should be appreciated that many of the redox substances described for use with a polymer component can also be used without the polymer component.

[0184] One type of polymeric electron transfer agent comprises a redox substance covalently bound to a polymeric composition. An example of this type of mediator is poly(vinylferrocene). Another type of electron transfer agent comprises an ionically bound redox substance. This type of mediator can comprise a charged polymer coupled to a redox substance with an opposite charge. Examples of this type of mediator include a negatively charged polymer coupled to a positively charged redox substance (such as osmium or ruthenium polypyridyl cation). Another example of an ionically bound mediator is a positively charged polymer, such as quaternized poly(4-vinylpyridine) or poly(1-vinylimidazole), coupled to a negatively charged redox substance (such as ferricyanide or ferrocyanide). In other embodiments, the electron transfer agent comprises a redox substance coordinated to the polymer. For example, the mediator can be formed by coordination of an osmium or cobalt 2,2′-bipyridine complex with poly(1-vinylimidazole) or poly(4-vinylpyridine).

[0185] Suitable electron transfer agents are osmium transition metal complexes having one or more ligands, each ligand having a nitrogen-containing heterocycle, such as 2,2′-bipyridine, 1,10-phenanthroline, or derivatives thereof. Electron transfer agents may also have one or more ligands covalently bound to a polymer, each ligand having at least one nitrogen-containing heterocycle, such as pyridine, imidazole, or derivatives thereof. This disclosure can employ electron transfer agents having a redox potential ranging from about -100 mV to about +150 mV relative to a standard calomel electrode (SCE) (e.g., ranging from about -100 mV to about +150 mV, e.g., ranging from about -50 mV to about +50 mV), for example, electron transfer agents having an osmium redox center and a redox potential ranging from +50 mV to -150 mV relative to the SCE.

[0186] The sensing layer may also include a catalyst capable of catalyzing a reaction of the analyte. In some embodiments, the catalyst may also act as an electron transfer agent. Examples of suitable catalysts are enzymes that catalyze reactions of the analyte. For example, when the analyte of interest is glucose, catalysts such as glucose oxidase, glucose dehydrogenase (e.g., pyrroloquinolinequinone glucose dehydrogenase (PQQ) or oligosaccharide dehydrogenase) may be used. When the analyte of interest is lactate, lactate oxidase or lactate dehydrogenase may be used. When the analyte of interest is oxygen or when oxygen is generated or consumed in response to a reaction of the analyte, laccase may be used.

[0187] In some embodiments, the catalyst can be attached to a polymer, crosslinking the catalyst with another electron transfer agent (as described above, which may be polymerized). In some embodiments, a second catalyst may also be used. This second catalyst can be used to catalyze the reaction of a product compound generated from the catalytic reaction of the analyte. The second catalyst can operate together with the electron transfer agent to electrolyze the product compound to generate a signal at the working electrode. Alternatively, a second catalyst can be provided in an interference elimination layer to catalyze the reaction that removes interferences.

[0188] Some implementations include WiredEnzyme, which operates at a mild oxidation potential (e.g., a potential of about -40 mV). TM Sensing layer. This sensing layer uses an osmium (Os)-based mediator designed for low-potential operation and is stably anchored within a polymer layer. Thus, in some embodiments, the sensing element is a redox-active component comprising (1) an osmium-based mediator molecule linked by a stable (bident) ligand anchored to the polymer backbone and (2) a glucose oxidase molecule. These two components are cross-linked together.

[0189] exist Figure 14 In the illustrated embodiment, the first sensing layer 1261 has a first active region 1411 on which a catalyst (e.g., an enzyme) is deposited; the second sensing layer 1262 has a second active region 1420 on which a catalyst is deposited, wherein the second active region may have two sub-regions 1421 and 1422; and the third sensing layer 1265 may not have a catalyst deposited on it, or in other words, no catalyst is deposited on the third sensing layer 1265. According to some embodiments of the invention, portions of the second sensing layer 1262 and the third sensing layer 1265 on which no catalyst for reaction with the analyte is deposited may also contain dummy catalysts for providing redox sensitivity.

