191 results about "Continuous glucose monitoring" patented technology

System and method for communicating glucose concentration information between devices of a continuous glucose monitoring system is provided. The continuous glucose monitoring system can include a sensor module generates a glucose concentration measurement data and transmits the data to one or more further devices of the continuous glucose monitoring system. The further devices can include a receiver unit and one or more secondary display devices. The receiver unit can be configured to be a stand-alone device of or physically connect to a secondary display device. A user interface can also be provided that provides enhanced functionality for using the continuous glucose monitoring system.

The invention is embodied in a system for diabetes management including a medical device (MD) and a consumer electronic device (CED). The CED may be used to monitor and/or control the MD. In particular embodiments, the system may include a connector that plugs into the CED to allow communication between the MD and the CED. The medical device may be an external infusion device, implantable pump, glucose meter, glucose monitor, continuous glucose monitoring system, or the like. The CED may be any type of consumer electronic device including, but not limited to, cellular phones, personal digital assistants (PDAs), BlackBerry, Smartphones, pocketpc phones, mp3 players, radios, CD players, and the like.

The use of electrical impedance spectroscopy to adjust calibration settings in an in vivo monitoring system, such as an in vivo continuous glucose monitoring sensor. The adjustments can compensate for the condition of the sensor membrane in vivo.

Embodiments of the present invention provide a new system and methods for monitoring blood glucose concentration. A user of a continuous glucose monitor may program upper and lower blood glucose notification thresholds to fluctuate over time in order to facilitate management of the short-term effects of food consumption, insulin delivery aberrations, physical activity, emotions, and unforeseen circumstances.

A medical device for predicting a user's future glycemic state includes a memory module, a processor module and a user alert module. The memory module is configured to receive and store a plurality of glucose concentrations as a function of time that were generated by a user's use of a continuous glucose monitor. The processor module is configured to derive first and second glucose prediction equations that are fits to the plurality of glucose concentrations stored in the memory module with the fits being based on first and second mathematical models, respectively. The processor module is also configured to calculate first and second predicted glucose concentrations at a future time using the first and second glucose prediction equations, respectively, and to also calculate an average predicted glucose concentration and a merit index based on the first and second predicted glucose calculations. The processor module is further configured to input the plurality of glucose concentrations as a function of time, the average predicted glucose concentration and the merit index into a trained model (e.g., a Hidden Markov Model) that outputs a set of glucose concentration probabilities for the future time and to then predict the user's future glycemic state based on the set of glucose concentration probabilities. The user alert module is configured to alert the user in a manner dependent on the predicted user's future glycemic state.

A method for individualized management of diabetes in insulin-dependent patients provides a period of evaluation as the patient adheres to a structured pattern of eating, sleeping, and physical activity. Glucose is monitored with a continuous glucose monitoring system, insulin doses are metered, carbohydrate consumption is quantified, and glucose, carbohydrate, and insulin data are collected and analyzed. Insulin dosage is adjusted in three steps: (1) an insulin dosage is estimated from conventional formulas, (2) adjustments are made according to the patient's clinical specifics, and (3) further insulin dose adjustments are made according to glucose data obtained during the evaluation period. By the end of the evaluation period, substantially normal glucose values are achieved, and quantitative relationships from data are calculated that are then applied to determine insulin dosages for an ensuing period of therapy. By this method, diabetic patients achieve a near normal glycemic profile, and without significant occurrence of hypoglycemic episodes.

In a method of recalibrating continuous glucose monitoring data from a user, operable on a digital processor, an indication from the user that the user has taken a meal is received (806). A self-monitored of blood glucose levels from the user (810) at two separate times during a day corresponding to when the user has taken a meal. A glucose signal is received from a continuous glucose monitoring sensor (818) at times corresponding to the two separate times that the user has taken a meal. Two reconstructed blood glucose values based on the glucose signal from the continuous monitoring sensor at times when the at least two self-monitored of blood glucose levels are received from the user. A linear regression is performed (822) using y=ax+b, wherein x corresponds to the two reconstructed blood glucose values and y corresponds to the two self-monitored of blood glucose levels thereby generating an estimation of a and b. A recalibration signal, including the estimation of a and b, is transmitted to the continuous glucose monitoring sensor (824) based on the linear regression.

Continuous glucose monitoring (CGM) data and insulin delivery data are used to generate more reliable projected alarms related to a projected glucose levels. A memory stores endogenous data related to measurements of glucose level in a patient, and also stores exogenous data, such as insulin on board, both of which are used by a processor to create projected alarms. Profiles of CGM data are created for use in tuning patient-specific insulin data, such at basal rate, carb ratio, and insulin sensitivity. A processor searches for patterns in the data profiles and if found, recommended changes to patient-specific insulin data are provided to permit more accurate control over a patient's glucose levels.

A system and method for reducing the number of hypoglycemic alarms presented to a user is presented. The system and methods include use of model based state estimation and variable-delayed threshold values to balance the risk of not presenting an alarm caused by an actual hypoglycemic state with the presentation of alarms caused by artifacts in the signals produced by a continuous glucose monitor.

