Classifications

• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue
  • A61B5/1495—Calibrating or testing of in-vivo probes
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue
  • A61B5/14503—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue
  • A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue
  • A61B5/1468—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue using chemical or electrochemical methods, e.g. by polarographic means
  • A61B5/1486—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue using chemical or electrochemical methods, e.g. by polarographic means using enzyme electrodes, e.g. with immobilised oxidase
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
  • G16H40/40—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B2560/00—Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
  • A61B2560/02—Operational features
  • A61B2560/0223—Operational features of calibration, e.g. protocols for calibrating sensors

Definitions

• the detection of the level of glucose or other analytes, such as lactate, oxygen or the like, in certain individuals is vitally important to their health.
• the monitoring of glucose is particularly important to individuals with diabetes. Diabetics may need to monitor glucose levels to determine when insulin is needed to reduce glucose levels in their bodies or when additional glucose is needed to raise the level of glucose in their bodies.
• Devices have been developed for continuous or automatic monitoring of analytes, such as glucose, in bodily fluid such as in the blood stream or in interstitial fluid.
• analytes such as glucose
• Some of these analyte measuring devices are configured so that at least a portion of the devices are positioned below a skin surface of a user, e.g., in a blood vessel or in the subcutaneous tissue of a user.
• the resulting potential trauma to the skin and/or underlying tissue may, at times, result in instability of signals monitored by the sensor. This may occur in a number of analyte sensors, but not in all cases. This instability is characterized by a decrease in the sensor signal, and when this occurs, generally, the analyte levels monitored may not be reported, recorded or output to the user.
• Calibration is a process by which a conversion factor (or sensitivity) is determined and represented, in its simplest form, as a ratio of the electrical current generated by the analyte sensor to the reference blood glucose value (for example, from an in vitro blood glucose meter) associated in time (for example, relatively time corresponding) with the current signal from the analyte sensor.
• the sensitivity is constant throughout the life of the analyte sensor when positioned in fluid contact with an analyte of a user (such as interstitial fluid). In practice, however, the sensitivity may vary over time.
• ESA Early Sensitivity Attenuation
• the ESA condition may be a result of a physiological response to the introduction of the analyte sensor to the subcutaneous tissue, and may be present for any subcutaneously inserted analyte sensor.
• a typical standard calibration does not detect or manage the attenuated signal characteristics, and also may potentially update or modify the calibration sensitivity using the erroneous and attenuated sensor signal.
• the reported or resulting sensor data may be erroneously high when the sensor sensitivity has recovered after the termination of the signal attenuation event.
• Such high biased results may be clinically unsafe, as they may lead to missed hypoglycaemic events, or overdoses of medication such as insulin.
• sensor calibration is performed prior to an early signal attenuation event, erroneously low biased sensor data will likely result during the period of the sensor sensitivity depression.
• Such low glucose results may, depending on the magnitude of the early signal attenuation event, result in false hypoglycaemia alarms or missed hyperglycaemic events.
• Embodiments of the subject disclosure include device and methods of detecting a change, e.g., a decrease (or monitoring for a change in the signal level), in sensitivity associated with an analyte sensor to identify or detect early signal attenuation (ESA).
• ESA early signal attenuation
• the detected or monitored analyte level is reported or output after a short sensor equilibration time period (e.g., approximately one hour or more or less) when detected change is not associated with early signal attenuation.
• FIG. 1 shows a block diagram of an embodiment of a data monitoring and management system according to the present disclosure
• FIG. 2 shows a block diagram of an embodiment of the data processing unit of the data monitoring and management system of FIG. 1 ;
• FIG. 3 shows a block diagram of an embodiment of the receiver/monitor unit of the data monitoring and management system of FIG. 1;
• FIG. 4 shows a schematic diagram of an embodiment of an analyte sensor according to the present disclosure
• FIGS. 5A-5B show a perspective view and a cross sectional view, respectively of an embodiment the analyte sensor of FIG. 4;
• FIG. 6 is a flowchart illustrating an overall analyte sensor calibration management in accordance with one embodiment of the present disclosure
• FIG. 7 is a flowchart illustrating early signal attenuation (ESA) detection routine of FIG. 6 in accordance with one aspect of the present disclosure
• FIG. 8 is a flowchart illustrating early signal attenuation (ESA) categorization routine of FIG. 6 in accordance with one aspect of the present disclosure.
• FIG. 9 is a flowchart illustrating early signal attenuation (ESA) management routine of FIG. 6 in accordance with one aspect of the present disclosure.
• ESA early signal attenuation
• ESA early signal attenuation
• Analyte sensors may be manufactured and/or the trauma resulting from the inserted sensor may be such that the sensor attains a stability point or an equilibration level after a relatively short time period - for example, within approximately one hour (or less) from the initial sensor insertion.
• the signals from the analyte sensor may be monitored for ESA condition detection.
• the analyte monitoring system may be configured to request a reference blood glucose value from the user, for example, a fmgerstick in vitro test using a blood glucose meter, to calibrate the sensor signals, and thereafter, report or display to the user the monitored analyte levels.
• a reference blood glucose value from the user, for example, a fmgerstick in vitro test using a blood glucose meter
• the initial baseline calibration of the analyte sensor may be performed after approximately one hour from the initial sensor insertion, and upon successful calibration, the resulting real time analyte levels displayed to the user, or otherwise stored or logged in the analyte monitoring system and/or transmitted to a remote device or terminal.
• the analyte monitoring system may be configured to alert the user to wait a predetermined time period before providing the reference blood glucose value to provide the sensor to stabilize, or alternatively, the user may be prompted to provide the reference blood glucose value to confirm whether the potential ESA condition monitored is an actual occurrence of ESA condition.
• the scheduled calibration of the analyte sensor may be delayed to provide the sensor additional time period to reach a desired or acceptable stability level.
• boundaries may be established to provide the sensor additional time to reach a predetermined or acceptable stability level before the received analyte sensor signals are calibrated, and thus, provided to the user.
• other conditions and parameters may be provided to establish or detect ESA condition during a predetermined time period from the initial sensor insertion, for example, during the first 24 hours of sensor insertion.
• the analyte monitoring system may display or otherwise accept, output, log, or process the monitored analyte level, substantially in real time, received from the transcutaneously positioned sensor.
• the acceptable stability level is analyzed at approximately one hour from the initial sensor insertion, and thereafter, when no ESA condition is detected, the analyte sensor data is calibrated against a reference blood glucose value (for example, received from an in vitro glucose meter).
• the analyte monitoring system may be configured in one embodiment to perform one or more routines or functions to verify the sensor related signals to confirm the ESA condition, to notify the user to refrain from performing a f ⁇ ngerstick test using a blood glucose meter to provide a reference blood glucose value for calibration, among others.
• embodiments of the present disclosure relate to methods and devices for detecting at least one analyte such as glucose in body fluid.
• the present disclosure relates to the continuous and/or automatic in vivo monitoring of the level of one or more analyte using a continuous analyte monitoring system that includes an analyte sensor at least a portion of which is to be positioned beneath a skin surface of a user for a period of time and/or the discrete monitoring of one or more analytes using an in vitro blood glucose (“BG”) meter and an analyte test strip.
• BG in vitro blood glucose
• Embodiments include combined or combinable devices, systems and methods and/or transferring data between an in vivo continuous system and a BG meter system.
• embodiments include analyte monitoring devices and systems that include an analyte sensor- at least a portion of which is positionable beneath the skin of the user - for the in vivo detection, of an analyte, such as glucose, lactate, and the like, in a body fluid.
• an analyte such as glucose, lactate, and the like
• Embodiments include wholly implantable analyte sensors and analyte sensors in which only a portion of the sensor is positioned under the skin and a portion of the sensor resides above the skin, e.g., for contact to a transmitter, receiver, transceiver, processor, etc.
• the sensor may be, for example, subcutaneously positionable in a patient for the continuous or periodic monitoring of a level of an analyte in a patient's interstitial fluid.
• continuous monitoring and periodic monitoring will be used interchangeably, unless noted otherwise.
• the sensor response may be correlated and/or converted to analyte levels in blood or other fluids.
• an analyte sensor may be positioned in contact with interstitial fluid to detect the level of glucose, which detected glucose may be used to infer the glucose level in the patient's bloodstream.
• Analyte sensors may be insertable into a vein, artery, or other portion of the body containing fluid.
• Embodiments of the analyte sensors of the subject disclosure may be configured for monitoring the level of the analyte over a time period which may range from minutes, hours, days, weeks, or longer.
• analyte sensors such as glucose sensors, that are capable of in vivo detection of an analyte for about one hour or more, e.g., about a few hours or more, e.g., about a few days of more, e.g., about three or more days, e.g., about five days or more, e.g., about seven days or more, e.g., about several weeks or at least one month.
• Future analyte levels may be predicted based on information obtained, e.g., the current analyte level at time to, the rate of change of the analyte, etc.
• Predictive alarms may notify the user of predicted analyte levels that may be of concern prior in advance of the analyte level reaching the future level. This enables the user an opportunity to take corrective action.
• FIG. 1 shows a data monitoring and management system such as, for example, an analyte (e.g., glucose) monitoring system 100 in accordance with certain embodiments.
