Various analyte sensor systems for controlling activation of analyte sensor electronics circuitry are provided. Related methods for controlling analyte sensor electronics circuitry are also provided. Various analyte sensor systems for monitoring an analyte in a host are also provided. Various circuits for controlling activation of an analyte sensor system are also provided. Analyte sensor systems utilizing a state machine having a plurality of states for collecting a plurality of digital counts and waking a controller responsive to a wake up signal are also provided. Related methods for such analyte sensor systems are also provided. Systems for controlling activation of analyte sensor electronics circuitry utilizing a magnetic sensor are further provided. One or more display device configured to display one or more analyte concentration values are also provided.

A system and method for personalized calibration for glucose sensing. In some embodiments, the method includes obtaining a plurality of first glucose measurements from a subject, at a plurality of first sampling times during a time interval, using a first glucose sensor; obtaining a plurality of second glucose measurements from the subject, at a plurality of second sampling times during the time interval, using a second glucose sensor; and estimating a first in-vivo calibration parameter for the first glucose sensor and the second glucose sensor, based on the first glucose measurements and the second glucose measurements, wherein a first in-vivo time-constant, relating blood glucose to an output of the first glucose sensor, is different from a second in-vivo time-constant, relating blood glucose to an output of the second glucose sensor.

A system and method for personalized calibration for glucose sensing. In some embodiments, the method includes obtaining a plurality of first glucose measurements from a subject, at a plurality of first sampling times during a time interval, using a first glucose sensor; obtaining a plurality of second glucose measurements from the subject, at a plurality of second sampling times during the time interval, using a second glucose sensor; and estimating a first in-vivo calibration parameter for the first glucose sensor and the second glucose sensor, based on the first glucose measurements and the second glucose measurements, wherein a first in-vivo time-constant, relating blood glucose to an output of the first glucose sensor, is different from a second in-vivo time-constant, relating blood glucose to an output of the second glucose sensor.

Continuous Glucose Monitoring (CGM) devices provide glucose concentration measurements in the subcutaneous tissue with limited accuracy and precision. Therefore, CGM readings cannot be incorporated in a straightforward manner in outcome metrics of clinical trials e.g. aimed to assess new glycaemic-regulation therapies. To define those outcome metrics, frequent Blood Glucose (BG) reference measurements are still needed, with consequent relevant difficulties in outpatient settings. Here we propose a “retrofitting” algorithm that produces a quasi continuous time BG profile by simultaneously exploiting the high accuracy of available BG references (possibly very sparsely collected) and the high temporal resolution of CGM data (usually noisy and affected by significant bias). The inputs of the algorithm are: a CGM time series; some reference BG measurements; a model of blood to interstitial glucose kinetics; and a model of the deterioration in time of sensor accuracy, together with (if available) a priori information (e.g. probabilistic distribution) on the parameters of the model. The algorithm first checks for the presence of possible artifacts or outliers on both CGM datastream and BG references, and then rescales the CGM time series by exploiting a retrospective calibration approach based on a regularized deconvolution method subject to the constraint of returning a profile laying within the confidence interval of the reference BG measurements. As output, the retrofitting algorithm produces an improved “retrofitted” quasi-continuous glucose concentration signal that is better (in terms of both accuracy and precision) than the CGM trace originally measured by the sensor. In clinical trials, the so-obtained retrofitted traces can be used to calculate solid outcome measures, avoiding the need of increasing the data collection burden at the patient level.

