70 results about "Glucose Measurement" patented technology

A method may comprise (a) inserting an insulin delivery device subcutaneously into a body of a subject, which comprises an amperometric glucose sensor comprising an electrode layer comprising an indicating electrode and underlying a redox-catalytic layer comprising a redox mediator; (b) using said insulin delivery device to deliver an insulin formulation (e.g., comprising a phenol or cresol excipient) subcutaneously to said subject; and (c) using said amperometric glucose sensor to measure a subcutaneous glucose concentration, which comprises using said redox-catalytic layer to allow electron transfer from subcutaneous glucose to said indicating electrode sufficient to cause a response of said amperometric glucose sensor at an applied bias potential of no more than +250 millivolts, wherein (b) and (c) are performed at the same time for at least one hour, while maintaining a sensor sensitivity of at least 50% of an initial sensor sensitivity for up to one hour.

In an aspect, the present disclosure provides a method comprising: (a) positioning an insulin delivery device on a body of a subject via a single puncture site in said body of said subject; (b) using said insulin delivery device to deliver an insulin or insulin analog formulation to said subject via said single puncture site; and (c) using a sensor of said insulin delivery device to measure a glucose concentration in said body of said subject via said single puncture site, wherein (b) and (c) are performed at substantially the same time for a time period of at least 1 hour subsequent to said positioning in (a), while maintaining a sensitivity of said sensor of at least 50% of an initial sensitivity of said sensor.

Detection of anomalous computing environment behavior using glucose is described. An anomaly detection system receives glucose measurements and event records during a first time period. Missing events that are missing from the event records during the first time period are identified by processing the glucose measurements using an event engine simulator. An anomaly detection model is generated based on the missing events during the first time period. Subsequently, the anomaly detection system receives additional glucose measurements and additional event records during a second time period. Missing events that are missing from the additional event records during the second time period are identified by processing the additional glucose measurements using the event engine simulator. Anomalous behavior is detected if the identified missing events that are missing from the event records during the second time period are outside a predicted range of missing events of the anomaly detection model.

Glucose level measurements of a user are obtained over time, such as from a wearable glucose monitoring device being worn by the user. These glucose level measurements can be produced substantially continuously, such that the device may be configured to produce the glucose level measurements at regular or irregular intervals of time, responsive to establishing a communicative coupling with a different device, and so forth. These glucose level measurements are analyzed to detect deviations from past glucose measurements, such as glucose measurements received earlier in the day or glucose measurements received at corresponding times of one or more preceding days. Indications of detected deviations are provided to the user or communicated elsewhere, such as to a healthcare professional.

The present invention relates to a computer-implemented method for aiding in the guidance of diabetes drug therapy of an individual suffering from diabetes mellitus. The method is based on glucose data from said individual that are received at a processing unit, wherein said glucose data comprise at least three fasting glucose measurement values from said individual, and / or at least three matched pre-prandial glucose measurement values and postprandial glucose measurement values at the same meal from said individual. Further contemplated by the present invention is a device for aiding in the guidance of drug diabetes therapy of an individual suffering from diabetes, said device comprising a processing unit, and a computer program including computer-executable instructions, wherein said instructions, when executed by the processing unit, causes the processing unit to perform the computer-implemented method of the present invention.

This invention provides an improved method for electrochemical glucose measurement and an improved composition for glucose measurement. This invention also provides a composition for glucose measurement comprising a flavin compound. This invention also provides an electrode comprising a flavin compound and a sensor and a glucose fuel cell comprising such electrode. In addition, this invention provides a method for electrochemical glucose measurement and a method for electric power generation using a flavin compound. The flavin compound of the present invention is non-toxic or less toxic and it can be thus used for a means of self-contained continuous glucose measurement.

A method may comprise (a) inserting an insulin delivery device subcutaneously into a body of a subject, which comprises an amperometric glucose sensor comprising an electrode layer comprising an indicating electrode and underlying a redox-catalytic layer comprising a redox mediator; (b) using said insulin delivery device to deliver an insulin formulation (e.g., comprising a phenol or cresol excipient) subcutaneously to said subject; and (c) using said amperometric glucose sensor to measure a subcutaneous glucose concentration, which comprises using said redox-catalytic layer to allow electron transfer from subcutaneous glucose to said indicating electrode sufficient to cause a response of said amperometric glucose sensor at an applied bias potential of no more than +250 millivolts, wherein (b) and (c) are performed at the same time for at least one hour, while maintaining a sensor sensitivity of at least 50% of an initial sensor sensitivity for up to one hour.