• an analyte e.g., glucose
• FIG. 1 shows a data monitoring and management system such as, for example, an analyte (e.g., glucose) monitoring system 100 in accordance with certain embodiments.
• analyte e.g., glucose
• the analyte monitoring system may be configured to monitor a variety of analytes at the same time or at different times.
• Analytes that may be monitored include, but are not limited to, acetyl choline, amylase, bilirubin, cholesterol, chorionic gonadotropin, creatine kinase (e.g., CK- MB), creatine, creatinine, DNA, fructosamine, glucose, glutamine, growth hormones, hormones, ketone bodies, lactate, peroxide, prostate-specific antigen, prothrombin, RNA, thyroid stimulating hormone, and troponin.
• concentration of drugs such as, for example, antibiotics (e.g., gentamicin, vancomycin, and the like), digitoxin, digoxin, drugs of abuse, theophylline, and warfarin, may also be monitored. In those embodiments that monitor more than one analyte, the analytes may be monitored at the same or different times.
• the analyte monitoring system 100 includes a sensor 101 , a data processing unit 102 connectable to the sensor 101, and a primary receiver unit 104 which is configured to communicate with the data processing unit 102 via a communication link 103.
• the primary receiver unit 104 may be further configured to transmit data to a data processing terminal 105 to evaluate or otherwise process or format data received by the primary receiver unit 104.
• the data processing terminal 105 may be configured to receive data directly from the data processing unit
• the data processing unit 102 may include a transmitter or a transceiver to transmit and/or receive data to and/or from the primary receiver unit 104, and/or the data processing terminal 105 and/or optionally the secondary receiver unit 106.
• an optional secondary receiver unit 106 which is operatively coupled to the communication link and configured to receive data transmitted from the data processing unit 102.
• the secondary receiver unit 106 may be configured to communicate with the primary receiver unit 104, as well as the data processing terminal 105.
• the secondary receiver unit 106 may be configured for bidirectional wireless communication with each of the primary receiver unit 104 and the data processing terminal 105.
• the secondary receiver unit 106 may be a de- featured receiver as compared to the primary receiver, i.e., the secondary receiver may include a limited or minimal number of functions and features as compared with the primary receiver unit
• the secondary receiver unit 106 may include a smaller (in one or more, including all, dimensions), compact housing or embodied in a device such as a wrist watch, arm band, etc., for example.
• the secondary receiver unit 106 may be configured with the same or substantially similar functions and features as the primary receiver unit 104.
• the secondary receiver unit 106 may include a docking portion to be mated with a docking cradle unit for placement by, e.g., the bedside for night time monitoring, and/or bi-directional communication device.
• a docking cradle may recharge a power supply.
• OnIy one sensor 101, data processing unit 102 and data processing terminal 105 are shown in the embodiment of the analyte monitoring system 100 illustrated in FIG. 1. However, it will be appreciated by one of ordinary skill in the art that the analyte monitoring system 100 may include more than one sensor 101 and/or more than one data processing unit 102, and/or more than one data processing terminal 105.
• analyte information obtained by a first positioned sensor may be employed as a comparison to analyte information obtained by a second sensor. This may be useful to confirm or validate analyte information obtained from one or both of the sensors. Such redundancy may be useful if analyte information is contemplated in critical therapy-related decisions.
• a first sensor may be used to calibrate a second sensor.
• the analyte monitoring system 100 may be a continuous monitoring system, or semi-continuous, or a discrete monitoring system.
• each component may be configured to be uniquely identified by one or more of the other components in the system so that communication conflict may be readily resolved between the various components within the analyte monitoring system 100.
• unique IDs, communication channels, and the like may be used.
• the sensor 101 is physically positioned in or on the body of a user whose analyte level is being monitored. The sensor 101 may be configured to at least periodically sample the analyte level of the user and convert the sampled analyte level into a corresponding signal for transmission by the data processing unit 102.
• the data processing unit 102 is coupleable to the sensor 101 so that both devices are positioned in or on the user's body, with at least a portion of the analyte sensor 101 positioned transcutaneously.
• the data processing unit 102 may include a fixation element such as adhesive or the like to secure it to the user's body.
• a mount (not shown) attachable to the user and mateable with the unit 102 may be used.
• a mount may include an adhesive surface.
• the data processing unit 102 performs data processing functions, where such functions may include but are not limited to, filtering and encoding of data signals, each of which corresponds to a sampled analyte level of the user, for transmission to the primary receiver unit 104 via the communication link 103.
• the sensor 101 or the data processing unit 102 or a combined sensor/data processing unit may be wholly implantable under the skin layer of the user.
• the primary receiver unit 104 may include an analog interface section including an RF receiver and an antenna that is configured to communicate with the data processing unit 102 via the communication link 103, and a data processing section for processing the received data from the data processing unit 102 such as data decoding, error detection and correction, data clock generation, data bit recovery, etc., or any combination thereof.
• the primary receiver unit 104 in certain embodiments is configured to synchronize with the data processing unit 102 to uniquely identify the data processing unit 102, based on, for example, an identification information of the data processing unit 102, and thereafter, to periodically receive signals transmitted from the data processing unit 102 associated with the monitored analyte levels detected by the sensor 101.
• the data processing terminal 105 may include a personal computer, a portable computer such as a laptop or a handheld device (e.g., personal digital assistants (PDAs), telephone such as a cellular phone (e.g., a multimedia and Internet-enabled mobile phone such as an iPhone or similar phone), mp3 player, pager, and the like), or drug delivery device, each of which may be configured for data communication with the receiver via a wired or a wireless connection. Additionally, the data processing terminal 105 may further be connected to a data network (not shown) for storing, retrieving, updating, and/or analyzing data corresponding to the detected analyte level of the user.
• a data network not shown
• the data processing terminal 105 may include an infusion device such as an insulin infusion pump or the like, which may be configured to administer insulin to patients, and which may be configured to communicate with the primary receiver unit 104 for receiving, among others, the measured analyte level.
• the primary receiver unit 104 may be configured to integrate an infusion device therein so that the primary receiver unit 104 is configured to administer insulin (or other appropriate drug) therapy to patients, for example, for administering and modifying basal profiles, as well as for determining appropriate boluses for administration based on, among others, the detected analyte levels received from the data processing unit 102.
• An infusion device may be an external device or an internal device (wholly implantable in a user).
• the data processing terminal 105 which may include an insulin pump, may be configured to receive the analyte signals from the data processing unit 102, and thus, incorporate the functions of the primary receiver unit 104 including data processing for managing the patient's insulin therapy and analyte monitoring.
• the communication link 103 as well as one or more of the other communication interfaces shown in FIG. 1 , may use one or more of an RF communication protocol, an infrared communication protocol, a Bluetooth enabled communication protocol, an 802.1 Ix wireless communication protocol, or an equivalent wireless communication protocol which would allow secure, wireless communication of several units (for example, per HIPPA requirements) while avoiding potential data collision and interference.
• FIG. 2 shows a block diagram of an embodiment of the data processing unit of the data monitoring and management system of FIG. 1.
• the data processing unit 102 thus may include one or more of an analog interface 201 configured to communicate with the sensor 101 (FIG. 1), a user input 202, and a temperature measurement section 203, each of which is operatively coupled to a processor 204 such as a central processing unit (CPU).
• the data processing unit 102 may include user input and/or interface components or may be free of user input and/or interface components.
• one or more application-specific integrated circuits (ASIC) may be used to implement one or more functions or routines associated with the operations of the data processing unit (and/or receiver unit) using for example one or more state machines and buffers.
• ASIC application-specific integrated circuits
• FIG. 2 is a serial communication section 205 which is operatively coupled to the processor 204.
• the data processing unit 102 may include a bi-directional communication link 209 between the analog interface 201 and the serial communication section 205.
• the data processing unit includes an RF transmitter 206, which is also operatively coupled to the processor 204.
• the RF transmitter 206 in some embodiments, may be configured as an RF receiver or an RF transmitter/receiver, such as a transceiver.
• a power supply 207 such as a battery, may also be provided in the data processing unit 102 to provide the necessary power for the data processing unit 102.
• clock 208 may be provided to, among others, supply real time information to the processor 204.
• the sensor unit 101 includes four contacts, three of which are electrodes - work electrode (W) 210, guard contact (G) 211 , reference electrode (R) 212, and counter electrode (C) 213, each operatively coupled to the analog interface 201 of the data processing unit 102.
• W work electrode
• G guard contact
• R reference electrode
• C counter electrode
• each of the work electrode (W) 210, guard contact (G) 21 1 , reference electrode (R) 212, and counter electrode (C) 213 may be made using a conductive material that may be applied by, e.g., chemical vapor deposition (CVD), physical vapor deposition, sputtering, reactive sputtering, printing, coating, ablating (e.g., laser ablation), painting, dip coating, etching, and the like.
• CVD chemical vapor deposition
• sputtering e.g., reactive sputtering
• printing e.g., coating, ablating (e.g., laser ablation), painting, dip coating, etching, and the like.