Continuous Glucose Monitoring (CGM) devices provide glucose concentration measurements in the subcutaneous tissue with limited accuracy and precision. Therefore, CGM readings cannot be incorporated in a straightforward manner in outcome metrics of clinical trials e.g. aimed to assess new glycaemic-regulation therapies. To define those outcome metrics, frequent Blood Glucose (BG) reference measurements are still needed, with consequent relevant difficulties in outpatient settings. Here we propose a “retrofitting” algorithm that produces a quasi continuous time BG profile by simultaneously exploiting the high accuracy of available BG references (possibly very sparsely collected) and the high temporal resolution of CGM data (usually noisy and affected by significant bias). The inputs of the algorithm are: a CGM time series; some reference BG measurements; a model of blood to interstitial glucose kinetics; and a model of the deterioration in time of sensor accuracy, together with (if available) a priori information (e.g. probabilistic distribution) on the parameters of the model. The algorithm first checks for the presence of possible artifacts or outliers on both CGM datastream and BG references, and then rescales the CGM time series by exploiting a retrospective calibration approach based on a regularized deconvolution method subject to the constraint of returning a profile laying within the confidence interval of the reference BG measurements. As output, the retrofitting algorithm produces an improved “retrofitted” quasi-continuous glucose concentration signal that is better (in terms of both accuracy and precision) than the CGM trace originally measured by the sensor. In clinical trials, the so-obtained retrofitted traces can be used to calculate solid outcome measures, avoiding the need of increasing the data collection burden at the patient level.

A process for calibrating a glucose sensor under sterile conditions includes providing separate, sterile, glucose-containing calibration fluids, each having a different glucose concentration, and in turn providing these fluids to a sensing zone containing a sensing probe of a glucose sensor. Each solution is typically, in turn, propelled into the sensing zone, thus flushing out used fluid already present in the sensing zone. The process provides rapid calibration of a glucose sensor in a sterile fashion and is therefore appropriate for point-of-use calibration.

A process for calibrating a glucose sensor under sterile conditions includes providing separate, sterile, glucose-containing calibration fluids, each having a different glucose concentration, and in turn providing these fluids to a sensing zone containing a sensing probe of a glucose sensor. Each solution is typically, in turn, propelled into the sensing zone, thus flushing out used fluid already present in the sensing zone. The process provides rapid calibration of a glucose sensor in a sterile fashion and is therefore appropriate for point-of-use calibration.

Systems and methods described provide dynamic and intelligent ways to change the required level of user interaction during use of a monitoring device. The systems and methods generally relate to real time switching between a first or initial mode of user interaction and a second or new mode of user interaction. In some cases, the switching will be automatic and transparent to the user, and in other cases user notification may occur. The mode switching generally affects the user’s interaction with the device, and not just internal processing. The mode switching may relate to calibration modes, data transmission modes, control modes, or the like.

Systems and methods described provide dynamic and intelligent ways to change the required level of user interaction during use of a monitoring device. The systems and methods generally relate to real time switching between a first or initial mode of user interaction and a second or new mode of user interaction. In some cases, the switching will be automatic and transparent to the user, and in other cases user notification may occur. The mode switching generally affects the user’s interaction with the device, and not just internal processing. The mode switching may relate to calibration modes, data transmission modes, control modes, or the like.

Disclosed is a method for initializing an analyte measurement system (1, 2, 3), the analyte measurement system (1, 2, 3) being designed for continuous in-vivo measurement of a body fluid analyte concentration. The method including the steps of: a) providing the analyte measurement system (1, 2, 3,) with a control device (3) and a separate skin-mountable patch device (1, 2), the patch device (1, 2) including a disposable unit (1) and an electronics unit (2), the disposable unit (1) including a transcutaneous analyte sensor (10) and machine-readable sensor identifier (121), the electronics unit (2) being configured to releasable couple for an application time period to the disposable unit (1); b) providing a number of stored initialization data sets in a remote database system (4), each stored initialization data set comprising initialization data for an analyte sensor batch; c) reading, via a reading device (31) of the control device (3), the sensor identifier from the disposable unit (1) into the control device (3) and transmitting the sensor identifier to the remote database system; d) determining a matching initialization data set, the matching initialization data set being a stored initialization data set that matches the sensor identifier; e) transmitting the matching initialization data set from the remote database system to the control device (3); f) transmitting the matching initialization data set to the electronics unit (2) and storing the matching initialization data set in a memory (21) of the electronics unit (2).