[0190] like Figure 14As shown, according to some embodiments of this disclosure, the surface area of ​​the catalyst deposited on different sensing layers (such as the first sensing layer 1261, the second sensing layer 1262, and the third sensing layer 1265) may differ between the sensing layers. For example, the first sensing layer 1261, the second sensing layer 1262, and the third sensing layer 1265 may have the same total surface area, but the surface area of ​​the active region or area containing the catalyst (or enzyme) may differ. Figure 14 In the specific example shown, the surface area of ​​the first active region 1411 of the first sensing layer 1261 is twice the surface area of ​​the second active region 1420 of the second sensing layer 1262 (equivalently, the surface area of ​​the second active region 1420 can be considered as half the surface area of ​​the first active region 1411). Therefore, according to some embodiments of this disclosure, the first sensing layer 1261 has a first active region 1411, the surface area of ​​which is larger than the surface area of ​​the second active region 1420 of the second sensing layer 1262. In some embodiments, the first active region 1411 of the first sensing layer 1261 has a larger amount of catalyst than the second active region 1420 of the second sensing layer 1262.

[0191] As described above, according to some embodiments of the present disclosure, the third sensing layer 1265 does not include an active region in which a catalyst is disposed, although embodiments of the present disclosure are not limited thereto.

[0192] Although Figure 14 The first active region 1411 is described as having a single continuous region, but embodiments of this disclosure are not limited to this and may have, for example, multiple non-continuous sub-regions.

[0193] Although Figure 14 The second active region 1420 is described as having two non-contiguous sub-regions 1421 and 1422, but embodiments of this disclosure are not limited thereto, and the second active region may include, for example, a single contiguous active region or two or more non-contiguous sub-regions.

[0194] Although Figure 14 The present disclosure describes an active region in which an enzyme or catalyst is deposited as a substantially flat rectangular shape; however, embodiments thereof are not limited thereto, and the enzyme or catalyst may be deposited in other shapes, such as a substantially flat circle, or may have a three-dimensional shape, such as a rectangular prism, cylinder, hemisphere, etc.

[0195] Although Figure 14The second sensing layer 1262 is described as having a smaller area on which the catalyst is deposited than that of the first sensing layer 1261, but embodiments of the present disclosure are not limited thereto. For example, in some embodiments of the present disclosure, the area of ​​the second sensing layer 1262 on which the catalyst is deposited is the same as the area of ​​the first sensing layer 1261 (in other words, the amount or quantity of catalyst or enzyme deposited on the first sensing layer 1261 and the second sensing layer 1262 is the same).

[0196] Although Figure 13B and Figure 13C The first sensing layer 1261 of the first working electrode 1201 and the second sensing layer 1262 of the second working electrode 1202 are described as being located on the same side of the substrate 1231, but the embodiments of this disclosure are not limited thereto. For example, the second sensing layer 1262 may be located on the side of the substrate 1231 opposite to the first sensing layer 1261 (e.g., on the same side of the substrate 1231 as the counter electrode 1203).

[0197] Although Figure 13C An embodiment including three working electrodes has been described, including a first working electrode, a second working electrode, and a third working electrode; however, embodiments of this disclosure are not limited thereto. For example, in some embodiments of this disclosure, a first working electrode 1201 configured to detect an analyte and a third working electrode 1205 configured to detect individual background shift may be used together without including a second working electrode 1202 on the insertion tip 1230. Equivalently or similarly, the second sensing layer 1262 of the second working electrode 1202 may be substantially similar to... Figure 14 The third sensing layer 1265 described herein may not contain a catalyst that interacts with the target analyte.

[0198] Background current was detected using a multi-channel analyte sensor.

[0199] Some aspects of embodiments of this disclosure involve using multiple sensors to detect background currents from an individual in real time. According to some embodiments of this disclosure, the detected background current, or the detected background signal, can then be used to correct the analyte signal output from the analyte sensor by reducing or removing background noise.

[0200] As discussed above, some aspects of this disclosure involve subtracting or reducing the background current in a detected analyte signal by adjusting the signal based on a global background offset (time-varying or time-invariant).