A method of determining an insulin bolus to be administered by an insulin delivering device is disclosed. According to the inventive method, glucose measurement data corresponding to glucose level measurement signals detected by a continuous glucose sensor are received. An insulin bolus to be administered by the insulin delivering device is determined based on a formula having expressions indicative of, for example, glucose level derived from the glucose measurement data, carbohydrate-to-insulin ratio (CIR) and an insulin sensitivity factor (ISF). The method can be carried out using a processor of a device such as insulin pen, an insulin pump, a remote control device configured to remotely control an insulin pump or an insulin pen, a continuous glucose meter, a controller of a continuous glucose meter, a blood glucose meter, and a portable electronic device such as a smart phone, smart watch or tablet.

A computer-implemented method for predicting a risk whether a hypoglycemic event will occur during a prediction time interval is disclosed. The method comprises: providing user values for a plurality of machine learning input parameters, the user values determined from glucose monitoring data with glucose measurement values detected for a user before a cut-off time, the plurality of machine learning input parameters comprising: at least one first glucose measurement value determined from glucose measurements values measured within at most 10 minutes before the cut-off time, and a hypoglycemic event share value indicative of a share of previous prediction time intervals with detected hypoglycemic events out of a total number of previous prediction time intervals before the cut-off time; predicting, based on the user values and using a machine learning model, a risk whether a hypoglycemic event will occur during a prediction time interval associated with assumed sleep of the user, the machine learning model generated based on the machine learning input parameters and using historical glucose monitoring data of a user population; and generating an output based on the predicted risk. Further, a data processing system, a computer program, a system, and a remote control are disclosed.

Implantable device for measuring the glucose concentration of a body fluid when implanted, the implantable device comprising a glucose measurement unit, the glucose measurement unit comprising a first light source configured to emit light towards a light transmissive part of a housing of the device and a first optical sensor configured to detect light returned through the light transmissive part from the first light source, and output a first electrical signal based on the detected light; and a wireless communication module configured to wirelessly communicate with an external wireless communication device, wherein the wireless communication module is configured to wirelessly transmit a signal based on the first electrical signal to the external wireless communication device.

A device for continuously monitoring glucose levels in a patient includes a lead assembly in electrical communication with an electronics assembly. The electronics assembly is configured to be positioned in the subcutaneous tissue and the lead assembly is configured to be positioned in a vessel of the patient, such as in a vein or in an epidural space. The lead assembly has a lumen, and includes at least one electrode in electrical communication with the electronics assembly.

The present invention provides a biosensor for detecting glucose in saliva by using a saliva glucose measurement device, the biosensor comprising: an electrically insulated substrate; a plurality of electrodes disposed on the substrate and including a working electrode and a reference electrode for detecting glucose in the saliva; and a reagent layer disposed on the plurality of electrodes, wherein the reagent layer is disposed in a saliva inflow path which is located in the biosensor and configured to allow the saliva to flow thereinto. The reagent layer includes glucose dehydrogenase (GDH) and an electron transfer mediator, the saliva glucose measurement device is configured to apply a voltage to the working electrode and the reference electrode, the working electrode and the reference electrode are configured to transmit, to the saliva glucose measurement device, a current signal generated due to an oxidation / reduction reaction between the glucose dehydrogenase and the glucose in the saliva according to the applied voltage, and the value of the applied voltage is included in a numerical range of 150 mV to 300 mV.

In an embodiment, a system for mitigating diabetic ketoacidosis (DKA) risk for a patient in real-time includes a continuous glucose monitoring (CGM) system configured to generate one or more glucose measurements associated with a cunent glucose level of a patient over a period, one or more memories including executable instructions, and one or more processors in data communication with the one or more memories. The one or more processors are configured to execute the executable instructions to receive glucose measurements for the patient from the CGM system, receive insulin data for the patient, evaluate criteria associated with DKA using first information related to the glucose measurements and second information related to the insulin data, detect a risk of DKA for the patient responsive to a combination of the first information and the second information satisfying the criteria associated with DKA, and alert the patient based on the detected risk.

Systems and methods of optimizing glucose medication dosages are based on modeling a patient's glucose lowering response using historical glucose data. The model is actively updated to account for changes in the patient's medication treatments and physiological conditions based on real-time or near real-time glucose measurements from the patient. The system can analyze various dosages of insulin based on the patient's current therapy and the model to determine an optimized dosage. Also disclosed is a system and method for retrieving a patient's current medication therapies from medical records using an automated system. Also disclosed are methods of implementing remotely-updatable limitations for medication optimization algorithms.

