116 results about "Insulin infusion" patented technology

A closed loop therapy system for controlling a concentration of a substance, such as blood glucose concentration, in the body of a user. The system and method employ a sensor system that measures a glucose level in the body, a controller that uses the measured glucose levels to generate an output that can be used to automatically or manually control an intradermal insulin infusion system to set a constant or time-varying profile of target blood glucose concentrations in a user, and then infuse an appropriate amount of insulin into the body of the user so as to reach and maintain the target values of the blood glucose concentration.

The invention relates to a method which utilizes blood glucose (“BG”) sampling, insulin infusion / injection records, heart rate (“HR”) information and heart rate varability (“HRV”) information to estimate BG in the near future and to estimate of the risk of the onset of hypoglycemia. The invention also relates to an apparatus for predicting BG levels and for assessing the risk of the onset of hypoglycemia in the near future. The invention is based on two predetermined bio-mathematical routines: a network model of BG fluctuations and a BG profile for assessment of the risk of hypoglycemia.

A closed loop infusion system controls the rate that fluid is infused into the body of a user. The closed loop infusion system includes a sensor system, a controller, and a delivery system. The sensor system includes a sensor for monitoring a condition of the user. The sensor produces a sensor signal, which is representative of the condition of the user. The sensor signal is used to generate a controller input. The controller uses the controller input to generate commands to operate the delivery system. The delivery system infuses a liquid into the user at a rate dictated by the commands from the controller. Preferably, the sensor system monitors the glucose concentration in the body of the user, and the liquid infused by the delivery system into the body of the user includes insulin.

Present invention is a system of blood glucose monitoring and intensive insulin therapy in a ICU for strict maintenance of normoglycemia which reduces intensive care and hospital mortality and morbidity of critically ill adult patients. The findings of present study also reveal factors determining insulin doses needed to maintain normoglycemia as well as the impact of insulin dose versus blood glucose level on the observed outcome benefits have been established. The invention provides a control system that adapts the flow of the insulin infusion based on insulin requirement calculated by blood glucose levels and clinical parameters such as history of diabetes, Body Mass Index, blood glucose level on admission, reason of ICU admission, time in the ICU, type and severity of illness, caloric intake, obesity, drugs affecting insulin sensitivity). This automated insulin monitoring systems significantly reduces the workload and human resource management problems for intensive insulin therapy in patients in the ICU.

Present invention is a system of blood glucose monitoring and intensive insulin therapy in a ICU for strict maintenance of normoglycemia which reduces intensive care and hospital mortality and morbidity of critically ill adult patients. The findings of present study also reveal factors determining insulin doses needed to maintain normoglycemia as well as the impact of insulin dose versus blood glucose level on the observed outcome benefits have been established. The invention provides a control system that adapts the flow of the insulin infusion based on insulin requirement calculated by blood glucose levels and clinical parameters such as history of diabetes, Body Mass Index, blood glucose level on admission, reason of ICU admission, time in the ICU, type and severity of illness, caloric intake, obesity, drugs affecting insulin sensitivity). This automated insulin monitoring systems significantly reduces the workload and human resource management problems for intensive insulin therapy in patients in the ICU.

Provided are a measurement device by which the blood-sugar level or the like associated with the living activity of a diabetic patient can be measured easily and precisely and the measured valued associated with the living activity can be clinically applied easily, and an insulin infusion device, a measurement method, a method for controlling an insulin fusion device, and a program. A blood-sugar level measurement device (100) is provided with a blood-sugar level sensor (200) and an acceleration sensor (112) for measuring movement information associated with human body activity, wherein a CPU (110 controls, on the basis of the measured movement information, whether or not the measurement operation of a blood-sugar measurement circuit (113) can be executed. The CPU (110) further associates and records in a recording unit (111) the measured blood-sugar level and the movement information measured by the acceleration sensor (112), and displays the associated blood-sugar level and movement information on a display unit (102). The CPU (110) further combines the blood-sugar level measured by the blood-sugar level sensor (200) and the data detected by the acceleration sensor (112) and executes each mode processing.