[0201] According to some embodiments of this disclosure, multichannel analyte sensors (such as those described above) Figure 12 , Figure 13A , Figure 13B , Figure 13C and Figure 14The described analyte sensor is used to simultaneously detect both analyte signals from the patient and individual background signals.

[0202] According to some embodiments of this disclosure, signals measured by the first working electrode 1201 and the second working electrode 1202 are used to perform background current removal.

[0203] As discussed above, the analyte sensor can be configured to output a signal according to the relationship i = m * C + b, where i is the measurement current of the analyte sensor, m is the sensitivity of the analyte sensor, C is the concentration of the analyte, and b is the offset corresponding to the background signal.

[0204] According to some embodiments, the first sensing layer 1261 of the first working electrode 1201 and the second sensing layer 1262 of the second working electrode 1202 have different sensitivities m due to the different surface areas (or sizes) of their respective active regions. In the above example, the second sensing layer 1262 comprises half the catalyst of the first sensing layer 1261, and therefore the sensitivity m2 of the second sensing layer 1262 can be approximately half the sensitivity m1 of the first sensing layer 1261 (m2 ≈ 0.5 * m1). Generally speaking, the ratio k can represent the amount (or surface area) of catalyst deposited on the second sensing layer 1262 divided by the amount of catalyst deposited on the first sensing layer 1261, such that m2 ≈ k * m1.

[0205] Figure 15A and Figure 15B These are graphs showing in vitro calibration data for dual glucose sensors with different sensitivities, calibrated using analytes and interfering agents, respectively. Ascorbic acid is a known example of an interfering agent; it reacts with the working electrode in a manner similar to glucose, thus potentially causing false positive readings when glucose is the target or analyte of interest.

[0206] Figure 15A and Figure 15B Each of these includes a measurement current relating to the concentration of glucose or ascorbic acid for a first current WE1 measured from a first working electrode (e.g., first working electrode 1201) and a second current WE2 measured from a second working electrode (e.g., second working electrode 1202), wherein the first working electrode 1201 has approximately twice the glucose sensing area of ​​the second working electrode 1202 (e.g., with...). Figure 14 Consistently, the effective area of ​​the first working electrode is approximately twice that of the second working electrode. Each graph also plots the difference between the two measured currents, WE1-WE2. Each trace is the average value (mean) of the six sensors.

[0207] Table 1 provides Figure 15A and Figure 15BAn overview of the in vitro calibration data is shown.

[0208]

[0209]

[0210] For each of the six sensors tested, the ratios between glucose sensitivity, ascorbic acid sensitivity, and these two values ​​are listed for the signals obtained from WE1 and WE2, and the differential signal obtained by subtracting WE2 from WE1 (Δ(WE1-WE2)). The averages of these values ​​for the six sensors tested are also listed. Note that the ratio between glucose sensitivity and ascorbic acid sensitivity is highest for each of the six sensors tested when the differential signal obtained by subtracting WE2 from WE1 is used as a measurement.

[0211] In the embodiment shown above, the first working electrode 1201 (WE1) and the second working electrode 1202 (WE2) have similar total areas. Therefore, it is desirable for the two working electrodes to detect approximately the same background current. On the other hand, because they deposit different amounts of catalyst on their respective sensing layers, their sensitivity varies with the ratio k, as described above.

[0212] The first current i1 or WE1 measured by the first working electrode 1201 can be interpreted as the sum of the signal m1*C corresponding to the analyte concentration and the background shift b:

[0213] WE1 = m1*C + b

[0214] Similarly, the second current i2 or WE2 measured by the second working electrode 1202 can be interpreted as the sum of the signal m2*C corresponding to the concentration of the analyte and the background offset b:

[0215] WE2=m2*C+b

[0216] Since we assume m2≈k*m1, the second current WE2 or i2 can be expressed as:

[0217] WE2=k*m1*C+b

[0218] Furthermore, assuming that the background offset b measured by the first working electrode and the second working electrode is essentially the same, WE1-WE2 can be expressed as:

[0219] WE1-WE2=(m1*C+b)-(k*m1*C+b)

[0220] =m1*C+bk*m1*Cb

[0221] =m1*Ck*m1*C+bb

[0222] = (1-k)*m1*C

[0223] Therefore, the calculated difference WE1-WE2 corresponds to a scaled version of the analyte concentration with virtually no individual background signal b. Reasonable estimates of the values ​​m1 and k, or equivalently m1 and m2, are known in advance through the sensor design and may be combined with information from production batch samples.

