Medtronic, Inc.

Medtronic Minimed, Inc.

Covidien LP

David Probst

Mohsen Askarinya

Randal C Schulhauser

Patrick W Kinzie

Daniel Hahn

Akhil Srinivasan

Santhisagar Vaddiraju

Melissa Tsang

Chi-En Lin

James Kevin Carney

Mark D Breyen

Thomas P Miltich

Jennifer Lorenz Marckmann

Alejo Chavez Gaxiola

Robert C Mucic

Mark R Boone

Michael E Miller

Jian L Cao

Shantanu Sarkar

John Wainwright

Michael D Eggen

Richard J O'Brien

Peter Ajemba

Steven C Jacks

Tyler R Wong

Kathryn Hilpisch

Jadin C Jackson

Kamal Deep Mothilal

Matthew L Plante

Xin Heng

Eric C Maass

Aaron Gilletti

Robert Mckinlay

Amruta Paritosh Dixit

Riley Clayton Kimball

Wally Dong

Brennan Toshner

Ning Yu

Kenneth A Timmerman

Stanley J Taraszewski

Matthew A Joyce

Laura M Zimmerman

Kathryn Ann Milbrandt

John P Keane

Vu Nguyen

Parisa Kamgar

Mark Phelps

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

A method of testing one or more analyte sensors each comprising a first electrode; a second electrode; and a material layer disposed on or above the first electrode; the method including (a) applying a voltage potential to the first electrode with respect to the second electrode; (b) measuring a test signal comprising an output current from the first electrode that results from the application of the voltage potential; (c) using the test signal from (b) to observe an electrical characteristic of the analyte sensor; and (d) correlating the electrical characteristic a parameter associated with an electrochemical response of the analyte sensor to an analyte, wherein the testing is under dry conditions without exposure of the electrodes to a fluid containing the analyte or an in-vivo environment containing the analyte.

Dry electrochemical impedance spectroscopy metrology for conductive chemical layers

This disclosure is directed to systems and techniques for detecting change in patient health based upon patient data. In one example, a medical system comprising processing circuitry communicably coupled to a glucose sensor and configured to generate continuous glucose sensor measurements of a patient. The processing circuitry is further configured to: extract at least one feature from the continuous glucose sensor measurements over at least one time period, wherein the at least one feature comprises one or more of an amount of time within a pre-determined glucose level range, a number of hypoglycemia events, a number of hyperglycemia events, or one or more statistical metrics corresponding to the continuous glucose sensor measurements; apply a machine learning model to the at least one extracted feature to produce data indicative of a risk of a cardiovascular event; and generate output data based on the risk of the cardiovascular event.

Detection of changes in patient health based on glucose data

An embodiment of a sensor device includes a base substrate, a circuit pattern formed overlying the interior surface of the substrate, a physiological characteristic sensor element on the exterior surface of the substrate, conductive plug elements located in vias formed through the substrate, each conductive plug element having one end coupled to a sensor electrode, and having another end coupled to the circuit pattern, a multilayer component stack carried on the substrate and connected to the circuit pattern, the stack including features and components to provide processing and wireless communication functionality for sensor data obtained in association with operation of the sensor device, and an enclosure structure coupled to the substrate to enclose the interior surface of the substrate, the circuit pattern, and the stack.

Waferscale physiological characteristic sensor package with integrated wireless transmitter

An example medical device includes an optical sensor, processing circuitry, an antenna, and a power source. The optical sensor includes a light source; a reference optical beacon having a first fluorophore that emits a first fluorescence proportional to a first concentration of a substance proximate the beacon; a test optical beacon having a reagent substrate that reacts with an analyte to produce the substance and a second fluorophore that emits a second fluorescence proportional to a second concentration of the substance proximate the test beacon; and a photodetector to detect the first and second fluorescence. The processing circuitry determines a difference between the first and second fluorescence, which is indicative of the concentration of the analyte. The antenna and power source enable the medical device to operate completely within a biological system for continuous analyte monitoring.

Optical based glucose sensor

A biocompatible medical device may include an electrochemical sensor including a common reference electrode; at least one counter electrode; and a work electrode platform comprising a plurality of respective work electrodes, each respective work electrode electrically coupled to the common reference electrode and comprising a respective reagent substrate configured to react with a respective analyte to produce a respective signal indicative of a concentration of the respective analyte; and processing circuitry operatively coupled to the electrochemical sensor, and configured to receive from the electrochemical sensor a plurality of signals from the plurality of respective work electrodes; identify the respective signal corresponding to a respective selected work electrode; and process the identified signal to determine the concentration of the respective analyte associated with the respective selected work electrode.

Electrochemical sensor including multiple work electrodes and common reference electrode

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

In some examples, an apparatus configured to be worn by a patient for cardiac defibrillation comprises sensing electrodes configured to sense a cardiac signal of the patient, defibrillation electrodes, therapy delivery circuitry configured to deliver defibrillation therapy to the patient via the defibrillation electrodes, communication circuitry configured to receive data of at least one physiological signal of the patient from at least one sensing device separate from the apparatus, a memory configured to store the data, the cardiac signal, and a machine learning algorithm, and processing circuitry configured to apply the machine learning algorithm to the data and the cardiac signal to probabilistically-determine at least one state of the patient and determine whether to control delivery of the defibrillation therapy based on the at least one probabilistically-determined patient state.

Wearable defibrillation apparatus configured to apply a machine learning algorithm

An enzymatic sensor configured to determine the concentration of levodopa present in a sample according to a current or a resonant frequency produced in response to levodopa interactions with L-amino acid decarboxylase present in the sensor. A processor associated with the sensor determines levodopa concentration and produces dose recommendation or output according to levodopa concentration.

Levodopa sensor for tight tuning of dosage

The invention includes method and materials designed to measure the material properties (e.g. thickness) of layers of material in a sensor using non-Faradaic EIS (Electrochemical Impedance Spectroscopy) methods. The methods are non-destructive, very sensitive and rapid. Typically in these methods, an AC voltage is applied to the desired material layer while the output current and therefore impedance is measured. This voltage can be applied in multiple frequencies in sweep mode in order to detect both the material and, for example, the thickness of the target material. In this way, EIS allows the characterization of properties of various layers of material disposed in devices such as electrochemical glucose sensors.

Measurement of device materials using non-Faradaic electrochemical impedance spectroscopy

An electrochemical sensor may include a common reference electrode, at least one counter electrode, and a work electrode platform including a plurality of respective work electrodes. Each respective work electrode of the plurality of respective work electrodes may be electrically coupled to the common reference electrode and include a respective reagent substrate configured to react with a respective analyte to produce a signal indicative of a concentration of the respective analyte.

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Chandler, AZ, United States of America

David Probst