A controller for an insulin infusion device includes a processor device and a memory element that cooperate to provide a processor-implemented closed-loop insulin limit module. The insulin limit module is operated to obtain: a fasting blood glucose value of a user; a total daily insulin value of the user; and fasting insulin delivery data that is indicative of insulin delivered to the user during a fasting period. The insulin limit module calculates a maximum insulin infusion rate for the user based on the fasting blood glucose value, the total daily insulin value, and the fasting insulin delivery data. The maximum insulin infusion rate is applicable during a period of closed-loop operation of the insulin infusion device.

A system and method for providing optimal insulin injections to a subject, using a controller, a continuous glucose monitor, and an insulin delivery unit is disclosed. The controller possesses a discrete-time, linear model predictive control law, means for sending information to the insulin delivery unit, and means for receiving information from the CGM. The control law implemented is derived from a discrete-time model of glucose insulin dynamics and an aggressiveness parameter. The result is that using only glucose measurements obtained from sensor readings and, prior values of external insulin infusion and meal and exercise announcement the optimal insulin injection necessary to safely regulate blood glucose can be calculated.

A method of managing use of an insulin infusion device are provided. The method receives glucose data for a user of the infusion device, wherein the glucose data indicates blood glucose levels of the user for a period of time during which the insulin infusion device is regulating delivery of insulin to the user. The received glucose data is received to detect certain event occurrences, which may be indicative of a correctable basal rate setting of the insulin infusion device and / or indicative of potential maladjustment of a user-specific setting of a bolus calculator setting of the insulin infusion device. The method outputs a recommendation to adjust the basal rate setting and / or the bolus calculator setting as needed to address the detected event occurrences.

Disclosed is a medical infusion device including a dedicated processing unit for detecting abnormal operation of the operation of the device. Specifically, a watchdog controller is employed as an independent monitor of the functioning of microprocessors used in the medical infusion device for controlling things such as RF communication, insulin infusion, and system integrity. Through the use of an independently-powered watchdog control system, the accuracy and reliability of the device is enhanced, resulting in greater assurance to the patient receiving periodic or continuous infusion of a drug.

A closed-loop system for insulin infusion overnight uses a model predictive control algorithm (“MPC”). Used with the MPC is a glucose measurement error model which was derived from actual glucose sensor error data. That sensor error data included both a sensor artifacts component, including dropouts, and a persistent error component, including calibration error, all of which was obtained experimentally from living subjects. The MPC algorithm advised on insulin infusion every fifteen minutes. Sensor glucose input to the MPC was obtained by combining model-calculated, noise-free interstitial glucose with experimentally-derived transient and persistent sensor artifacts associated with the FreeStyle Navigator® Continuous Glucose Monitor System (“FSN”). The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during simulated overnight closed-loop control with the MPC algorithm using the glucose measurement error model suggesting that the continuous glucose monitoring technologies facilitate safe closed-loop insulin delivery.

An electronic controller for an insulin infusion device includes at least one processor device and at least one memory element that cooperate to provide a processor-implemented closed-loop initiation module. The initiation module is operated to obtain a most recent calibration factor for a continuous glucose sensor, the most recent calibration factor representing a first conversion value applicable to convert a first sensor value to a first blood glucose value. The initiation module also obtains a prior calibration factor for the sensor, and calibration timestamp data for the most recent calibration factor and the prior calibration factor. The initiation module regulates entry into a closed-loop operating mode of the insulin infusion device, based on the most recent calibration factor, the prior calibration factor, and the calibration timestamp data.

A closed-loop system for insulin infusion overnight uses a model predictive control algorithm (“MPC”). Used with the MPC is a glucose measurement error model which was derived from actual glucose sensor error data. That sensor error data included both a sensor artifacts component, including dropouts, and a persistent error component, including calibration error, all of which was obtained experimentally from living subjects. The MPC algorithm advised on insulin infusion every fifteen minutes. Sensor glucose input to the MPC was obtained by combining model-calculated, noise-free interstitial glucose with experimentally-derived transient and persistent sensor artifacts associated with the FreeStyle Navigator® Continuous Glucose Monitor System (“FSN”). The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during simulated overnight closed-loop control with the MPC algorithm using the glucose measurement error model suggesting that the continuous glucose monitoring technologies facilitate safe closed-loop insulin delivery.