[0224] Similarly, the background signal b can be calculated by scaling the above WE1-WE2 values ​​and subtracting the scaling value from the initial measured current WE1 or WE2. For example, assume:

[0225] WE1-WE2=(1-k)*m1*C

[0226] Then

[0227]

[0228] Therefore, starting with the measuring current WE1 passing through the first working electrode 1201:

[0229] WE1 = m1*C + b

[0230]

[0231]

[0232] Alternatively, in some implementations, similar calculations can be performed based on WE2, such as:

[0233] WE2=k*m1*C+

[0234]

[0235]

[0236] Figure 16 This is a flowchart of a method 1600 for calculating and / or removing individual background offsets according to one embodiment of this disclosure. Figure 16 In the illustrated embodiment, in operation 1610, the analyte monitoring system 100 detects an analyte signal (or a first analyte signal) from a first working electrode (e.g., first working electrode 1201) of the analyte sensor, and in operation 1620, the analyte monitoring system 100 detects a second analyte signal from a second working electrode (e.g., second working electrode 1202) of the analyte sensor. In some embodiments of this disclosure, the first analyte signal and the second analyte signal are detected simultaneously and / or substantially simultaneously.

[0237] In operation 1630, the analyte monitoring system 100 calculates the difference between a first analyte signal and a second analyte signal. For example, the first analyte signal may correspond to a current WE1 measured from a first working electrode, as discussed above, and the second analyte signal may correspond to a current WE2 measured from a second working electrode, as discussed above, such that the difference between the first analyte signal and the second analyte signal may correspond to the difference WE1-WE2.

[0238] Therefore, in operation 1640, the analyte monitoring system 100 calculates the adjusted analyte data based on the difference between the (first) analyte signal and the second analyte signal (WE1-WE2).

[0239] For example, in some implementations, the difference WE1-WE2 is output as adjusted analyte data (in some implementations, a 1-k factor is used to interpret, for example, the sensitivity of the adjusted analyte data by some scaling factor).

[0240] In some implementations, the analyte monitoring system 100 calculates individual offsets, as discussed above. The calculated individual offsets can then be further processed to calculate offsets, as discussed in more detail below.

[0241] In some embodiments of this disclosure, the insertion tip 1230 includes a working electrode that does not include an additional catalyst or enzyme. (See above regarding...) Figure 13C and Figure 14 In the specific example discussed, the third working electrode 1205 includes a third sensing layer 1265 that contains no (or substantially no) catalyst (e.g., a catalyst deposited on the active region 1411 of the first sensing layer 1261 to react with the target analyte). Therefore, the signal or current measured by the third working electrode 1205 can be assumed to be a measurement of a background signal or background current, since the third sensing layer 1265 of such a third working electrode 1205 is substantially unresponsive to the target analyte. Thus, embodiments of this disclosure including working electrodes that are substantially free of catalyst or do not contain a catalyst for reacting with the target analyte can be used to measure background signals or background currents directly from the patient's interstitial fluid.

[0242] Therefore, aspects of embodiments of this disclosure relate to systems and methods for removing or detecting individual background signals of a patient.

[0243] In another scenario, the offsets may be different. After identifying the common offset as previously described, in some aspects of embodiments of this disclosure, relative offsets can be identified to further improve the accuracy of the system. As described above, using known values ​​of m1 and m2 and an estimated value of offset b, adjustments y1 and y2 can be calculated at any time t (as shown, for example, in...). Figure 17 (Top sub-figure in the image).