• ablating e.g., laser ablation
• Materials include but are not limited to aluminum, carbon (such as graphite), cobalt, copper, gallium, gold, indium, iridium, iron, lead, magnesium, mercury (as an amalgam), nickel, niobium, osmium, palladium, platinum, rhenium, rhodium, selenium, silicon (e.g., doped polycrystalline silicon), silver, tantalum, tin, titanium, tungsten, uranium, vanadium, zinc, zirconium, mixtures thereof, and alloys, oxides, or metallic compounds of these elements.
• the processor 204 may be configured to generate and/or process control signals to the various sections of the data processing unit 102 during the operation of the data processing unit 102.
• the processor 204 also includes memory (not shown) for storing data such as the identification information for the data processing unit 102, as well as the data associated with signals received from the sensor 101. The stored information may be retrieved and processed for transmission to the primary receiver unit 104 under the control of the processor 204.
• the power supply 207 may include a commercially available battery.
• a manufacturing process of the data processing unit 102 may place the data processing unit 102 in the lower power, non-operating state (i.e., post-manufacture sleep mode). In this manner, the shelf life of the data processing unit 102 may be significantly improved.
• the power supply unit 207 is shown as coupled to the processor 204, and as such, the processor 204 is configured to provide control of the power supply unit 207, it should be noted that within the scope of the present disclosure, the power supply unit 207 is configured to provide the necessary power to each of the components of the data processing unit 102 shown in FIG. 2.
• the power supply section 207 of the data processing unit 102 in one embodiment may include a rechargeable battery unit that may be recharged by a separate power supply recharging unit (for example, provided in the receiver unit 104) so that the data processing unit 102 may be powered for a longer period of usage time.
• the data processing unit 102 may be configured without a battery in the power supply section 207, in which case the data processing unit 102 may be configured to receive power from an external power supply source (for example, a battery, electrical outlet, etc.) as discussed in further detail below.
• an external power supply source for example, a battery, electrical outlet, etc.
• a temperature detection section 203 of the data processing unit 102 is configured to monitor the temperature of the skin near the sensor insertion site. The temperature reading may be used to adjust the analyte readings obtained from the analog interface 201. Also shown is a leak detection circuit 214 coupled to the guard trace (G) 21 1 and the processor 204 in the data processing unit 102 of the data monitoring and management system 100. The leak detection circuit 214 may be configured to detect leakage current in the sensor 101 to determine whether the measured sensor data are corrupt or whether the measured data from the sensor 101 is accurate. Such detection may trigger a notification to the user.
• FIG. 3 shows a block diagram of an embodiment of the receiver/monitor unit, such as the primary receiver unit 104, of the data monitoring and management system shown in FIG. 1.
• the primary receiver unit 104 includes one or more of: a blood glucose test strip interface 301 , an RF receiver 302, an input 303, a temperature monitor section 304, and a clock 305, each of which are operatively coupled to a processing and storage section 307.
• the primary receiver unit 104 also includes a power supply 306 operatively coupled to a power conversion and monitoring section 308. Further, the power conversion and monitoring section 308 is also coupled to the receiver processing and storage section 307.
• a receiver serial communication section 309, and an output 310 each operatively coupled to the processing and storage unit 307.
• the receiver may include user input and/or interface components or may be free of user input and/or interface components.
• the test strip interface 301 includes a glucose level testing portion to receive a blood (or other body fluid sample) glucose test or information related thereto.
• the interface may include a test strip port to receive a glucose test strip.
• the device may determine the glucose level of the test strip, and optionally display (or otherwise notice) the glucose level on the output 310 of the primary receiver unit 104.
• test strip Any suitable test strip may be employed, e.g., test strips that only require a very small amount (e.g., one microliter or less, e.g., 0.5 microliter or less, e.g., 0.1 microliter or less), of applied sample to the strip in order to obtain accurate glucose information, e.g. FreeStyle ® blood glucose test strips from Abbott Diabetes Care Inc.
• Glucose information obtained by the in vitro glucose testing device may be used for a variety of purposes, computations, etc.
• the information may be used to calibrate sensor 101 , confirm results of the sensor 101 to increase the confidence thereof (e.g., in instances in which information obtained by sensor 101 is employed in therapy related decisions), etc.
• the RF receiver 302 is configured to communicate, via the communication link 103 (FIG. 1) with the RF transmitter 206 of the data processing unit 102, to receive encoded data from the data processing unit 102 for, among others, signal mixing, demodulation, and other data processing.
• the input 303 of the primary receiver unit 104 is configured to allow the user to enter information into the primary receiver unit 104 as needed.
• the input 303 may include keys of a keypad, a touch-sensitive screen, and/or a voice-activated input command unit, and the like.
• the temperature monitor section 304 may be configured to provide temperature information of the primary receiver unit 104 to the processing and control section 307, while the clock 305 provides, among others, real time or clock information to the processing and storage section 307.
• Each of the various components of the primary receiver unit 104 shown in FIG. 3 is powered by the power supply 306 (or other power supply) which, in certain embodiments, includes a battery. Furthermore, the power conversion and monitoring section 308 is configured to monitor the power usage by the various components in the primary receiver unit 104 for effective power management and may alert the user, for example, in the event of power usage which renders the primary receiver unit 104 in sub-optimal operating conditions.
• the serial communication section 309 in the primary receiver unit 104 is configured to provide a bi-directional communication path from the testing and/or manufacturing equipment for, among others, initialization, testing, and configuration of the primary receiver unit 104. Serial communication section 309 can also be used to upload data to a computer, such as time -stamped blood glucose data.
• the communication link with an external device can be made, for example, by cable (such as USB or serial cable), infrared (IR) or RF link.
• the output/display 310 of the primary receiver unit 104 is configured to provide, among others, a graphical user interface (GUI), and may include a liquid crystal display (LCD) for displaying information. Additionally, the output/display 310 may also include an integrated speaker for outputting audible signals as well as to provide vibration output as commonly found in handheld electronic devices, such as mobile telephones, pagers, etc.
• the primary receiver unit 104 also includes an electro-luminescent lamp configured to provide backlighting to the output 310 for output visual display in dark ambient surroundings. Referring back to FIG.
• the primary receiver unit 104 may also include a storage section such as a programmable, non- volatile memory device as part of the processing and storage section 307, or provided separately in the primary receiver unit 104, operatively coupled to the processor.
• the processing and storage section 307 may be configured to perform Manchester decoding (or other protocol(s)) as well as error detection and correction upon the encoded data received from the data processing unit 102 via the communication link 103.
• the data processing unit 102 and/or the primary receiver unit 104 and/or the secondary receiver unit 106, and/or the data processing terminal/infusion section 105 may be configured to receive the blood glucose value wirelessly over a communication link from, for example, a blood glucose meter.
• a user manipulating or using the analyte monitoring system 100 may manually input the blood glucose value using, for example, a user interface (for example, a keyboard, keypad, voice commands, and the like) incorporated in the one or more of the data processing unit 102, the primary receiver unit 104, secondary receiver unit 106, or the data processing terminal/infusion section
• FIG. 4 shows a schematic diagram of an embodiment of an analyte sensor in accordance with the present disclosure.
• the sensor 400 includes electrodes 401 , 402 and 403 on a base 404.
• the sensor may be wholly implantable in a user or may be configured so that only a portion is positioned within (internal) a user and another portion outside (external) a user.
• the sensor 400 may include a portion positionable above a surface of the skin 410, and a portion positioned below the skin.
• the external portion may include contacts (connected to respective electrodes of the second portion by traces) to connect to another device also external to the user such as a transmitter unit. While the embodiment of FIG.
• FIG. 4 shows three electrodes side-by-side on the same surface of base 404, other configurations are contemplated, e.g., fewer or greater electrodes, some or all electrodes on different surfaces of the base or present on another base, some or all electrodes stacked together, electrodes of differing materials and dimensions, etc.
• FIG. 5 A shows a perspective view of an embodiment of an electrochemical analyte sensor 500 having a first portion (which in this embodiment may be characterized as a major portion) positionable above a surface of the skin 510, and a second portion (which in this embodiment may be characterized as a minor portion) that includes an insertion tip 530 positionable below the skin, e.g., penetrating through the skin and into, e.g., the subcutaneous space 520, in contact with the user's biofluid such as interstitial fluid.
• Contact portions of a working electrode 501, a reference electrode 502, and a counter electrode 503 are positioned on the portion of the sensor 500 situated above the skin surface 510.
• a counter electrode 503 are shown at the second section and particularly at the insertion tip 530. Traces may be provided from the electrode at the tip to the contact, as shown in FIG. 5 A. It is to be understood that greater or fewer electrodes may be provided on a sensor.
• a sensor may include more than one working electrode and/or the counter and reference electrodes may be a single counter/reference electrode, etc.
• FIG. 5B shows a cross sectional view of a portion of the sensor 500 of FIG. 5 A.
• the electrodes 501 , 502 and 503, of the sensor 500 as well as the substrate and the dielectric layers are provided in a layered configuration or construction.
• the sensor 500 (such as the sensor unit 101 FIG. 1), includes a substrate layer 504, and a first conducting layer 501 such as carbon, gold, etc., disposed on at least a portion of the substrate layer 504, and which may provide the working electrode. Also shown disposed on at least a portion of the first conducting layer 501 is a sensing layer 508.
• a first insulation layer such as a first dielectric layer 505 is disposed or layered on at least a portion of the first conducting layer 501 , and further, a second conducting layer 509 may be disposed or stacked on top of at least a portion of the first insulation layer (or dielectric layer) 505. As shown in FIG.
