Medtronic Minimed, Inc.

Steven C Jacks

Peter Ajemba

Raghavendhar Gautham

Michael E Miller

Andrea Varsavsky

Keith Nogueira

Akhil Srinivasan

Jeffrey Nishida

Andy Y Tsai

Tri T Dang

Sarkis Aroyan

Rajiv Shah

Jacob E Pananen

Bradley Chi Liang

Pablo Vazquez

Daniel E Pesantez

Megan E Little

Ashley N Sullivan

Robert C Mucic

Mohsen Askarinya

Brian T Kannard

David Probst

Melissa Tsang

Chi-En Lin

Tyler R Wong

Jeffery Nishida

Medical devices and related systems and methods are provided. A method of controlling medication delivery based on sensor input involves obtaining a measurement parameter representing an electrical response of a first instance of a sensing element to a physiological condition of a person. The measurement parameter is converted into a calibrated measurement parameter using calibration data specific to the first instance of the sensing element. The method further involves determining a measurement value using the calibrated measurement parameter as input to a performance model. The performance model is derived from historical calibrated measurement parameters and corresponding reference values. The historical calibrated measurement parameters are from other instances of the sensing element. A command is then determined based on the measurement value and sent to a medical device. The command causes the medical device to deliver a dose of medication influencing the physiological condition of the person.

Medication delivery using calibrated sensor measurements

Techniques disclosed herein relate to determining a calibrated measurement value indicative of a physiological condition of a patient using sensor calibration data determined based on fabrication measurements. In some embodiments, the techniques involve obtaining one or more electrical signals from a sensing element of a sensing arrangement, where the one or more electrical signals are influenced by a physiological condition in a body of a patient; obtaining calibration data associated with the sensing element, where the calibration data is based on fabrication process measurement data for the sensing element and a calibration model for a certain physiological condition; and determining, using the one or more electrical signals and the calibration data associated with the sensing element, a calibrated output value indicative of the physiological condition.

Sensor measurement value calibration using sensor calibration data determined based on fabrication measurements

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.

Methods, systems, and devices for calibration and optimization of glucose sensors and sensor output

Techniques disclosed herein relate to determining a calibrated measurement value indicative of a physiological condition of a patient using sensor calibration data and a performance model. In some embodiments, the techniques involve obtaining one or more electrical signals from a sensing element of a sensing arrangement, where the one or more electrical signals are influenced by a physiological condition in a body of a patient. The techniques also involve obtaining calibration data associated with the sensing element from a data storage element of the sensing arrangement, converting the one or more electrical signals into one or more calibrated measurement parameters using the calibration data, obtaining a performance model associated with the sensing element, obtaining personal data associated with the patient, and determining, using the performance model and based on the personal data and the one or more calibrated measurement parameters, a calibrated output value indicative of the physiological condition.

Sensor measurement value calibration using sensor calibration data and a performance model

Medical devices and related systems and methods are provided. A method of calibrating an instance of a sensing element involves obtaining fabrication process measurement data from a substrate having the instance of the sensing element fabricated thereon, obtaining a calibration model associated with the sensing element, determining calibration data associated with the instance of the sensing element for converting the electrical signals into a calibrated measurement parameter based on the fabrication process measurement data using the calibration model, and storing the calibration data in a data storage element associated with the instance of the sensing element.

Sensor calibration using fabrication measurements

Medical devices, systems and methods are provided. One method involves obtaining fabrication process measurement data for a plurality of instances of a sensing element, obtaining reference output measurement data from the plurality of instances in response to a reference stimulus, determining a predictive model for a measurement output of the sensing element as a function of fabrication process measurement variables based on the relationship between the fabrication process measurement data and the reference output measurement data, generating a simulated output measurement distribution across a range of the fabrication process measurement variables using the predictive model, identifying performance thresholds for the measurement output based on the simulated output measurement distribution, obtaining output measurement data from the instance of the sensing element in response to the reference stimulus, and verifying the output measurement data satisfies the performance threshold prior to calibrating a subsequent instance of the sensing element.

Manufacturing controls for sensor calibration using fabrication measurements

A physiological characteristic sensor, a method for forming a physiological characteristic sensor, and a method for forming a platinum deposit having a rough surface are presented here. The method for forming a physiological characteristic sensor includes immersing a sensor electrode in a platinum electrolytic bath. Further, the method includes performing an electrodeposition process by sequentially applying a pulsed signal to the sensor electrode, wherein the pulsed signal includes a repeated cycle of a first current and a second current different from the first current, and applying a non-pulsed continuous signal to the sensor electrode, wherein the non-pulsed continuous signal includes a non-repeated application of a third current, to form a platinum deposit on the sensor electrode.

Physiological characteristic sensors and methods for forming such sensors

A physiological characteristic sensor, a method for forming a physiological characteristic sensor, and a method for forming a platinum deposit having a rough surface are presented here. The method for forming a physiological characteristic sensor includes immersing a sensor electrode in a platinum electrolytic bath. Further, the method includes performing an electrodeposition process by sequentially applying a pulsed signal to the sensor electrode and applying a non-pulsed continuous signal to the sensor electrode to form a platinum deposit on the sensor electrode.

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Culver City, CA, United States of America

Steven C Jacks