[0244] y1 = [WE1 - b] / m1

[0245] y2=[WE2-b] / m2

[0246] Let TW be a time window (e.g., TW could be 4 hours, 12 hours, or 24 hours), where it is assumed that the magnitude of the relative offset is sufficiently constant. At any given time t, it is assumed that there exist Nw-adjusted quantities y1 and y2 from both electrodes in the time instance between t and t-TW. These Nw-adjusted quantities are collected into a time pair set (y1(1), y2(1)), (y1(2), y2(2)), (y1(3), y2(3)), ..., (y1(Nw), y2(Nw)).

[0247] In one implementation, the offset of y1 relative to y2 is estimated by finding parameters associated with the following relationship based on the adjustment amount Nw:

[0248] y1=K1*y2+δ

[0249] K1 and δ can be determined using various methods, such as linear regression, orthogonal regression, or Deming regression. Figure 17 The bottom subplot illustrates the determination of δ using a TW equal to 96 hours. Then, in addition to the common offset, if y2 is determined to be more reliable than y1 within the most recent time window TR, the relative offset can be removed from y1, where TR can be the same time window as TW or a different time window. For example, it could be 2 hours, 6 hours, or 24 hours. The criterion for determining which of the two adjustments (y1 relative to y2) is more reliable can be based on the statistical properties of each channel (e.g., variance, standard deviation, power spectral density, etc.) or the relative statistical properties of the two channels (e.g., which one has a larger standard deviation).

[0250] For example, if it is currently determined that y2 is more reliable than y1, then the analytical value yv based on y1 is adjusted using the latest δ estimate:

[0251] yv=y1-δ

[0252] exist Figure 17 The top subplot shows an illustration of this adjustment value.

[0253] If y2 is determined to be more reliable than y1 and the latest δ estimate is less than the first negative threshold K-1, then y1 can be determined to be experiencing a system failure (such as LSA). In one implementation, this triggers the end of the sensor lifetime. In another implementation, the analyte value yv is still used based on the adjustment yv = y1 - δ, provided that the latest δ estimate is less than the second negative threshold K-2, but greater than the more negative threshold K-3, and the end of the sensor lifetime is triggered when the δ estimate is less than the third negative threshold K-3.

[0254] If it is currently determined that y1 is more reliable than y2, then the presented analytical value yv based on y1 does not need to be adjusted using the latest δ estimate (e.g., δ = 0):

[0255] yv=y1-0

[0256] An estimate of the offset of y2 relative to y1 can be calculated by following the same procedure described, by switching the roles of y1 and y2.

[0257] In another implementation, the common offset b can be zero, and only the relative offset δ is determined. The described procedure can be accomplished by setting b to zero.

[0258] Calculate the offset from one or more individual offsets and the global offset.

[0259] As mentioned above Figure 11 As discussed, in various embodiments of this disclosure, the offset can be calculated based on fixed and / or time-varying offsets, wherein the offset can be global or individual.

[0260] According to some embodiments of this disclosure, as referred to above... Figure 8 The discussion focuses on calculating global background offset based on data from several different sensor wears on several different patients. Global background offset can include time-varying global background offset and non-time-varying global background offset. Time-varying global background offset is based on the elapsed time from the start of wear, while non-time-varying global background offset remains a fixed or constant value over time.

[0261] According to some embodiments of this disclosure, individual background shifts can be calculated based on measurements from a specific patient. For example, as described above, a multi-channel analyte sensor (see, for example, Figure 16(as described above) and / or by using a dedicated working electrode for measuring background signals to measure the background signal of a specific patient. Individual background signals or individual background currents measured during a specific wearing period can be used "in real time" to calculate the offset. Furthermore, in some embodiments of this disclosure, the analyte monitoring system 100 stores individual background offsets measured during various wearing periods as historical individual background offsets and calculates an individual background model (or statistical model) based on the historical individual background offsets, such as by calculating the average of the historical individual background offsets (in some embodiments, outlier historical individual background offsets are removed before calculating the model).