An electronic computing device as presented here includes a device communications layer, a processor device, and a reporting layer. The device communications layer receives sensor data for a user of an insulin infusion device, wherein the sensor data indicates blood glucose levels of the user for a specified period of time, and over a plurality of days. The processor device analyzes the received sensor data to detect an event occurrence indicative of a correctable basal rate setting of the insulin infusion device. The reporting layer generates a report containing a graphical representation of the received sensor data and a recommendation to adjust a basal rate setting of the insulin infusion device, wherein the recommendation is intended to address the detected event occurrence.

The lack of safe, reliable, automated and clinically acceptable blood sampling has been the main problem precluding the development of real-time systems for blood analysis and subsequent closed-loop physiological function control. While the analysis of a static blood sample in laboratory conditions has been rapidly advancing in reliability and blood volume reduction, non-invasive real-time blood analysis performed in vivo (while the blood is circulating in the body) has been elusive and unreliable. In this study we propose an innovative idea for semi-invasive blood sampling and analysis, which resembles the operation of a mosquito. At a miniature scale the proposed system does penetrate the skin to extract a static blood sample for further analysis, but the extent of this penetration, and the fact that it can be made painless, is particularly attractive for such applications as automated glucose analysis for closed-loop control of insulin infusion (artificial pancreas), continuous drug monitoring, or even periodic DNA analysis for security and identification purposes. These design aspects are described, and a specific implementation, applying MEMS (Micro Electro Mechanical Systems) technology, is suggested. The proposed microsystem is a matrix of individually controllable e-Mosquito™ cells, packaged in a disposable patch and attached to the skin, could be an avenue for real-time semi-invasive blood analysis and diagnostics.

Processor-implemented methods of controlling an insulin infusion device for a user are provided here. A first method obtains and analyzes calibration factors (and corresponding timestamp data) for a continuous glucose sensor, and regulates entry into a closed-loop operating mode of the infusion device based on the calibration factors and timestamp data. A second method obtains a most recent sensor glucose value and a target glucose setpoint value for the user at the outset of the closed-loop mode. The second method adjusts the closed-loop insulin infusion rate over time, in response to the sensor glucose value and the setpoint value. A third method calculates an upper insulin limit that applies to the insulin infusion rate during the closed-loop mode. The insulin limit is calculated based on a fasting blood glucose value of the user, a total daily insulin value of the user, and fasting insulin delivery data for the user.

An electronic device includes a processor architecture and a memory element that stores instructions that, when executed by the processor architecture, perform a method of controlling an insulin infusion device for a user. The method operates the device in a closed-loop mode to deliver insulin to the user, obtains current insulin-delivered data and current glucose sensor data for the user, and processes historical insulin-delivered data and historical sensor data, to obtain predicted sensor glucose values for a historical time period. The method continues by calculating a difference between the current sensor glucose value and a predicted current sensor glucose value for the most recent sampling period. An alert is generated when the difference exceeds a threshold error amount.

Methods and apparatuses providing accessibility options for the blind and poorly sighted for use with insulin therapy systems. A remote control device, with speech output capability and comprehensive speech menu system, may monitor or intercept data generated by a blood glucose meter, and delay, modify and retransmit said data to an insulin pump. The remote control device may also be used to program and set operating parameters of an insulin pump and also record data received from an insulin pump. The remote control device may also be used in conjunction with a personal computing device.

An insulin infusion set (30) for use with an inserter (40) is disclosed. The infusion set (30) includes an extension set (50). The extension set (50) includes a housing (70), a base (90) and a latching device (82). The base (90) houses a base septum (120) and an infusion cannula (42). The latching device (82) releasably attaches the housing (70) to the base. When the housing (70) is attached to the base (90), a part of the housing (70) extends into and opens the base septum (120).