A method, system, and computer readable medium for a dual mode closed loop control (CLC) system is provided that integrates each of (i) an adaptive, individualized model predictive control (MPC) control law that adjusts the control strength of insulin infusion as a function of recent past control actions, glucose measurements, and derivatives thereof, (ii) an automatic bolus priming system (BPS) that commands an extra insulin injection upon detection of a viable metabolic condition (e.g., an unannounced meal), and (iii) a hyperglycemia mitigation system (HMS) to avoid pervasive hyperglycemia.

Diabetes prediction using glucose measurements and machine learning is described. In one or more implementations, an observation analysis platform includes a machine learning model trained using historical glucose measurements and historical outcome data for a population of users to predict a diabetes classification for an individual user. The historical glucose measurements for the population of users can be provided by glucose monitoring devices worn by users of the population of users, while the historical outcome data includes one or more diagnostic measurements obtained from a source independent of the glucose monitoring devices. After training is complete, the machine learning model predicts a diabetes classification for a user based on glucose measurements collected by a wearable glucose monitoring device over an observation period spanning multiple days. The predicted diabetes classification can then be output, such as by generating one or more notifications or user interfaces based on the classification.

The present invention is a glucose monitoring device designed specifically for deaf individuals. The device comprises a housing containing components such as glucose monitoring circuitry for measuring glucose levels in blood samples. The front surface features a display screen that shows glucose readings and other relevant data. The housing is equipped with multiple bright flashing lights and a vibration motor to provide both visual and tactile alerts when glucose levels are abnormal. The alerts persist until acknowledged by pressing an acknowledgement button. Additionally, the device includes a pivotal stand on the rear surface, enabling the device to be angled for optimal visibility of alerts. The system also incorporates a wireless communication channel for transmitting real-time glucose measurements to a remote computing device, facilitating monitoring by users, guardians, or medical practitioners.

A method, system, and computer-readable medium are provided for a dual mode closed loop control (CLC) system that integrates each of (i) an adaptive, personalized model predictive control (MPC) control law that adjusts the control intensity of insulin infusion according to recent past control actions, glucose measurements, and derivatives thereof, and (ii) an adaptive, personalized model predictive control (MPC) control law that adjusts the control intensity of insulin infusion according to the recent past control actions, glucose measurements, and derivatives thereof. In one embodiment, the system includes (i) an insulin injection system (e.g., an automated meal dose initiation system (BPS) that commands additional insulin injection upon detection of viable metabolic conditions (e.g., unnotified feeding), and (iii) a hyperglycemia relief system (HMS) to avoid prevalent hyperglycemia.

Data describing glucose measurements is received from a continuous glucose monitoring (CGM) system worn by a user and predicted glucose values during a future time period are generated for the user based on the data. A determination is made that at least one of the predicted glucose values satisfies a threshold value for an alert, which is associated with a prediction horizon that defines an amount of time prior to satisfaction of the threshold value for communicating the alert to the user. Output of the alert is caused responsive to determining that the at least one predicted glucose value satisfies the threshold value for the alert within the prediction horizon, relative to a current time. The prediction horizon is modified based on a user response to the alert. Output of a subsequent instance of the alert is caused based on the modified prediction horizon.

Certain aspects of the present disclosure provide a monitoring system comprising one or more memories comprising executable instructions and one or more processors in data communication with the one or more memories and configured to execute the executable instructions to calculate a first reabsorption threshold based on glucose measurements and 1,5-AG measurements of a patient over a first period of time and calculate a second reabsorption threshold based on the glucose measurements and the 1,5-AG measurements of the patient over a second period of time. The one or more processors are further configured to detect a change of the second reabsorption threshold relative to the first reabsorption threshold; determine whether the change of the second reabsorption threshold relative to the first reabsorption threshold is an increase or a decrease; and provide therapy management guidance to the patient based on the increase or the decrease.

In an aspect, the present disclosure provides an insulin delivery device configured to be positioned on a body of a subject via a single puncture site in said body of said subject, wherein said insulin delivery device is configured to deliver an insulin or insulin analog formulation to said subject via said single puncture site, wherein said insulin delivery device comprises a sensor configured to measure a glucose concentration in said body of said subject via said single puncture site, and wherein said delivering and said measuring are performed at substantially the same time for a time period of at least 1 hour subsequent to said positioning, while maintaining a sensitivity of said sensor of at least 50% of an initial sensitivity of said sensor.