• the second conducting layer 509 may provide the reference electrode 502, and in one aspect, may include a layer of silver/silver chloride (Ag/AgCl), gold, etc.
• a second insulation layer 506 such as a dielectric layer in one embodiment may be disposed or layered on at least a portion of the second conducting layer 509.
• a third conducting layer 503 may provide the counter electrode 503. It may be disposed on at least a portion of the second insulation layer 506.
• a third insulation layer 507 may be disposed or layered on at least a portion of the third conducting layer 503. In this manner, the sensor 500 may be layered such that at least a portion of each of the conducting layers is separated by a respective insulation layer (for example, a dielectric layer).
• FIGS. 5A and 5B show the layers having different lengths. Some or all of the layers may have the same or different lengths and/or widths.
• some or all of the electrodes 501 , 502, 503 may be provided on the same side of the substrate 504 in the layered construction as described above, or alternatively, may be provided in a co-planar manner such that two or more electrodes may be positioned on the same plane (e.g., side-by side (e.g., parallel) or angled relative to each other) on the substrate 504.
• co-planar electrodes may include a suitable spacing there between and/or include dielectric material or insulation material disposed between the conducting layers/electrodes.
• one or more of the electrodes 501 , 502, 503 may be disposed on opposing sides of the substrate 504.
• contact pads may be on the same or different sides of the substrate.
• an electrode may be on a first side and its respective contact may be on a second side, e.g., a trace connecting the electrode and the contact may traverse through the substrate.
• the data processing unit 102 may be configured to perform sensor insertion detection and data quality analysis, information pertaining to which may also transmitted to the primary receiver unit 104 periodically at the predetermined time interval.
• the receiver unit 104 may be configured to perform, for example, skin temperature compensation/correction as well as calibration of the sensor data received from the data processing unit 102.
• analyte sensors may include an analyte-responsive enzyme to provide a sensing component or sensing layer.
• Some analytes such as oxygen, can be directly electrooxidized or electroreduced on a sensor, and more specifically at least on a working electrode of a sensor.
• Other analytes such as glucose and lactate, require the presence of at least one electron transfer agent and/or at least one catalyst to facilitate the electrooxidation or electroreduction of the analyte.
• Catalysts may also be used for those analytes, such as oxygen, that can be directly electrooxidized or electroreduced on the working electrode.
• each working electrode includes a sensing layer (see for example sensing layer 508 of FIG.
• a sensing layer is formed near or on only a small portion of at least a working electrode.
• the sensing layer is deposited on the conductive material of a working electrode.
• the sensing layer may extend beyond the conductive material of the working electrode.
• the sensing layer may also extend over other electrodes, e.g., over the counter electrode and/or reference electrode (or counter/reference is provided).
• the sensing layer may be integral with the material of an electrode.
• a sensing layer that is in direct contact with the working electrode may contain an electron transfer agent to transfer electrons directly or indirectly between the analyte and the working electrode, and/or a catalyst to facilitate a reaction of the analyte.
• a glucose, lactate, or oxygen electrode may be formed having a sensing layer which contains a catalyst, such as glucose oxidase, lactate oxidase, or laccase, respectively, and an electron transfer agent that facilitates the electrooxidation of the glucose, lactate, or oxygen, respectively.
• one or more of the working electrodes do not have a corresponding sensing layer, or have a sensing layer which does not contain one or more components (e.g., an electron transfer agent and/or catalyst) needed to electrolyze the analyte.
• the signal at this working electrode corresponds to background signal which may be removed from the analyte signal obtained from one or more other working electrodes that are associated with fully-functional sensing layers by, for example, subtracting the signal.
• the sensing layer includes one or more electron transfer agents.
• Electron transfer agents that may be employed are electroreducible and electrooxidizable ions or molecules having redox potentials that are a few hundred millivolts above or below the redox potential of the standard calomel electrode (SCE).
• the electron transfer agent may be organic, organometallic, or inorganic. Examples of organic redox species are quinones and species that in their oxidized state have quinoid structures, such as Nile blue and indophenol. Examples of organometallic redox species are metallocenes such as ferrocene. Examples of inorganic redox species are hexacyanoferrate (III), ruthenium hexamine etc.
• electron transfer agents have structures or charges which prevent or substantially reduce the diffusional loss of the electron transfer agent during the period of time that the sample is being analyzed.
• electron transfer agents include but are not limited to a redox species, e.g., bound to a polymer which can in turn be disposed on or near the working electrode.
• the bond between the redox species and the polymer may be covalent, coordinative, or ionic.
• the redox species is a transition metal compound or complex, e.g., osmium, ruthenium, iron, and cobalt compounds or complexes. It will be recognized that many redox species described for use with a polymeric component may also be used, without a polymeric component.
• polymeric electron transfer agent contains a redox species covalently bound in a polymeric composition.
• An example of this type of mediator is poly(vinylferrocene).
• Another type of electron transfer agent contains an ionically- bound redox species.
• This type of mediator may include a charged polymer coupled to an oppositely charged redox species.
• Examples of this type of mediator include a negatively charged polymer coupled to a positively charged redox species such as an osmium or ruthenium polypyridyl cation.
• an ionically-bound mediator is a positively charged polymer such as quaternized poly(4-vinyl pyridine) or poly(l -vinyl imidazole) coupled to a negatively charged redox species such as ferricyanide or ferrocyanide.
• electron transfer agents include a redox species coordinatively bound to a polymer.
• the mediator may be formed by coordination of an osmium or cobalt 2,2'-bipyridyl complex to poly(l -vinyl imidazole) or poly(4-vinyl pyridine).
• Suitable electron transfer agents are osmium transition metal complexes with one or more ligands, each ligand having a nitrogen-containing heterocycle such as 2,2'-bipyridine, 1 , 10-phenanthroline, 1 -methyl, 2-pyridyl biimidazole, or derivatives thereof.
• the electron transfer agents may also have one or more ligands covalently bound in a polymer, each ligand having at least one nitrogen-containing heterocycle, such as pyridine, imidazole, or derivatives thereof.
• the electron transfer agents may also have one or more ligands covalently bound in a polymer, each ligand having at least one nitrogen-containing heterocycle, such as pyridine, imidazole, or derivatives thereof.
• an electron transfer agent includes (a) a polymer or copolymer having pyridine or imidazole functional groups and (b) osmium cations complexed with two ligands, each ligand containing 2,2'-bipyridine, 1 , 10- phenanthroline, or derivatives thereof, the two ligands not necessarily being the same.
• Some derivatives of 2,2'-bipyridine for complexation with the osmium cation include but are not limited to 4,4'-dimethyl-2,2'-bipyridine and mono-, di-, and polyalkoxy- 2,2'-bipyridines, such as 4,4'-dimethoxy-2,2'-bipyridine.
• Derivatives of 1 ,10- phenanthroline for complexation with the osmium cation include but are not limited to 4,7-dimethyl- 1 , 10-phenanthroline and mono, di-, and polyalkoxy-1,10- phenanthrolines, such as 4,7-dimethoxy- 1 , 10-phenanthroline.
• Polymers for complexation with the osmium cation include but are not limited to polymers and copolymers of po Iy(I -vinyl imidazole) (referred to as "PVI”) and poly(4-vinyl pyridine) (referred to as "PVP").
• Suitable copolymer substituents of poly(l -vinyl imidazole) include acrylonitrile, acrylamide, and substituted or quaternized N-vinyl imidazole, e.g., electron transfer agents with osmium complexed to a polymer or copolymer of po Iy(I -vinyl imidazole).
• Embodiments may employ electron transfer agents having a redox potential ranging from about -200 mV to about +200 mV versus the standard calomel electrode (SCE).
• the sensing layer may also include a catalyst which is capable of catalyzing a reaction of the analyte.
• the catalyst may also, in some embodiments, act as an electron transfer agent.
• One example of a suitable catalyst is an enzyme which catalyzes a reaction of the analyte.
• a catalyst such as a glucose oxidase, glucose dehydrogenase (e.g., pyrroloquinoline quinone (PQQ) dependent glucose dehydrogenase, flavine adenine dinucleotide (FAD) dependent glucose dehydrogenase, or nicotinamide adenine dinucleotide (NAD) dependent glucose dehydrogenase), may be used when the analyte of interest is glucose.
• PQQ pyrroloquinoline quinone
• FAD flavine adenine dinucleotide
• NAD nicotinamide adenine dinucleotide dependent glucose dehydrogenase
• a lactate oxidase or lactate dehydrogenase may be used when the analyte of interest is lactate.
• Laccase 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.
• a catalyst may be attached to a polymer, cross linking the catalyst with another electron transfer agent (which, as described above, may be polymeric.
• a second catalyst may also be used in certain embodiments. This second catalyst may be used to catalyze a reaction of a product compound resulting from the catalyzed reaction of the analyte. The second catalyst may operate with an electron transfer agent to electrolyze the product compound to generate a signal at the working electrode.
• a second catalyst may be provided in an interferent- eliminating layer to catalyze reactions that remove interferents.
• Certain embodiments include a Wired EnzymeTM sensing layer that works at a gentle oxidizing potential, e.g., a potential of about +40 mV.