[0262] Return to reference Figure 11 In some embodiments of this disclosure, the analyte monitoring system 100 subtracts an offset from the analyte signal during operation 1110. In various embodiments of this disclosure, the analyte monitoring system 100 obtains the offset based on one or more of time-varying or time-invariant (or fixed) global offsets and individual offsets, such as those described above.

[0263] In some embodiments of this disclosure, the analyte monitoring system 100 applies only an offset based on a global background offset. The global background offset may be time-varying or time-invariant.

[0264] In some embodiments of this disclosure, the analyte monitoring system 100 applies an individual background offset individually. The individual background offset may be time-varying or time-invariant. As described above, the time-varying or time-invariant individual offset can be calculated in real time based on measurements obtained from the working electrodes of the analyte sensor, regardless of individual or global historical measurements. The time-varying or time-invariant individual offset can be calculated for a specific patient based on the patient's historical data to generate an individual historical background offset model (time-varying or time-invariant) throughout the wearable application. In some embodiments of this disclosure, the individual background offset is calculated based on a combination of the real-time individual background offset and the individual historical background offset model, such as through a linear combination (e.g., weighting the real-time individual background offset and the individual historical background offset model).

[0265] In some embodiments of this disclosure, any of the global background offsets described above is combined with any of the individual background offset models described above, for example, through a linear combination. For example, the global background offset and / or the individual background offset can be time-varying or time-invariant, and the individual background offset can be real-time, historical, or a combination thereof.

[0266] Therefore, aspects of embodiments of this disclosure relate to systems and methods for reducing or removing background signals from analyte signals.

[0267] Using a multi-channel sensor to detect late-stage sensor attenuation (LSA)

[0268] Some aspects of embodiments of this disclosure relate to systems and methods for detecting late sensor attenuation (LSA) using multichannel sensors. Experimental results show that when using multichannel sensors with interleaved (or different) depth sensing layers (such as, Figure 13A , Figure 13B as well as Figure 13C When using a multi-channel sensor (as shown in the diagram), the LSA effect appears faster in shallower channels than in deeper channels.

[0269] Figure 17 Measurements from two sensor data channels and the difference between the measurements from the two sensors are described over a 14-day wear period. Figure 17 In the embodiment shown, the two sensor data channels correspond to two different sensors simultaneously inserted into the same body. The concept described using this illustration can be applied to sensors designed with dual channels in a single filament (or sensor tail), or to two sensors on different filaments (or two different sensor tails), for example, as described above. Figure 13A , Figure 13B and Figure 13C As shown. In Figure 17 In the example shown, channel 2 began to experience late sensor degradation (LSA) after approximately 11 days. Figure 17 The middle subplot shows the difference (D) and relative difference (RD) between the two sensors, and these differences and relative differences begin to become increasingly negative after approximately 11 days of wear. The bottom subplot shows the offset obtained by calculating an orthogonal fit between the two channels, where the shift time window is used to determine which time pairs are used, and the number of days set (4 days in this example) to calculate the fixed gain used for the orthogonal fit. As in the D and RD plots, for this example, the offset from this orthogonal fit (in the bottom subplot) indicates the detectable change after approximately 10 days. The top plot also shows an adjusted version based on the data read from channel 2 based on the calculated fixed gain.

[0270] exist Figure 13A , Figure 13B and Figure 13C In the illustrated embodiment, the first sensing layer 1261 of the first working electrode 1201 and the second sensing layer 1262 of the second working electrode 1202 are located at different positions along the length of the insertion tip 1230. More specifically, the first sensing layer 1261 is described as being at the distal end of the second sensing layer 1262 relative to the point where the insertion tip 1230 connects to the substrate 1208 of the electrochemical analyte sensor 1200 (equivalently, the second sensing layer 1262 is close to the first sensing layer 1261). Thus, when the insertion tip 1230 is properly inserted into the patient, the first sensing layer 1261 (below the surface of the skin 1210) is deeper than the second sensing layer 1262.