Methods and systems for encouraging interactions with a glucose monitoring system include incrementing a score and / or providing a reward based on a variety of different interactions with the glucose monitoring system. The interactions which improve the score may include initiating or changing displays, downloading data, setting operational parameters and other interactions that are independent of a user's glucose measurements. Encouraging these interactions can enhance success in maintaining healthy glucose concentrations.

A method, system, and computer-readable medium are provided for a dual mode Closed-Loop Control (CLC) system integrating each of (i) an adaptive, personalized Model Predictive Control (MPC) control law that modulates the control strength of insulin infusion depending on recent past control actions, glucose measurements, and their derivative(s), (ii) an automatic Bolus Priming System (BPS) that commands additional insulin injections upon the detection of enabling metabolic conditions (e.g., an unannounced meal), and (iii) a hyperglycemia mitigation system (HMS) to avoid prevailing hyperglycemia.

A device for continuously monitoring glucose levels in a patient includes a lead assembly in electrical communication with an electronics assembly. The electronics assembly is configured to be positioned in the subcutaneous tissue and the lead assembly is configured to be positioned in a vessel of the patient, such as in a vein or in an epidural space. The lead assembly has a lumen, and includes at least one electrode in electrical communication with the electronics assembly.

Multi-state engagement with continuous glucose monitoring (CGM) systems is described. Given the number of people that wear CGM systems and because CGM systems produce measurements continuously, a platform that provides a CGM system may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process. In implementations, a CGM platform includes a data analytics platform that obtains packages of glucose measurements provided by a CGM system and also obtains additional data associated with a user. The data analytics platform generates state information for the user by processing these CGM packages and the additional data, at least in part, by using one or more models. Based on this state information, the data analytics platform controls communication with the user, which may include generating intervention strategies to prevent users from transitioning to a negative state such as discontinuing use of the CGM system.

A continuous glucose monitoring system may utilize externally sourced information regarding the physiological state and ambient environment of its user for externally calibrating sensor glucose measurements. Externally sourced factory calibration information may be utilized, where the information is generated by comparing metrics obtained from the data used to generate the sensor's glucose sensing algorithm to similar data obtained from each batch of sensors to be used with the algorithm in the future. The output sensor glucose value of a glucose sensor may also be estimated by analytically optimizing input sensor signals to accurately correct for changes in sensitivity, run-in time, glucose current dips, and other variable sensor wear effects. Correction actors, fusion algorithms, EIS, and advanced ASICs may be used to implement the foregoing, thereby achieving the goal of improved accuracy and reliability without the need for blood-glucose calibration, and providing a calibration-free, or near calibration-free, sensor.

Presented is a medicament delivery system including a controller, a wearable medication delivery device, an analyte sensor, and other devices. In an example, a receiver is operable to receive glucose measurement values from the analyte sensor. A number of devices of the medicament delivery system may include a processor operable to execute programming code and to identify anomalous readings among the received glucose measurement values. The identified anomalous reading may, for example, be based on the received glucose measurement values violating a measurement change threshold indicative of abnormal sensor behavior. The processor may be operable to, in response to identifying the anomalous reading, revert a medicament delivery setting to a default safety basal delivery setting and / or generate a notification, an inquiry, and / or an alert for presentation to a user.

The invention discloses a conductive polymer with a synergistic effect, a preparation method of the conductive polymer and a biosensor containing the conductive polymer, and relates to the technical field of biosensors. The synthetic method of the conductive polymer with the synergistic effect comprises the following steps: preparing a first polymer, wherein the first polymer is obtained by grafting a transition metal complex with both amino and carboxyl onto poly (4-vinylpyridine) with amino or carboxyl; and reacting the prepared first polymer with a second polymer through a cross-linking agent to obtain the conductive polymer with the synergistic effect, when being used as a glucose biosensor, the biosensor has the advantages of extremely short polarization time, short response time and good glucose measurement linear range.

Various systems and methods are disclosed. One or more of the methods disclosed uses machine learning algorithms to predict biophysical responses from biophysical data, such as heart rate monitor data, food logs, or glucose measurements. Biophysical responses may include behavioral responses. Additional systems and methods extract nutritional information from food items by parsing strings containing names of food items.

A device for continuously monitoring glucose levels in a patient includes a lead assembly in electrical communication with an electronics assembly. The electronics assembly is configured to be positioned in the subcutaneous tissue and the lead assembly is configured to be positioned in a vessel of the patient, such as in a vein or in an epidural space. The lead assembly has a lumen, and includes at least one electrode in electrical communication with the electronics assembly.