Medtronic, Inc.

Warsaw Orthopedic, Inc.

Medtronic Minimed, Inc.

Medtronic Xomed, Inc.

Covidien LP

Medtronic Vascular, Inc.

Patrick W Kinzie

Randal C Schulhauser

Richard L Brown

Mohsen Askarinya

David Probst

Emily Clare Byrne

Daniel Hahn

Santhisagar Vaddiraju

Matthew M Morrison

Jeffrey R VanRaaphorst

Avram Scheiner

William C Harding

James Kevin Carney

Mark D Breyen

Thomas P Miltich

Jadin C Jackson

Akhil Srinivasan

Jennifer Lorenz Marckmann

Jeff M Cherry

Alejo Chavez Gaxiola

Ryan H Gertenbach

Michael J Ferguson

Eduardo N Warman

Eric J Panken

David C Hacker

Colin A Chong

John Wainwright

Tyler S Stevenson

Aaron Gilletti

Julia Slopsema

Joe Don Sartor

Jian L Cao

Richard J O'Brien

Eric M Christensen

Paul G Krause

David J Miller

Jason C Lee

Eric C Maass

Osvaldo Andres Barrera

Martha De Cunha Maluf-Burgman

Gerard A Bast

Sneha Saikia

Dorothy Dominiack

Brian D Pederson

Brian Lee Bechard

Mark Phelps

A system for detecting strokes includes a sensor device configured to obtain physiological data from a patient, for example brain activity data. The sensor device can include electrodes configured to be disposed at the back of the patient's neck or base of the skull. The electrodes can detect electrical signals corresponding to brain activity in the P3, Pz, and/or P4 brain regions or other brain regions. A computing device communicatively coupled to the sensor device is configured to receive the physiological data and analyze it to indicate whether the patient has suffered a stroke.

Systems and methods for detecting strokes

A system including a range of motion, quality of sleep, overall, and control modules. The range of motion module, prior to a procedure being performed on a patient, determines a first range of motion score of the patient based on a first signal generated by a sensor. The quality of sleep module, prior to the procedure being performed on the patient, determines a first quality of sleep score or a first pain score based on the first signal. The overall module determines a combined score based on the first range of motion score and the first quality of sleep score or the first pain score. The control module compares the combined score to a predetermined threshold and predicts an outcome of the procedure based on the comparison. The control module, based on the combined score, determines whether to perform the procedure, adjust the procedure or refrain from performing the procedure.

Systems and methods for pre-operative procedure determination and outcome predicting

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

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

A method of implanting a lead includes inserting a needle through tissue near a chin of a patient and through a tongue of the patient, inserting an introducer through an opening created by the needle, and inserting the lead through the introducer, the lead comprising an elongated member and one or more electrodes in a distal portion of the elongated member such that the one or more electrodes are implantable proximate to one or more motor points of a protrusor muscle within the tongue of the patient, wherein inserting the lead comprises inserting the lead to have a shape of one of a helix, a compound helix, a wave shape, or saw-tooth shape, or to have a loop in the lead.

Medical lead for treating obstructive sleep apnea (OSA) with electrical stimulation

A sleep apnea and obesity comorbidity treatment system includes a transceiver and a control module. The control module is configured to: receive sensor data, where the sensor data is indicative of a glucose level of a patient and a ketones level of the patient, transmit the sensor data to a remote feedback device, receive feedback information from the remote feedback device based on the sensor data, and where the feedback information provides indications to the patient to maintain or alter a behavior of the patient based on the glucose level and the ketones level, and based on the feedback information, performing an operation to maintain or alter at least one of a diet or physical activity of the patient.

Personalized and contextualized treatment of sleep apnea and obesity comorbidity

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

Methods, systems, and devices for creating a model of a medical device for use in an extended reality (XR) system are described. The method may include receiving a three-dimensional model of the medical device, where the three-dimensional model is represented by a plurality of vectors. The method may further include reducing a number of the plurality of vectors to at least below a maximum vector count threshold while maintaining at least a minimum model resolution threshold. In some cases, the method may include assigning one or more components to the reduced number of the plurality of vectors. The method may further include configuring a software-executable file for displaying an XR version of the three-dimensional model of the medical device.

Extended reality assembly modeling

A lead for delivering electrical stimulation therapy is described. The lead includes an elongated member defining a longitudinal axis, one or more electrodes disposed at a distal end of the elongated member, a plurality of collars located along the longitudinal axis, and one or more fixation members. At least one of the fixation members is a bow-like member having a first connection point to a first collar of the plurality of collars and a second connection point to a second collar of the plurality of collars. The distal end of the elongated member is configured for insertion in a tongue of a patient such that the one or more electrodes are implanted proximate to one or more motor points of a protrusor muscle within the tongue of the patient and the bow-like member of the one or more fixation members is implanted within tissue of the tongue.

Growing community of inventors

Glendale, AZ, United States of America

Patrick W Kinzie