[0271] Therefore, some aspects of embodiments of this disclosure involve detecting the onset of late sensor attenuation (LSA) by analyzing the outputs of two channels of a multichannel analyte sensor, wherein the two channels correspond to measurements from two analyte sensing layers located at different depths beneath the patient's skin surface. Typically, embodiments of this disclosure involve detecting the onset of LSA based on detecting the level of inconsistency between the outputs of the two channels.

[0272] In a system implementation where more than one glucose sensing channel is placed within a monofilament, wherein the primary and secondary channels are positioned at different depths relative to the insertion site, the analyte monitoring system 100 assumes that the probability of a fault (e.g., LSA) initiation is different between the two (or more) channels and is a function of the position (or depth) of the corresponding sensing layer. Furthermore, the system can allow different channels to have different sensitivities to analyte (e.g., glucose) concentrations (see, for example, the above). Figure 14 (Related discussion).

[0273] Figure 18 This is a flowchart of a method 1800 for detecting late sensor attenuation (LSA) according to one embodiment of this disclosure. Figure 18 In the illustrated embodiment, in operation 1810, the analyte monitoring system 100 detects an analyte signal (or a first analyte signal) from a first working electrode (e.g., first working electrode 1201) of the analyte sensor, and in operation 1820, the analyte monitoring system 100 detects a second analyte signal from a second working electrode (e.g., second working electrode 1202) of the analyte sensor. In some embodiments of this disclosure, the first analyte signal and the second analyte signal are detected simultaneously and / or substantially simultaneously.

[0274] According to one embodiment of this disclosure, the initiation of an LSA is detected by fitting signals from two or more channels (e.g., a first analyte signal and a second analyte signal) relative to each other. This fitting generates one or more parameters (such as slope and intercept), wherein one or more parameters may be fixed relative to the sensor's initiation based on a predetermined time window, and may allow one or more parameters to change over the duration of wear based on a movement time window of predetermined width. Then, in operation 1830, the parameters may be compared to each other to calculate one or more consistency measures, such as difference (D), relative difference (RD), and / or orthogonal fit, based on past data (e.g., based on a cumulative window from the start of wear or a movement or sliding window over a specific time period). Then, in operation 1840, the one or more consistency measures may be compared to one or more threshold levels. When one or more consistency measures indicate that the measurement difference exceeds a threshold level (or meets a threshold condition) or the parameter is outside a specific range of acceptable values, then in operation 1850, the analyte monitoring system determines that a system failure (such as an LSA) has occurred.

[0275] In some embodiments of this disclosure, the length of the movement time window can be adjusted based on sensor-wearing specific factors. For example, a longer time window may be used for sensor wear with higher diurnal glucose variability compared to sensor wear with lower diurnal glucose variability. In another instance, a longer time window may be required for sensor wear with frequent instances of rapid glucose variability compared to sensors with fewer instances of rapid glucose variability.

[0276] In some embodiments of this disclosure, in response to the detection of an LSA, the analyte monitoring system 100 may perform one or more further actions. In some embodiments, the analyte monitoring system 100 generates an alarm to notify the patient or user that the analyte sensor 102 has experienced a system failure. In some embodiments of this disclosure, the detected LSA indicates a fault in data from a shallower channel (e.g., the second working electrode 1202), but data from a deeper channel (e.g., the first working electrode 1201) may still be within the normal operating accuracy range. In some cases, the detection of the fault may necessitate the early termination and replacement of the analyte sensor device 102, and the analyte monitoring system 100 generates a corresponding alarm, which may be displayed on the analyte readout device 110 / 120.

[0277] In some embodiments of this disclosure, one or more parameters are used to reconstruct a fault-free signal by compensating for fitting parameters on channels experiencing system faults. According to some embodiments of this disclosure, a level of inconsistency (e.g., offset from orthogonal fitting) reflected by one or more metrics is used to construct a compensated signal on channels experiencing system faults (e.g., LSA). Reference Figure 17 As discussed above, orthogonal fitting can be used to calculate the fixed gain of the orthogonal fit. Together with the fixed gain from the orthogonal fit, the time-varying offset can be used to adjust... Figure 17 The example shown uses channel 2 to generate an adjusted or corrected time trace (labeled "Adj.ch.2(fixed gain)"), which is typically consistent with channel 1.