• This sensing layer uses an osmium (Os) -based mediator designed for low potential operation and is stably anchored in a polymeric layer.
• the sensing element is redox active component that includes (1) Osmium-based mediator molecules attached by stable (bidente) ligands anchored to a polymeric backbone, and
• a mass transport limiting layer (not shown), e.g., an analyte flux modulating layer, may be included with the sensor to act as a diffusion-limiting barrier to reduce the rate of mass transport of the analyte, for example, glucose or lactate, into the region around the working electrodes.
• the mass transport limiting layers are useful in limiting the flux of an analyte to a working electrode in an electrochemical sensor so that the sensor is linearly responsive over a large range of analyte concentrations and is easily calibrated.
• Mass transport limiting layers may include polymers and may be biocompatible.
• a mass transport limiting layer may serve many functions, e.g., functionalities of a biocompatible layer and/or interferent-eliminating layer may be provided by the mass transport limiting layer.
• a mass transport limiting layer is a membrane composed of crosslinked polymers containing heterocyclic nitrogen groups, such as polymers of polyvinylpyridine and polyvinylimidazole.
• Embodiments also include membranes that are made of a polyurethane, or polyether urethane, or chemically related material, or membranes that are made of silicone, and the like.
• a membrane is formed by crosslinking in situ a polymer, modified with a zwitterionic moiety, a non-pyridine copolymer component, and optionally another moiety that is either hydrophilic or hydrophobic, and/or has other desirable properties, in an alcohol-buffer solution.
• the modified polymer may be made from a precursor polymer containing heterocyclic nitrogen groups.
• hydrophilic or hydrophobic modifiers may be used to "fine-tune" the permeability of the resulting membrane to an 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.
• a membrane may be formed in situ by applying an alcohol-buffer solution of a crosslmker and a modified polymer over an enzyme-containing sensing layer and allowing the solution to cure for about one to two days or other appropriate time period.
• the crosslinker-polymer solution may be applied to the sensing layer by placing a droplet or droplets of the solution on the sensor, by dipping the sensor into the solution, or the like.
• the thickness of the membrane is controlled by the concentration of the solution, by the number of droplets of the solution applied, by the number of times the sensor is dipped in the solution, or by any combination of these factors.
• a membrane applied in this manner may have any combination of the following functions: (1) mass transport limitation, i.e., reduction of the flux of analyte that can reach the sensing layer, (2) biocompatibility enhancement, or (3) interferent reduction.
• the electrochemical sensors may employ any suitable measurement technique. For example, may detect current or may employ potentiometry. Technique may include, but are not limited to amperometry, coulometry, voltammetry. In some embodiments, sensing systems may be optical, colorimetric, and the like.
• the sensing system detects hydrogen peroxide to infer glucose levels.
• a hydrogen peroxide-detecting sensor may be constructed in which a sensing layer includes enzyme such as glucose oxides, glucose dehydrogensae, or the like, and is positioned proximate to the working electrode.
• the sending layer may be covered by a membrane that is selectively permeable to glucose. Once the glucose passes through the membrane, it is oxidized by the enzyme and reduced glucose oxidase can then be oxidized by reacting with molecular oxygen to produce hydrogen peroxide.
• Certain embodiments include a hydrogen peroxide-detecting sensor constructed from a sensing layer prepared by crosslinking two components together, for example: (1) a redox compound such as a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials of about +200 mV vs. SCE, and (2) periodate oxidized horseradish peroxidase (HRP).
• a redox compound such as a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials of about +200 mV vs. SCE
• HRP horseradish peroxidase
• a potentiometric sensor can be constructed as follows.
• a glucose-sensing layer is constructed by crosslinking together (1) a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials from about - 200 mV to +200 mV vs. SCE, and (2) glucose oxidase.
• This sensor can then be used in a potentiometric mode, by exposing the sensor to a glucose containing solution, under conditions of zero current flow, and allowing the ratio of reduced/oxidized Os to reach an equilibrium value.
• the reduced/oxidized Os ratio varies in a reproducible way with the glucose concentration, and will cause the electrode's potential to vary in a similar way.
• a sensor may also include an active agent such as an anticlotting and/or antiglycolytic agent(s) disposed on at least a portion a sensor that is positioned in a user.
• An anticlotting agent may reduce or eliminate the clotting of blood or other body fluid around the sensor, particularly after insertion of the sensor. Blood clots may foul the sensor or irreproducibly reduce the amount of analyte which diffuses into the sensor.
• useful anticlotting agents include heparin and tissue plasminogen activator (TPA), as well as other known anticlotting agents.
• Embodiments may include an antiglycolytic agent or precursor thereof. Examples of antiglyco lytic agents are glyceraldehyde, fluoride ion, and mannose.
• the term "antiglycolytic” is used broadly herein to include any substance that at least retards glucose consumption of living cells.
• Sensors described herein may be configured to require no system calibration or no user calibration.
• a sensor may be factory calibrated and need not require further calibrating.
• calibration may be required, but may be done without user intervention, i.e., may be automatic.
• the calibration may be according to a predetermined schedule or may be dynamic, i.e., the time for which may be determined by the system on a real-time basis according to various factors, such as but not limited to glucose concentration and/or temperature and/or rate of change of glucose, etc.
• Calibration may be accomplished using an in vitro test strip or other calibrator, e.g., a small sample test strip such as a test strip that requires less than about 1 microliter of sample (for example FreeStyle ® blood glucose monitoring test strips from Abbott Diabetes Care Inc.). For example, test strips that require less than about 1 nano liter of sample may be used.
• a sensor may be calibrated using only one sample of body fluid per calibration event. For example, a user need only lance a body part one time to obtain a sample for a calibration event (e.g., for a test strip), or may lance more than one time within a short period of time if an insufficient volume of sample is obtained firstly.
• Embodiments include obtaining and using multiple samples of body fluid for a given calibration event, where glucose values of each sample are substantially similar. Data obtained from a given calibration event may be used independently to calibrate or combined with data obtained from previous calibration events, e.g., averaged including weighted averaged, etc., to calibrate. In certain embodiments, a system need only be calibrated once by a user, where recalibration of the system is not required.
• An analyte system may include an optional alarm system that, e.g., based on information from a processor, warns the patient of a potentially detrimental condition of the analyte.
• an alarm system may warn a user of conditions such as hypoglycemia and/or hyperglycemia and/or impending hypoglycemia, and/or impending hyperglycemia.
• An alarm system may be triggered when analyte levels reach or exceed a threshold value.
• An alarm system may also, or alternatively, be activated when the rate of change, or acceleration of the rate of change, in analyte level increase or decrease approaches, reaches or exceeds a threshold rate or acceleration.
• an alarm system may be activated if the rate of change in glucose concentration exceeds a threshold value which might indicate that a hyperglycemic or hypoglycemic condition is likely to occur.
• a system may also include system alarms that notify a user of system information such as battery condition, calibration, sensor dislodgment, sensor malfunction, etc.
• Alarms may be, for example, auditory and/or visual.
• Other sensory-stimulating alarm systems may be used including alarm systems which heat, cool, vibrate, or produce a mild electrical shock when activated.
• the subject disclosure also includes sensors used in sensor-based drug delivery systems.
• the system may provide a drug to counteract the high or low level of the analyte in response to the signals from one or more sensors. Alternatively, the system may monitor the drug concentration to ensure that the drug remains within a desired therapeutic range.
• the drug delivery system may include one or more (e.g., two or more) sensors, a processing unit such as a transmitter, a receiver/display unit, and a drug administration system. In some cases, some or all components may be integrated in a single unit.
• the sensor-based drug delivery system may use data from the one or more sensors to provide necessary input for a control algorithm/mechanism to adjust the administration of drugs, e.g., automatically or semi-automatically.
• a glucose sensor may be used to control and adjust the administration of insulin from an external or implanted insulin pump.
• the sensitivity associated with the analyte sensor may be attenuated during the first 24 hours or so following the sensor insertion due to, for example, tissue trauma, and the like, potentially resulting in ESA condition for the analyte sensor.
• analyte sensor calibration management is provided to effectively detect the occurrence of the sensor ESA condition, properly categorize it and thereafter, manage the ESA condition such that potentially false readings from the sensor are minimized while the time period by which the reporting of the monitored analyte level from the sensor is initiated as close to the initial sensor insertion as possible.
• the analyte sensor calibration management routine may be configured to detect the presence of ESA condition, confirm the detected ESA event, and to manage calibration during the confirmed ESA event to ensure optimal calibration sensitivity estimate.
• the analyte sensor calibration management algorithm includes three parts" (1) ESA detection, (2) ESA categorization, and (3) ESA management. Each aspect or part of the management algorithm is discussed in detail below.
• the ESA detection component of the calibration management algorithm includes detection of the sensor signal (for example, the raw current signal from the analyte sensor) and evaluating it for characteristics of ESA condition. If ESA condition is detected based on this evaluation, a calibration of the analyte sensor is requested (for example, by prompting the user to perform a f ⁇ ngerstick measurement and enter the resulting reference blood glucose measurement value) to obtain a sensitivity used to confirm the ESA event.
• the ESA categorization aspect of the sensor calibration management routine in one aspect of the present disclosure includes rating the severity of the possible attenuation in the analyte sensor signal based on the sensitivities from the calibration measurements.
