Medtronic Minimed, Inc.

Lu Wang

Rajiv Shah

Wayne A Morgan

Barry Keenan

Richard S Yoon

John Joseph Mastrototaro

Desmond Barry Keenan

Yanan Zhang

John J Shin

Sami S Kanderian, Jr

John C Mueller, Jr

Kenneth W Cooper

Sami Kanderian

Nandita N Patel

Helen Lee

Richard Yoon

A method of calibrating glucose monitor data includes collecting the glucose monitor data over a period of time at predetermined intervals. It also includes obtaining at least two reference glucose values from a reference source that temporally correspond with the glucose monitor data obtained at the predetermined intervals. Also included is calculating the calibration characteristics using the reference glucose values and corresponding glucose monitor data to regress the obtained glucose monitor data. And, calibrating the obtained glucose monitor data using the calibration characteristics is included. In preferred embodiments, the reference source is a blood glucose meter, and the at least two reference glucose values are obtained from blood tests. In additional embodiments, calculation of the calibration characteristics includes linear regression and, in particular embodiments, least squares linear regression. Alternatively, calculation of the calibration characteristics includes non-linear regression. Data integrity may be verified and the data may be filtered.

Real time self-adjusting calibration algorithm

A system and method for calibrating a sensor of a characteristic monitoring system in real time utilizes a self-calibration module for periodic determination of, and compensation for, the IR drop across unwanted resistances in a cell. A current-interrupt switch is used to open the self-calibration module circuit and either measure the IR drop using a high-frequency (MHz) ADC module, or estimate it through linear regression of acquired samples of the voltage across the sensor's working and reference electrodes (Vmeasured) over time. The IR drop is then subtracted from the closed-circuit value of Vmeasured to calculate the overpotential that exists in the cell (Vimportant). Vimportant may be further optimized by subtracting the value of the open-circuit voltage (Voc) across the sensor's working and reference electrodes. The values of Vmeasured and Vimportant are then controlled by respective first and second control units to compensate for the IR drop.

Real-time self-calibrating sensor system and method

An implantable sensing system that includes a sensor for sensing a biological parameter, a processor connected to the sensor for processing the parameter and a drug delivery unit connected to the processor for responding to the processor based on the parameter. The processor is programmed to adjust an output of the sensor by compiling an array of data relating to the sensor, adjusting a sensor parameter a first time based on data in the array, adjusting a curve representing the sensor output based on data in the array and adjusting the sensor parameter a second time based on data in the array.

System and method for sensor recalibration

A method of calibrating glucose monitor data includes collecting the glucose monitor data over a period of time at predetermined intervals, obtaining reference glucose values from a reference source that temporally correspond with the glucose monitor data obtained at the predetermined intervals, calculating the calibration characteristics using the reference glucose values and corresponding glucose monitor data to regress the obtained glucose monitor data, and calibrating the obtained glucose monitor data using the calibration characteristics. In additional embodiments, calculation of the calibration characteristics includes linear regression and, in particular embodiments, least squares linear regression. Alternatively, calculation of the calibration characteristics includes non-linear regression. Data integrity may be verified and the data may be filtered.

Systems and methods for calibrating physiological characteristic sensors

A method and system that enables a user to maintain a sensor in real time. The present invention involves performing a diagnostic Electrochemical Impedance Spectroscopy (EIS) procedure to measure sensor impedance value in order to determine if the sensor is operating at an optimal level. If the sensor is not operating at an optimal level, the present invention may further involve performing a sensor remedial action. The sensor remedial action involves reversing the DC voltage being applied between the working electrode and the reference electrode. The reversed DC voltage may be coupled with an AC voltage to extend its reach.

Method and system for remedying sensor malfunctions detected by electrochemical impedance spectroscopy

A method and program prevents a user from bypassing a limit placed on a specified operating life of a sensor by disconnecting and reconnecting the sensor. The present invention checks a characteristic of the sensor to see if the sensor is used prior to the connection of the sensor, and rejects the sensor if the sensor is determined to have been used before. The process of checking the characteristic of the sensor involves performing an Electrochemical Impedance Spectroscopy (EIS) procedure and calculating an impedance value. The impedance value can be compared to various threshold values for a variety of purposes including the determination of age, condition, hydration, and stabilization of the sensor.

Method and system for detecting age, hydration, and functional states of sensors using electrochemical impedance spectroscopy

System and methods for calibrating physiological characteristic sensors

A system and method for calibrating a sensor. The method may include, without limitation, compiling an array of data relating to the sensor; adjusting a sensor parameter a first time based on data in the array; adjusting a curve representing the sensor output based on data in the array; and adjusting the sensor parameter a second time based on data in the array. The sensor may be an in vivo glucose sensor and the sensor parameter adjusted may be a current. The array may include historical as well as recent data, such as, for example, blood glucose readings and sensor electrode readings.

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Pasadena, CA, United States of America

Lu Wang