[0278] Therefore, in some embodiments of this disclosure, after detecting a temporary system failure, the analyte monitoring system 100 further applies a correction to the signal (e.g., a second analyte signal or a first analyte signal) to compensate for the temporary sensor failure or temporary sensor noise.

[0279] Although the invention has been described in conjunction with certain exemplary embodiments, it should be understood that the invention is not limited to the disclosed embodiments, but rather is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims and their equivalents.

Claims

1. An analytical apparatus, comprising: Communication circuits; as well as The processing circuit has a memory storing instructions that, when executed by the processing circuit, cause the processing circuit to perform the following operations: The system receives multiple analyte signals measured from an analyte sensor device having a sensor tail, the multiple analyte signals being received via the communication circuit, the multiple analyte signals including a first analyte signal received from a first working electrode having a first sensitivity and a second analyte signal received from a second working electrode having a second sensitivity lower than the first sensitivity; Adjusted analyte data is generated by reducing the background signal in the first analyte signal using an offset signal calculated based on the first analyte signal, the second analyte signal, and the difference between the first analyte signal and the second analyte signal, and includes at least the following: Calculate one or more consistency measures between the first analyte signal and the second analyte signal; In response to one or more consistency metrics exceeding a threshold indicating sensor failure, an orthogonal fit between the first analyte signal and the second analyte signal within a time window is calculated; a time-varying offset relative to the orthogonal fit is derived; and the time-varying offset is used to correct the first analyte signal to obtain adjusted analyte data. The analyte values ​​are calculated based on the adjusted analyte data; and The analytical values ​​are displayed on the display device.

2. The analytical apparatus according to claim 1, wherein, The memory further stores instructions that, when executed by the processing circuit, cause the processing circuit to perform the following operations: Display trend indicators; Display analyte levels; Generate an alarm; or Control the drug delivery device.

3. The analyzer apparatus according to claim 1, wherein, Reducing the background signal further includes: The offset is subtracted from the first analyte signal to generate an offset correction signal; Multiple sensitivities are calculated from the offset correction signal, each sensitivity corresponding to one of a plurality of analyte reference points; Calculate the median of multiple sensitivities within a time window; Based on the median of the plurality of sensitivities, the adjusted analyte data is calibrated to the offset correction signal; and The adjusted analyte data are paired with the plurality of analyte reference points.

4. The analyzer apparatus according to claim 3, wherein, The offset is calculated from the global time-varying background offset based on the time elapsed since the activation of the analyte sensor device, in order to calculate the offset correction signal.

5. The analyzer apparatus according to claim 3, wherein, The offset is a time-invariant offset.

6. The analytical apparatus according to claim 1, wherein, The analyte sensor device includes: The first working electrode is located at the tail of the sensor; and The second working electrode is located at the tail of the sensor.

7. The analyzer apparatus according to claim 6, wherein, The first working electrode has a first active region, and a first number of catalysts are disposed on the first active region. The second working electrode has a second active region, on which a second number of catalysts are arranged, and the surface area of ​​the second active region is smaller than the surface area of ​​the first active region.

8. The analyzer apparatus according to claim 6, wherein, The second working electrode is configured to measure the individual background current, and The second analyte signal is calculated based on the individual background current.

9. The analytical apparatus according to claim 1, wherein, The memory also stores instructions that, when executed by the processing circuit, cause the processing circuit to apply temperature correction to the first analyte signal based on the temperature from the temperature sensor of the analyte sensor device.

10. The analyzer apparatus according to claim 1, wherein, The sensor tail extends from the main body of the analyte sensor device, and The analyte sensor device includes: A first working electrode is located at the tail of the sensor, the first working electrode having a first sensing layer at a first position along the tail of the sensor; and A second working electrode is provided on the tail of the sensor, the second working electrode having a second sensing layer at a second position along the tail of the sensor, the second position being adjacent to the first position.

11. The analyzer apparatus according to claim 1, wherein, The sensor failure is due to late-stage sensor attenuation LSA.

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