An embodiment may be in the field of glycemic analysis and control. More specifically, an embodiment or approach may provide a novel method, system, and computer program for the visual and quantitative tracking of blood glucose variability in diabetes from self-monitoring blood glucose (SMBG) data and/or continuous glucose monitoring (CGM) data. More particularly, an embodiment or aspects thereof may use glucose measurements obtained from self-monitoring data and/or CGM data of an individual or a group of individuals to track and analyze blood glucose variability.

The present embodiments harness a wide variety of capabilities of modern smartphones, and combine these capabilities with information from a continuous glucose monitor to provide diabetics and related people with more information than the continuous glucose monitor can provide by itself. The increased information provides the diabetic with an increased likelihood of good diabetes management for better health.

A machine for processing continuous glucose monitoring data and issuing an alert if hypoglycemia is imminent has three modules: (a) a pre-processing module that receives and modulates continuous glucose monitoring data by reducing noise and adjusting for missed data points and shifts due to calibration; (b) a core algorithm module that receives data from the pre-processing module and calculates a rate of change to make a hypoglycemia prediction, and determine if hypoglycemia is imminent; and (c) an alarm mode module that receives data from the core algorithm and issues an audio or visual alert or warning message or a negative feedback signal to an insulin delivery device if hypoglycemia is imminent.

An inserter assembly for continuous glucose monitoring with medication delivery capability where the assembly has a deployment button containing a needle deployment mechanism having a sharp held in a pre-release position, a housing body in which the deployment button is movably received within a top end of the housing body, the housing body having a sensor deployment assembly containing a lumen and a sensor disposed within the lumen and extending out of the lumen to a circuit board that is part of the sensor deployment assembly, the sensor deployment assembly matingly connected to the sharp where the sharp extends beyond the sensor deployment assembly and contains the sensor not fixedly attached to the sharp, and a sensor housing releasably received within a lower end of the housing body, the sharp extending into a sensor deployment assembly recess within the sensor housing and directly above a sensor opening in a bottom of the sensor housing.

A system for predicting hypoglycemia based on continuous blood glucose monitor values is provided. The hypoglycemia detection algorithm is a set of individual alarms that are combined through a voting system into one combined alarm. The system could have five components and an overall voting algorithm that produces a binary alarm outcome depending on the number of constituent algorithms that report an alarm. A controller system automatically shuts off the insulin pump when pending or real hypoglycemia has been reached. The algorithms operate in a closed loop and automatically take action when the subject is asleep.

The various embodiments of the present invention provide a system and method for a fully mobile, non-invasive, continuous system for monitoring the cardiovascular and musculoskeletal health of an individual during exercise. The system includes one or more wearable devices affixed on the User with a chest strap or adhesive sticker, coupled with an application running on a computing device (smartphone/smartwatch), which performs various computations on the wearable device, or a smart phone/smart watch, or the cloud, and provides the user or the concerned personnel with various insights about the general health of the user. The exercise health monitoring system further enables the Users to get real time alerts during exercise or running, by way of vibrations or audio messages or notifications on the gateway device when they have an event of arrhythmia or cardiac fatigue, or they cross prescribed ranges of one or more of the following parameters: PEP, LVET, CO, HR, Shock, Braking Force, Sway.

A physiological condition monitoring system (e.g., a continuous glucose monitoring system) includes a physiological condition meter and a physiological condition sensor. The physiological condition meter and the physiological condition sensor are be placed in proximity to exchange a secret key using a near field wireless link, which is used to encrypt data to secure a radio frequency (RF) wireless channel.

The invention provides an intelligent method based on model predictive control for automatic infusion of large doses of insulin, which is characterized in that: a continuous glucose monitoring system (CGMS) and an insulin pump are used as the basis of hardware; online detection of food is carried out based on a strong tracking filter; when the food is detected, large doses of insulin is transfused immediately, and the amount of insulin depends on historical food; whether the dosage is needed to be increased is judged every 30 minutes based on the model predictive control, and the dosage is designed; when the blood glucose concentration decreases, whether the basic amount of insulin is needed to be maintained is determined according to the predicted blood glucose value; and finally the blood glucose concentration is controlled to be within the safe range. Compared with the existing corresponding technology, the invention has the advantages of high degree of intelligence and fully automatic operation, and the blood glucose control effects can be improved significantly in case that self-management cannot be carried out by patients.

The subject matter disclosed herein provides methods for presenting glucose level data. Glucose data for a patient may be received. A current glucose level and a rate of change of the current glucose level may be determined based on the received glucose data. A first interface may be displayed on a screen of a device. The first interface may include a unitary icon. The unitary icon may display the current glucose level and a visualization of the rate of change. Related apparatus, systems, techniques, and articles are also described.

This disclosure describes systems and methods for conducting and terminating spontaneous breathing trials on patients receiving mechanical ventilation. The disclosure describes a novel spontaneous breathing trial manager for a medical ventilator with rapid initiation and continuous monitoring of a patient's tolerance of the spontaneous breathing trial and displaying of that tolerance as a function of time, which provides for bedside adjustment of the spontaneous breathing trial parameters and automatic termination of a spontaneous breathing trial based on a time interval expiration or poor patient tolerance of the SBT.