The invention relates to a device and method for treating diabetic patients on insulin therapy. More specifically, the invention includes apparatus for infusing insulin into a patient in an amount determined by the patient's carbohydrate intake, blood glucose level, and the amount of insulin calculated to be present in the patient at the time the therapy is to be administered. In one embodiment, an insulin infusion device having an on-board processor obtains a patient's blood glucose value from a remote sensor and receives input from a user indicating their recent meal intake. The device may include an on-board food database for determining the carbohydrate content of the patient's recent meals and compare that with recent insulin deliveries into the patient to determine the insulin present in the patient prior to determining an appropriate insulin dosage.

A controller for an insulin infusion device includes at least one processor device and at least one memory element that cooperate to provide a processor-implemented closed-loop start-up module. The start-up module is operated to initiate a closed-loop mode of the infusion device and to obtain a most recent sensor glucose value for the user. The start-up module also calculates a difference between the most recent sensor glucose value and a target glucose setpoint value. When the difference is less than or equal to a threshold value, the closed-loop insulin infusion rate is adjusted over time, based on a fixed final target glucose value that is derived from the target glucose setpoint value. When the difference is greater than the threshold, the infusion rate is adjusted over time, based on a dynamic final target glucose value that decreases over time toward the target glucose setpoint value.

An insulin infusion device includes a processor architecture, and a memory element that stores executable instructions to perform a method of controlling delivery of insulin to a user. The method operates the device in a closed-loop mode to deliver insulin, obtains patient-specific parameters for a current time sample, and estimates a plasma insulin value and a blood glucose value for the user based on at least some of the patient-specific parameters. The estimating is also based on a previously estimated plasma insulin value obtained for a previous time sample, and a previously estimated blood glucose value obtained for the previous time sample. A predicted sensor glucose value is generated for the current time sample, and the closed-loop mode or a safe basal mode is selected for controlling operation of the insulin infusion device in accordance with the selected mode.

A method of controlling an insulin infusion device is presented here. The method can be implemented in a suitably configured electronic device, on an electronic storage medium, or the like. In accordance with certain embodiments, the method evaluates the operational integrity of a glucose sensor that measures sensor glucose values for a user of the insulin infusion device, and calculates a sensor integrity metric based on the evaluation. The calculated sensor integrity metric is used to adjust the aggressiveness of a closed-loop therapy algorithm that is used to control a closed-loop operating mode of the insulin infusion device. The insulin infusion device is operated in the closed-loop operating mode in accordance with the adjusted therapy setting.

An insulin infusion device (1A) is disclosed. The device includes a body (3A), cannula (70) housed in the body (1A), a cannula insertion device (10, 20, 23) and a cannula retraction device (20, 23, 30). When the cannula insertion device is activated, the cannula (70) extends at least partly out of the body (1A) and into an infusion site and when the cannula retraction device is activated after the cannula insertion device has been activated, the cannula (70) retracts into the body (1A).

An electronic controller for an insulin infusion device includes a processor architecture and at least one memory element. The memory element stores executable instructions that, when executed by the processor architecture, provide an insulin on board (IOB) compensation module to estimate a current IOB value that indicates an amount of active insulin in the body of the user, calculate an IOB rate based at least in part on the estimated current IOB value, determine an adjusted insulin infusion rate based at least in part on the calculated IOB rate and an uncompensated insulin infusion rate, select a final insulin infusion rate for the device, and provide the selected final insulin infusion rate to regulate delivery of insulin by the device.

The present invention describes an active overlay of real-time glucose and / or insulin information on a display for convenient monitoring and control of information for the management of diabetes. The superimposed images on display can be varied based on automated and / or programmable processes and / or alerts of the system. In various embodiments, the system can include a console and / or remote control to allow the user to control the overlay display. In specific embodiments, the system can communicate with a glucose sensor and / or insulin infusion device.