• the ESA categorization routine may classify the sensor signal characteristics into one of three categories: (a) No ESA (0), (b) Possible ESA (1), or (b) Likely ESA (2), based upon which, the ESA management component of the calibration management routine, in one aspect, performs additional processing to, for example, output the resulting monitored analyte level (for example, on the display of the receiver unit 104/106 (FIG. 1), or request additional reference blood glucose measurements within a given time period, to verify that the ESA condition is no longer present or insignificant.
• the ESA management component of the calibration management routine performs additional processing to, for example, output the resulting monitored analyte level (for example, on the display of the receiver unit 104/106 (FIG. 1), or request additional reference blood glucose measurements
• the ESA management routine of the calibration management algorithm may be configured to either update the calibration sensitivity and report or display the monitored analyte level from the sensor, update the calibration sensitivity and temporarily report the monitored analyte level, or suspend reporting of the monitored analyte level, based, at least in part, on the ESA categorization routine.
• an effective sensor calibration management approach that optimizes the analyte monitoring system accuracy and improves user experience, based on, for example, maximizing data yield (reporting the monitored glucose level as early as possible from the initial insertion), while minimizing the number of necessary calibration attempts (for example, the need to perform in vitro blood glucose testing).
• the ESA detection routine of the calibration management algorithm may be configured to detect possible ESA events by evaluating various signal characteristics, including sensor output, temperature, and/or elapsed time from sensor insertion.
• the ESA detection routine in one aspect evaluates the sensor signal for characteristics similar to those present or associated with ESA events, including, for example a depression or attenuation in the sensor signal during the first 24 hours.
• the threshold for the ESA detection routine may vary according to apriori knowledge of how the probability of the ESA event may be correlated to other measurable quantities, and/or according to real-time revision of the likelihood of the ESA event itself.
• An example of apriori knowledge may include the correlation of the probability of the ESA condition to elapsed time since the start of sensor life (i.e., sensor insertion).
• the ESA detection routine determines that there is a high probability that the sensor output is exhibiting ESA condition characteristics
• another calibration measurement i.e., fingerstick test
• the calibration request timing and the sensor signal reporting following the ESA condition detection may vary depending on the certainty or the likelihood of the ESA condition presence based on the ESA detection routine.
• the ESA detection routine determines that the probability of ESA condition is high, then calibration may be requested immediately (for example, by prompting the user to perform another fingerstick test) and provide the reference blood glucose measurement value obtained, and the sensor data representing the monitored analyte level are not reported to the user, but rather, withheld (for example, by disabling, suspending or deactivating the display in the receiver unit 104/106) until a calibration measurement can be performed to confirm the presence of ESA condition.
• the ESA detection routine determines that the likelihood of the presence of ESA condition is less certain, sensor data corresponding to the monitored analyte level may be reported or displayed to the user on a conditional basis, and additional calibrations may be requested at a later scheduled time if the attenuated signal characteristics (potentially indicating a likelihood of ESA condition) persist for a predetermined time period.
• the ESA categorization routine of the analyte sensor calibration management algorithm in one aspect, may be configured to categorize the sensor signal characteristics into three levels that are based on the confidence in the existence of ESA condition for the sensor.
• the routine may be configured to assess the sensor signal by looking at magnitude of the raw sensor signal (Sr), as well as the sensitivity of the sensor signal obtained from a reference glucose measurement, for which both magnitude (Si) and variation (dSi) from previous reference measurements are considered. Thresholds for each signal measurement (Sr, Si and dSi), assigned for each of the three algorithm categorization levels (0, 1 or 2), may be checked to assign the sensitivity to one of the three ESA categories.
• the three categories indicate the confidence level or the likelihood that ESA condition is present for the analyte sensor. For example, No ESA (level 0) indicates that there is no likelihood that ESA condition is present for the sensor. Possible ESA (level 1) indicates that there may be a possibility of ESA condition present for the sensor at this calibration event. Further, Likely ESA (level 2) indicates that it is likely there is ESA condition present for the sensor at the current calibration event. The checks for these measurements are performed at each calibration measurement, for example, when the user performs a fingerstick test to provide the reference blood glucose measurement, resulting in the appropriate categorization for each calibration event.
• the thresholds for the ESA categorization routine may vary over time.
• the thresholds may also vary based on the outcome of previous calibration measurements for any given sensor, since the probability that a given calibration will result in a detection of ESA increases when a signal perturbation has been previously observed for the sensor.
• the ESA management routine of the sensor calibration management algorithm in one aspect of the present disclosure has three outcomes that are based on the level of confidence in the presence of ESA condition for the sensor. For calibrations that are categorized as having No ESA (level 0), it is not likely that an ESA event will result in inaccurate results, and therefore, the sensor data corresponding to the monitored analyte level are determined and reported based on the sensitivity obtained from the calibration event.
• the sensitivity estimate may likely be valid for a limited time period, and therefore, the sensor data corresponding to the monitored analyte level may be determined and reported to the user based on the sensitivity obtained from the calibration event on a probationary basis (for a predetermined time period such as, for example, two hours or any other suitable probationary time period), after which the user may be prompted to perform another calibration to confirm the continued validity of the sensitivity obtained from calibration.
• a probationary basis for a predetermined time period such as, for example, two hours or any other suitable probationary time period
• analyte sensor calibration management which effectively processes the analyte sensor signals to maximize the accurate reporting of the monitored analyte level while minimizing the potential for providing false or erroneous readings from the sensor during the occurrence of signal attenuation events.
• routines and algorithms described herein may be incorporated in the receiver unit 104/106, the transmitter unit 102, or the data processing terminal/infusion section 105 of the analyte monitoring system 100 (FIG. 1). More specifically, in accordance with the embodiments of the present disclosure, there may be provided one or more signal detectors configured to perform some, shared or all of the routines described herein to management sensor calibration for the ESA detection, the ESA categorization, and the ESA management, by for example, one or more processors, state machines and the like which may include integrated circuits, application specific integrated circuits (ASIC), and/or combination of hardware and software components including memory devices such as random access memory (RAM), read only memory (ROM), solid state drives, and the like.
• ASIC application specific integrated circuits
• RAM random access memory
• ROM read only memory
• solid state drives solid state drives
• a plurality of signal detectors may be used to implement the calibration management routine described herein.
• a first signal detector may be configured for detection of ESA state based on blood glucose measurements or other reference information and the analyte sensor data from the sensor analyte monitoring system.
• the outcome of a first signal detector may be configured to determine whether the monitored sensor signal from the analyte monitoring system is in ESA condition.
• a second signal detector may be configured to monitor the analyte monitoring system sampled data (for example, one minute data, or any suitable sampling rate).
• a second signal detector may be configured to instruct the analyte monitoring system to prompt the user to enter an immediate or scheduled blood glucose measurement (for example, based on a fingerstick test using a blood glucose meter) confirm whether an ESA condition exists, and to be used in conjunction with the first signal detector - i.e., the detection of ESA state of the analyte monitoring system based on the reference blood glucose measurements.
• the first and second signal detectors are configured to generate one of a plurality, e.g., three, ESA levels - level 0: no ESA, level 1 : possible ESA, and level 2: likely ESA.
• the level 2 condition associated with possible ESA state of the sensor may be characterized as no significant signal attenuation but based on the detected or monitored conditions associated with the sensor, a verification of the potential ESA condition is desired or necessary within a predetermined period, such as, two hours (or any other suitable time period).
• the fingerstick test (or reference blood glucose measurement)-based ESA detector operates when a calibration attempt passes a data condition verification routine during the active ESA detection phase. More specifically, the ESA_FS detector starts its activity at the first baseline calibration (for example, at about one hour or less from the time of sensor insertion). It remains active during the initial phase of the sensor life (for example, approximately the first 24 hours from initial insertion) when the likelihood of ESA condition is greatest.
• the first signal detector takes the role of "ESA Categorization” module 620 (FIG. 6) during active ESA condition detection phase.
• first signal detector also takes the role of "ESA Detection” module 610.
• the ESA_FS detector uses two tests, one relative and one absolute, either of which can detect signal attenuation levels (ESA_FS level) based on any reference blood glucose measurement within the active ESA detection phase.
• the higher of the two levels may be chosen if they are not the same for the two tests.
• the relative test compares the value of the latest immediate sensitivity based on the latest fmgerstick blood glucose test, S,(k), to the values of the previous immediate sensitivity, S 1 Qi-I), and the most recent immediate sensitivity used to calculate the composite sensitivity, S 1 (M).
• the values S 1 Qz), S 1 Qi-I), and S 1 (Tn) are selected such that calibration post condition verifications pass at those instances (at time index k, k-1, and m).
• manual calibrations are subject to the tests performed by the ESA_FS detector, but the resulting immediate sensitivities may not be used as previous values.
• ESA_FS level 2 (likely ESA condition) if: S 1 QLyS 1 QL-I) ⁇ Kl 0 _ ReL ESA_FS[2] , OR S 1 QLyS 1 (TO) ⁇ Kl o _R eLES A_FS_Cal[2],
• K 10 _ Rel _ ESA _FS[2] is less than or equal to K io Rd ESA FS[I], and further,
• Ki 0 Rei ESA_FS_Cai[2] is less than or equal to Ki 0 _ Rel _ESA_FS_GI1[I], and further, where each of these parameters may be predetermined values (for example, set at 0.5 or 0.75 or other suitable value) programmed or programmable in the receiver unit 104/106 (FIG. 1) of the analyte monitoring system, for example.
• the relative test of ESA FS generates a level 0 output indicative of absence of ESA condition.
• the absolute test compares the sensitivity level S t (k) to sensitivity thresholds scaled to the analyte sensor nominal sensitivity S nom .
• S 1 (Ii) may be chosen such that it passes calibration post condition verifications.
• ESA_FS levels are assigned as follows:
• ESA_FS level 2 (likely ESA condition) if: S ⁇ k)ZS 1101n ⁇ K 1111n Abs ESA FS [ 2 ]
• ESA_FS level 1 (possibl ESA condition) if NOT ESA FS level 2 AND:
• ⁇ K 111111 A bs ESA FS[2] is less tha nequal to K 1111n A bs ESA FS[i], and further, each of these two parameters may be predetermines or programmed.
• the absolute test of ESA FS generates a level 0 output (indicating no detected ESA condition).
• the threshold values for the relative and absolute tests above may be valid when the likelihood of ESA condition is the greatest.
• the likelihood of ESA may be assumed to be correlated to the elapsed time since sensor insertion, and that different likelihoods allow for different tradeoffs between maximizing ESA detection and minimizing the number of calibration requests.
• the second signal detector in the analyte monitoring system is based on inferring ESA condition from the analyte sensor signal characteristics.
• ESA signal attenuation
• the second signal detector may be configured to include the functions of the "ESA Detection" module 610 (FIG. 6), and is not used solely to categorize the detected ESA condition for the "ESA Management” module 630 of the overall system.
• the second signal detector produces a nonzero output, a reference blood glucose measurement is expected in a manner determined by the "ESA Management" module 630 of the overall system.
• G CAL a predefined number of the most recent unfiltered glucose samples from the analyte sensor, G CAL , are averaged to derive at the glucose value GESA CGM-
• the detector reports one of three possible ESA levels based on the glucose value GESA CGM-
• ESA level 2 (likely ESA condition) if: GESA CGM ⁇ G min E SA_CGM[2]
• ESA level 1 (possible ESA condition) if NOT ESA_FS level 2 AND: GESA CGM ⁇ Gm 1n ESA CGM[I]
• G min ESA_CGM[2] is less than or equal to G 1111n _ESA_CGM[I], and further, correspond to predetermined values or parameters programmed into the system.
• the absolute test of ESA generates a level 0 output indicating no detected ESA condition. Furthermore, if all of the most recent predefined number of unfiltered glucose sample GCAL is not available, the second signal detector may be configured to report a zero level.
• ESA Management may be influenced by the sensitivity and specificity of each detector, the history of past or prior calibration events and reference blood glucose measurement timing, the scheduled calibration events in the near future, and other aspects including usability.
• the second signal detector may be configured to begin to operate after the second baseline calibration (that is, the second scheduled calibration time period for the analyte sensor) which may be a floating calibration event (measured from when the no ESA condition is determined) scheduled following the first absolute calibration (measured from the initial sensor insertion event) and thereby reporting measured glucose levels to the user.
• the display or output of the measured glucose levels may be suspended at a predetermined time associated with the earliest allowable termination of the signal detectors in the system.
• the output from the second signal detector may be ignored when either less than a predefined idle time period has elapsed after a successful baseline calibration where asynchronous stability request is not allowed (for example, 30 minutes) after any calibration attempt, or when less than a predefined idle time period has elapsed prior to the next scheduled baseline calibration where asynchronous stability request is not allowed (for example, 30 minutes) before any scheduled calibration attempt.
• the first signal detector is used to determine whether ESA condition is present or absent. In one embodiment, it is assumed that ESA condition is absent at the sensor start - that is, when the sensor is initially inserted.
• the transition, behavior, and retention of the states in one aspect are described below. For example, in one aspect, transition into a determination that ESA condition is present occurs when the latest ESA FS level is determined to be greater than the largest allowable output level from the first signal detector of prior measurements that is considered as an indication of being free from early signal attenuation.
• only level 2 may be configured to trigger the transition to a state where it is determined that ESA condition is present.
• the receiver unit 104/106 (FIG. 1) may be configured to disable the output or display of the measured or detected glucose level.
• the receiver unit 104/106 may be configured to maintain the disabled (or suspended or deactivated) output/display for a predefined idle time period after the presence of ESA condition has been confirmed by the reference blood glucose measurement before the user is prompted for another confirmation (for example, by requesting another fmgerstick test) before transitioning to the state with confirmed no ESA condition.
• receiver unit 104/106 may be configured to not request a stability calibration verification while sensor is in ESA condition. However, any user-motivated or self- initiated fmgerstick blood glucose measurement may be used, if confirmed, to transition into a state where ESA condition is absent.
• the receiver unit 104/106 (FIG. 1) of the analyte monitoring system may be configured to request a reference blood glucose measurement to confirm that the absence of ESA condition is complete and/or to initiate calibration.
• transition into a state associated with absence of ESA condition occurs when a new fingerstick blood glucose measurement shows an ESA FS level (for example, the output of the first signal detector discussed above) that is less than or equal to the largest allowable output level from the first signal detector of prior measurements that is considered as an indication of being free from early signal attenuation.
• ESA FS level for example, the output of the first signal detector discussed above
• the sensor signals may be further processed to determine stability and possible errors. For example, in one aspect, when a level 2 output (i.e., likely ESA condition) from the second signal detector occurs for the first time, an immediate request for a stability calibration may be generated. After the first occurrence of level 2 output from the second signal detector, the analyte sensor signals are checked at the time intervals (for example, approximately 1 to 2 hours, or other suitable time interval) since the last reference blood glucose measurement with stability verification routine before another measurement is requested, after the most recent successful calibration.
• time intervals for example, approximately 1 to 2 hours, or other suitable time interval
• a nonzero level i.e., a level 1 or level 2 - possible or likely ESA condition
• a stability calibration request if a previous ESA_FS level is greater than 0, a reference blood glucose measurement is requested at a time interval since the last blood glucose measurement, and ESA_FS is determined using the new reference measurement.
• FIG. 6 is a flowchart illustrating an overall analyte sensor calibration management in accordance with one embodiment of the present disclosure.
• analyte sensor calibration management system in accordance with one aspect of the present disclosure includes an ESA detection module 610, and ESA categorization module 620, and an ESA management module.
• the ESA detection module 610 is configured to detect the occurrence of an early signal attenuation event during the initial time period following the analyte sensor insertion or wear, for example, the first 24 hour period measured from the initial sensor insertion.
• the ESA categorization module in one embodiment is configured to properly categorize the detected signal attenuation condition. Thereafter, depending upon the type of ESA condition detected - for example, no ESA condition detection, likely ESA condition detection, or possible ESA condition detection, the ESA management module 630 is configured to initiate one or more processes to confirm the detected and categorized signal attenuation condition. And further, to perform additional processing to effectively manage the calibration algorithm associated with the analyte sensor operation such that maximum reportable data yield may be attained, providing improved usability of the analyte sensor for continuously or intermittently monitoring and outputting monitored analyte level such as the fluctuation in the glucose level of a patient or a user.
• FIG. 7 is a flowchart illustrating early signal attenuation (ESA) detection routine of FIG. 6 in accordance with one aspect of the present disclosure.
• ESA detection routine executed by the ESA detection module 610 (FIG. 6), for example, is described. More specifically, for each monitored signal from the analyte sensor (such as for each one minute data from the analyte sensor), a new timestep is initiated (701), and it is determined whether ESA detector should be or has started (702). If it is determined that the ESA detector has not or should not be started, then the routine waits for the next time step (714) based on the next signal received from the sensor (for example, the subsequent one minute signal received from the analyte sensor). Referring to FIG.
• analyte sensor signal information as well as other relevant information is retrieved or obtained (707). That is, for example, the sensor raw current signal, the associated temperature information, sensor counter voltage data, for example, are obtained, in addition to other relevant information such as, for example, the sensor code sensitivity, immediate sensitivity, time duration elapsed since the sensor insertion, and time elapsed since the prior sensor calibration event, for example.
• other relevant data related to the operation and characteristics of the analyte sensor may be obtained.
• the probability or ESA condition presence is determined (709), the result of which is compared to one or more threshold values to determine whether high ESA condition probability exists (710). If it is determined that high ESA condition probability exists, then reference blood glucose measurement data is requested with a nonzero grace period (711), and the ESA detection routine is suspended to await for the requested reference blood glucose measurement data. On the other hand, if it is determined that high ESA condition probability does not exist (710), then it is determined whether medium ESA condition probability exists (712). If it is determined that medium ESA condition probably does not exist, then the routine proceeds to wait for the next sensor data (714).
• a pending reference blood glucose measurement timer is set to activate at a predetermined relative time in the future, unless a successful calibration event is detected prior to the expiration of the activated timer (713).
• the ESA detection module 610 may be configured to detect attenuation in analyte sensor signal during the initial time period from the sensor insertion.
• FIG. 8 is a flowchart illustrating early signal attenuation (ESA) categorization routine of FIG. 6 in accordance with one aspect of the present disclosure.
• ESA early signal attenuation
• the detected attenuation is categorized by, for example, the ESA categorization module (620). More specifically, referring now to FIG. 8, for each new timestep associated with the detection of the one minute sensor signal from the analyte sensor, for example (810), it is determined whether ESA detector is active (820). If it is determined that the ESA detector is not active (or the ESA routine is not activated or initiated), then the ESA categorization routine terminates (821).
• analyte sensor related information may include, for example, sensor signal history, previous reference blood glucose measurement values, calibration time period, and the like.
• the detected signal attenuation is categorized into one of three categories - level 0, level 1 , and level 2, corresponding to no ESA condition, possible ESA condition, and likely ESA condition, respectively (850) and as discussed in detail above.
• the routine proceeds to the ESA management module (630) (FIG. 6) and also, repeats the same categorization procedure for the next received sensor signal. Referring back, as discussed, after performing ESA condition categorization
• FIG. 9 is a flowchart illustrating early signal attenuation (ESA) management routine of FIG. 6 in accordance with one aspect of the present disclosure. As shown, for each analyte sensor signal received or detected (901), it is first determined whether the ESA detector is active (902). If it is determined that the ESA detector is not active, then the ESA management routine terminates (903).
• ESA early signal attenuation
• the ESA detector determines whether a grace period of an existing reference blood glucose measurement request has expired (904). If it is determined that the grace period of the existing reference blood glucose measurement request has expired, then the display or reporting module associated with the output of the analyte sensor data is disabled, suspended, deactivated or otherwise blanked such that no real time glucose information is provided to the user (910). If it is determined however, that the grace period of the existing reference blood glucose measurement request has not expired, then the ESA categorization module output from the ESA categorization module (620) is retrieved (905).
• the ESA categorization result or output exists (906). If not, then the output or reporting of the real time glucose information proceeds and the user is provided with the glucose level data (914), and thereafter waits to receive the next analyte signal associated with the next timestep (918). On the other hand, if the ESA categorization result exists (906), then it is determined whether the ESA categorization is associated with the current analyte signal (associated with the current timestep, for example) (907). If it is not associated with the current analyte signal, then the routine proceeds to displaying or outputting the monitored analyte level to the user (914), and waits to receive the next analyte signal associated with the next timestep (918).
• the ESA condition categorization is associated with level 2 category indicating a likely ESA condition for the sensor. If it is determined that the ESA condition categorization is associated with level 2 category, then a timer (T_Confirm timer) is started (909) and the reporting or output of the glucose data is disabled (910). If it is determined however, that the ESA condition category is not associated with level 2, then it is determined whether the categorized ESA condition is level 1 (91 1).
• a request for a blood glucose measurement is scheduled for a predetermined time period (T CaI U) with a nonzero grace period (912), and the real time glucose information is displayed or output to the user (914).
• the routine waits to receive the next analyte sensor signal (918).
• T_Conf ⁇ rm timer was started and the timer expired (915). If it has not expired, the routine waits to receive the next analyte signal (918). If, however, it is determined that the timer (T_Confirm) has lapsed (915), then it is determined whether the characteristics of the sensor is suitable, for example, for calibration (916). If it is determined that the sensor condition is not suitable (916), then the routine waits to receive the next analyte sensor signal (918). On the other hand, if it is determined that the sensor condition is stable (916), then a reference blood glucose measurement is requested with a zero grace period (917).
• method, apparatus and system for providing effective analyte sensor calibration management is described that monitors the early attenuation of sensor signals and processes the monitored signals to maximize the sensor data yield by providing as much of the useful and accurate monitored glucose level information to the user.
• Hyperglycemic events at 240 mg/dL were detected by threshold or projected alarm 97.2% of the time.
• the threshold or projected alarm false alarm rate was 25.2% at 70 mg/dL and 21.2% at 240 mg/dL.
• the analyte sensor calibration management minimizes the presentation of erroneous analyte sensor results due to ESA conditions, while maximizing reportable analyte sensor data for sensors that do not exhibit the ESA signal characteristic.
• the calibration management algorithm applies to any subcutaneously positioned analyte sensor which may exhibit ESA signal characteristics, and enables the management of calibration during periods when the analyte sensor sensitivity may deviate from the actual sensor sensitivity.
• a method in one aspect includes monitoring for a signal level below a predetermined threshold associated with analyte level from an analyte sensor during a predefined time period, and reporting analyte level associated with the analyte sensor when the signal level monitored is not detected during the predefined time period.
• the predefined time period may include less than approximately one hour.
• the method may include receiving a blood glucose measurement, and calibrating the analyte sensor based on the received blood glucose measurement.
• the predetermined threshold may be associated with one or more of an impending hypoglycemic state, or a predefined signal attenuation level.
• reporting the analyte level may include one or more of storing the analyte level, confirming the analyte level, or outputting the analyte level.
• the various processes described above including the processes performed by the data processing unit 102, receiver unit 104/106 or the data processing terminal/infusion section 105 (FIG. 1) in the software application execution environment in the analyte monitoring system 100 including the processes and routines described in conjunction with FIGS. 6-9, may be embodied as computer programs developed using an object oriented language that allows the modeling of complex systems with modular objects to create abstractions that are representative of real world, physical objects and their interrelationships.
• the software required to carry out the inventive process which may be stored in the memory or storage device (not shown) of the data processing unit 102, receiver unit 104/106 or the data processing terminal/infusion section 105, may be developed by a person of ordinary skill in the art and may include one or more computer program products.
• One embodiment of the present disclosure may include positioning an analyte sensor in fluid contact with an analyte, detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
• the signal from the analyte sensor may be associated with a monitored analyte level.
• the detected attenuation in the signal from the analyte sensor may be associated with an early signal attenuation condition.
• the plurality of signal attenuation conditions may include a reportable signal condition, a conditional reportable signal condition, and an unreportable signal condition.
• Another aspect may include outputting data associated with the monitored analyte level based on the detected analyte sensor signal when the detected analyte sensor signal attenuation includes a reportable signal condition or a conditional reportable signal condition.
• Outputting data associated with the monitored analyte level may include outputting data for a preset time period when the detected analyte sensor signal attenuation includes the conditional reportable signal condition.
• the preset time period may not exceed approximately two hours.
• One aspect may include requesting a reference blood glucose measurement during the preset time period.
• Another aspect may include calibrating the analyte sensor signal based at least in part on the reference blood glucose measurement received during the preset time period.
• Yet another aspect may include disabling outputting of the data associated with the monitored analyte level after the preset time period has elapsed.
• performing signal processing may include requesting a reference data, and determining a sensitivity value associated with the analyte sensor based on the reference data.
• the reference data may include an in vitro blood glucose measurement data.
• One aspect may include calibrating the analyte sensor based at least in part on the determined sensitivity value.
• a further embodiment of the present disclosure includes monitoring for a signal level below a predetermined threshold associated with analyte level from an analyte sensor during a predefined time period, and reporting analyte level associated with the analyte sensor when the signal level monitored is not detected during the predefined time period.
• the predefined time period may be less than approximately one hour.
• Another aspect may include receiving a blood glucose measurement, and calibrating the analyte sensor based on the received blood glucose measurement.
• the predetermined threshold may be associated with one or more of an impending hypoglycemic state, or a predefined signal attenuation level.
• Reporting the analyte level may include one or more of storing the analyte level, confirming the analyte level, or outputting the analyte level.
• Yet still another aspect of the present disclosure includes inserting at least a portion of a glucose sensor beneath a skin surface of an individual, analyzing glucose- related signal from the sensor to determine sensor stability, and reporting glucose related information to the individual only when it is determined that the sensor is stable, wherein the glucose related information is not reported prior to determination that the sensor is stable.
• Sensor stability may be determined using reference data.
• Reference data may comprise sampling blood of the individual.
• Reference data may be obtained from a glucose test strip.
• One aspect may include analyzing the sensor signal to determine whether there exists a decrease in sensor signal.
• the analyte sensor may report the glucose related information in about one hour following the insertion.
• An apparatus in accordance with still another aspect may include a data communication interface, one or more processors operatively coupled to the data communication interface, and a memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to position an analyte sensor in fluid contact with an analyte, detect an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorize the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and perform signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
• the signal from the analyte sensor may be associated with a monitored analyte level.
• the detected attenuation in the signal from the analyte sensor may be associated with an early signal attenuation condition.
• the predetermined time period may not exceed approximately 24 hours.
• the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to categorize the detected analyte sensor signal attenuation based at least in part on a predetermined plurality of signal attenuation conditions.
• the plurality of signal attenuation conditions may include a reportable signal condition, a conditional reportable signal condition, and an unreportable signal condition.
• the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to output data associated with the monitored analyte level based on the detected analyte sensor signal when the detected analyte sensor signal attenuation includes a reportable signal condition or a conditional reportable signal condition.
• the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to output data for a preset time period when the detected analyte sensor signal attenuation includes the conditional reportable signal condition.
• the preset time period may not exceed approximately two hours.
• Reference data may include an in vitro blood glucose measurement data.
• the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to calibrate the analyte sensor based at least in part on the determined sensitivity value.

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